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Top Agent Cards for 2026

2026-08-13T03:52:06Z

What Are Agent Cards?

Agent cards are scoped payment credentials that let an AI agent spend on a consumer's behalf without ever holding the consumer's real card number.

Visa, Mastercard, Amex, and Stripe all launched their own agent card programs between 2025 and 2026, each with different rules on reusability, approval flow, and fees.
Most purchases still require human approval as of mid-2026 — agents aren't yet spending fully autonomously.
Liability, security, and fee structures remain unresolved across the industry, and a separate, more fragmented set of protocols (AP4M, x402, MPP, AP2) is emerging for business-to-business and machine-to-machine payments.

AI agents can now research a purchase, compare options, and negotiate on your behalf — but for most of their history, they've hit a wall at checkout. Someone still had to type in a card number. That changed in 2025 and 2026, as major card networks and fintechs began issuing agent cards: payment credentials designed specifically for an autonomous AI agent to spend on a person's behalf, without ever handing over the person's real card details.

What Problem Do Agent Cards Solve?

Handing an AI agent your actual card number creates three potential problems:

Merchant trust: A merchant receiving a checkout request has no way to tell a legitimate AI agent acting on a real customer's behalf from a bot or bad actor impersonating one.
Consumer authorization: There's no standard way to prove which agent is authorized, what it's allowed to buy, and how much it's allowed to spend — without a human approving every single transaction.
Accountability: If an agent buys the wrong item, buys too much of something, or gets manipulated into an unwanted purchase, there's no established process for who's liable and how the transaction gets reversed.

Agent cards address all three with one mechanism: a credential that's cryptographically scoped to a specific agent, a specific spending policy, and a specific consumer. That scoping is what lets a merchant verify the agent instead of guessing, defines exactly what and how much the agent can buy without a human approving each purchase, and ties every transaction back to a traceable consent record if something goes wrong.

Agent Cards Compared: Fees, Reusability, and Approval

Product	Network/Issuer	Card type	Reusable?	Approval required?	Fees
Visa Intelligent Commerce / Trusted Agent Protocol	Visa (via issuing bank); layers onto OpenAI/Stripe's ACP inside ChatGPT	Wraps whatever Visa credit, debit, or prepaid card the consumer already links	Reusable, scoped to spending limits and an approved-merchant list	Yes — consumer gets a notification to approve each purchase in early rollout	No separate consumer fee disclosed; standard Visa interchange applies. Commercial terms of the ChatGPT integration specifically are undisclosed
Mastercard Agent Pay	Mastercard (Citi and US Bank were first issuers)	Wraps an existing Mastercard credit or debit card via a tokenized "Agentic Token"	Reusable by default — one token per agent, scoped at setup (e.g. "groceries only," a monthly cap); can also be issued single-use or time-limited	Not a live per-tap prompt — consent and scope are set upfront; a separate "Verifiable Intent" record documents what was asked for	No separate consumer fee disclosed; standard Mastercard interchange applies
American Express ACE Developer Kit + Agent Purchase Protection™	Amex	Amex credit/charge cards	Not yet publicly detailed	Not yet publicly detailed	No separate consumer fee disclosed
Stripe Issuing for Agents + Link	Stripe (issued via bank partners, on Visa/Mastercard rails)	Prepaid/debit-style virtual cards drawing from a funded Issuing balance, not revolving credit	Supports true single-use cards, capped to one merchant, one transaction, or a set amount	Configurable by the developer/business issuing the card, not a fixed consumer prompt	$0.10 per virtual card issued, plus 0.2% + $0.20 per transaction after the first $500K in volume (waived below that)
AgentCard (Alchemy)	Built on Visa Intelligent Commerce	Wraps whatever Visa card the consumer links	Inherits Visa Intelligent Commerce's scoping options	Inherits Visa's approval flow	Not publicly disclosed
InFlow	Built on Visa Intelligent Commerce	Wraps whatever Visa card the business/consumer links	Inherits Visa Intelligent Commerce's scoping options	Inherits Visa's approval flow	Not publicly disclosed

Where a fee isn't publicly disclosed, that's because most of these products aren't separate card products with their own pricing — they're a tokenization/authorization layer sitting on top of a card the consumer already has, so the applicable fee is whatever that underlying card's rate already is. Reusability and approval flows vary by issuer configuration rather than being fixed to the product — the table reflects the default or most commonly described setup as of mid-2026.

1. Visa Intelligent Commerce / Trusted Agent Protocol

Tell ChatGPT you want wireless headphones under $150, and it finds a qualifying pair and completes the purchase — that's Visa's own example of what its integration with OpenAI enables. Visa's Trusted Agent Protocol issues a Verified Agent ID alongside a consent record signed by the consumer's card issuer, so a merchant can confirm both that the agent is legitimate and that the consumer actually authorized it. Inside ChatGPT specifically, this sits on top of an existing layer rather than replacing it: ChatGPT's checkout has run on the Agentic Commerce Protocol (ACP) since September 2025, an open standard co-developed by OpenAI and Stripe, in which Stripe issues a Shared Payment Token (SPT) that lets ChatGPT initiate a payment without ever seeing the buyer's card details. Visa's June 2026 integration adds Visa's own tokenization, agent identification, and fraud-monitoring infrastructure on top of that protocol, letting eligible cards use network-level tokenized credentials for agent-initiated purchases inside ChatGPT and OpenAI's Codex. By December 2025, Visa reported hundreds of controlled, real-world agent-initiated transactions and projected millions of consumers would use agent checkout by the 2026 holiday season.

Features

Reusable: Yes, within set spending limits and an approved-merchant list, until the consumer revokes access
Approval: In the early rollout, the agent sends a notification and the consumer approves each purchase before it's completed; Visa expects this to loosen as trust builds
Fees: Rides on standard Visa interchange; the specific commercial terms of the Visa/ChatGPT integration haven't been disclosed

2. Mastercard Agent Pay

Launched in April 2025 with Microsoft, IBM, and Braintree as initial partners, Agent Pay issues an "Agentic Token" — an extension of Mastercard's existing tokenization infrastructure (MDES) — that represents a cardholder's card, scoped to one agent and one commerce policy. Citi and US Bank were the first two issuers to give their cardholders access. Microsoft's Copilot Checkout, built on Agent Pay, launched to consumers in January 2026 in partnership with PayPal.

Features

Reusable: Yes by default — one token per agent, scoped at issuance (e.g., category, monthly cap, day-of-week restrictions); can also be configured as single-use
Approval: No live per-transaction tap; consent and scope are set upfront, with a separate "Verifiable Intent" record capturing what the consumer actually asked for
Fees: No separate consumer fee disclosed; standard Mastercard interchange applies; revocation of a specific agent's access is real-time through the issuer's app

3. American Express Agentic Commerce Experiences (ACE) Developer Kit

Amex released its Agentic Commerce Experiences (ACE)™ Developer Kit in April 2026, a framework covering five integrated services: agent registration (verifying which AI agents are trusted to transact), account enablement (letting a cardmember register a card for agentic use), intent intelligence (capturing purchase intent for authentication and disputes), tokenized payment credentials, and cart-context sharing for validation. Alongside it, Amex announced Amex Agent Purchase Protection™ — a pledge, described as an industry first, to protect cardmembers from charges caused by a registered AI agent's error, provided the agent transmitted authenticated purchase intent at the time of the transaction. This is the clearest explicit liability commitment among the major networks so far; Visa and Mastercard haven't published an equivalent guarantee.

Features

Reusable / approval flow: Not yet publicly detailed beyond the five ACE services above
Fees: No separate consumer fee disclosed

4. Stripe Issuing for Agents + Link

Rather than creating a new type of credential, Stripe extended its existing card-issuing infrastructure: agents get programmatic access to a consumer's Link wallet, and can be issued one-time-use virtual cards or a Shared Payment Token backed by the cards and bank accounts already saved in that wallet. This is a lower-friction option for merchants already built on Stripe. The trade-off: Visa and Mastercard's frameworks issue an identity credential — a Verified Agent ID or Agentic Token — that any merchant on their network can independently check against the issuer; Stripe's cards are recognized as legitimate within Stripe's own processing relationship with a merchant, not via a shared, cross-network identity standard.

Features

Reusable: Configurable — supports genuine single-use cards capped to one merchant, one transaction, or a set dollar amount
Approval: Set by whichever business or developer is issuing the card, not a standard consumer-facing prompt
Fees: $0.10 per virtual card issued, plus 0.2% + $0.20 per transaction after the first $500K in volume (waived below that) — this is a platform/developer cost, not a disclosed consumer surcharge

5. AgentCard (Alchemy)

Alchemy's AgentCard integrates with Visa Intelligent Commerce to give an agent what the company describes as a complete identity-and-payment stack, provisioned through a single API. Alchemy's stated use cases — an agent booking travel, ordering groceries, or renewing a subscription for a consumer without that consumer touching a checkout screen — are the company's own examples of intended use rather than independently confirmed case studies; no third-party reporting confirms these specific scenarios happening at scale.

Features

Reusability / approvals / fees: Inherits whatever Visa Intelligent Commerce offers underneath, since AgentCard is a layer on top rather than a separate credential

6. InFlow

InFlow describes itself as "B2AI" infrastructure — Visa Intelligent Commerce supplies the underlying payment credentials and merchant acceptance, while InFlow layers on identity, multi-currency wallet functionality, and a policy-governed payments engine so a business can safely let agents transact on its behalf.

Features

Reusability / approvals / fees: Same as above — inherits Visa Intelligent Commerce's mechanics; InFlow's own pricing isn't publicly disclosed

Are Agent Cards Safe?

Agent cards solve the mechanical problem of letting an agent pay, but several key questions remain unresolved:

Liability: Who absorbs the cost when an agent makes an erroneous or unauthorized purchase? Amex is the clearest case so far, with its named Amex Agent Purchase Protection™ commitment; Visa and Mastercard haven't published an equivalent guarantee yet.
Security: An agent's payment credential is a new attack surface — credential theft or prompt injection during an automated checkout flow could result in unauthorized spending in ways that don't map cleanly onto existing card-fraud playbooks.
Regulation: Consumer protection law was written with a human pressing "buy" in mind. Regulators haven't yet settled how existing rules on authorization, disputes, and chargebacks apply when an AI agent is the one initiating the transaction.
Fragmentation: Visa, Mastercard, Amex, and various fintechs are each building their own agent-credential standard. Whether these converge into something interoperable, or remain a patchwork merchants have to integrate with individually, is still an open question.
Fee economics: No network currently discloses a separate consumer-facing surcharge for agent-initiated purchases — but merchant-side fees, and merchant appetite for them, have already reshaped one major product. OpenAI began charging a 4% transaction fee to US Shopify merchants using ChatGPT's Instant Checkout starting January 26, 2026 (PYMNTS). By March 2026, OpenAI scaled back in-chat, product-listing checkout — reportedly after only about a dozen of the millions of eligible Shopify merchants had actually integrated, and while OpenAI still lacked its own system for collecting and remitting US sales tax — in favor of routing purchases through integrated retailer apps like Instacart, Target, and Expedia (Forbes). The underlying open standard, the Agentic Commerce Protocol, is still active and still being developed for that app-based model; what's changed is the scope of direct, in-chat checkout, not the protocol itself. The commercial terms of Visa's newer card-network-level integration with ChatGPT remain undisclosed.

What's Next for AI Agent Payments?

Everything above is consumer-facing: a credential tied to one person's spending authority. A separate, faster-moving, and more fragmented landscape is emerging for a different problem: businesses and AI agents paying each other directly, often in stablecoins, at machine speed and often in fractions of a cent. Mastercard's Agent Pay for Machines, Coinbase's x402, Stripe's Machine Payments Protocol, and Google's AP2 are all built by different companies, solve overlapping but distinct pieces of that problem, and aren't interchangeable with one another. None of them are cards — they're payment protocols and settlement rails, and untangling how they actually relate to each other deserves its own explainer.

The Bottom Line

By mid-2026, giving an AI agent a way to pay stopped being a novelty and became a real, if still early-stage, product category. The mechanics — tokenized credentials, issuer-signed consent, spending policies — are converging across networks even as the branding differs. The open questions now are less about whether agents can pay, and more about who's accountable when they get it wrong.

The $43M Regulatory Gap in Asia’s Prediction Markets

2026-08-12T01:52:42Z

As prediction markets scale globally, their legal treatment diverges sharply by region. The US and UK have absorbed them into existing derivatives and betting frameworks, while most of Asia lacks any comparable regulatory path, leaving billions in liquidity flowing offshore untaxed and unsupervised. This report by Tiger Research and Limitless examines why that institutional gap exists and what building a regulatory foundation for prediction markets in Asia would require.

Key Takeaways

Asian markets lack the regulatory architecture needed to classify prediction markets, forcing regulators to leave them in a gray area.
Western jurisdictions leverage existing frameworks like derivatives regulation in the US or betting laws in the UK, which create clear entry paths for operators and establish regulatory oversight.
The absence of a framework in Asia does not suppress market activity, as evidenced by significant liquidity flowing into offshore platforms, but it prevents tax collection and consumer protection.
Building a regulatory foundation requires a public deliberative process to determine whether prediction markets should be treated as derivatives, gambling, or a new third category.

1. Definition and the Importance of Classification

Prediction markets have value as information platforms, as Tiger Research's earlier report on prediction markets established, but the law has never drawn a clean line between them and gambling.

That raises the question of how the law defines gambling, and in particular betting.

Section 9 of the UK’s Gambling Act 2005 broadly defines the subject matter of betting as follows, and brings any such activity within the scope of gambling regulation once monetary value attaches to it.

the outcome of a race, competition or other event or process,
the likelihood of anything occurring or not occurring, or
whether anything is or is not true.

Under this legal definition, prediction markets attach economic value to the outcome of a specific event or the determination of a fact, which means they share much of their structural core with betting, the central element of gambling.

The core of the regulatory debate ultimately comes down to a question of definition: whether to 1) bring prediction markets within the traditional gambling regulatory framework, 2) reclassify them under a financial architecture such as derivatives, or 3) establish them as an independent category through separate legislation.

2. The West: How Institutional Pathways Produced Different Outcomes

Compared to Asia, Western jurisdictions have a more permissive stance toward prediction markets, but not because of a cultural tolerance for gambling. It reflects the availability of institutional architecture that allows them to bypass a direct confrontation with gambling law. The main pathways were as follows.

United States: Prediction markets were classified as derivatives (swaps) under the Commodity Exchange Act and brought within the existing registration framework.
United Kingdom: The market was accommodated within a general-purpose “betting intermediary” licensing regime.
European Union: Where contracts are classified as financial instruments, a binary options ban applies; where that classification is avoided, strict national gambling laws present a second barrier.

The consistent pattern is that institutional incorporation was only possible in jurisdictions that possessed an alternative regulatory framework, derivatives law or a flexible licensing regime, independent of gambling statutes.

2.1. United States: Extending the Definition of Derivatives

The United States accommodated prediction markets not by endorsing the gambling framing but by applying the existing contract structure of the Commodity Exchange Act (CEA) in a purposeful way.

Commodity Futures Modernization Act of 2000 (CFMA): Established the foundation through an open-ended definition of “excluded commodity,” which allowed non-financial variables such as election outcomes and weather events to be classified alongside conventional commodities such as crude oil.
Dodd-Frank Act of 2010: Gave the CFTC two critical powers:
1. Exclusive federal jurisdiction over event contracts.
2. The authority under Rule 40.11 to prohibit individual contracts related to terrorism, assassination, war, and gaming.

Neither statute was designed with prediction markets in mind, but together they created the legal basis for treating such contracts as financial agreements rather than gambling. They also established a centralized regulatory counterparty in the CFTC, replacing what would otherwise have been a fragmented process of state-by-state lobbying.

The legal architecture that accumulated over time produced a market ordered around licensed entities.

In November 2020, Kalshi secured Designated Contract Market (DCM) status, allowing it to sell a broad range of event contracts to retail investors. Polymarket, after a 2022 enforcement action, moved toward regulatory compliance through its 2025 acquisition of licensed exchange QCEX.

2.2. United Kingdom: Incorporation Through a General Licensing Framework

Rather than treating prediction markets as an extension of derivatives, the UK approached them as a form of betting and used the existing Gambling Act 2005 to accommodate them within the regulatory perimeter. Three provisions were particularly important.

Section 9: Defines betting broadly enough to provide a flexible legal foundation for prediction markets.
Section 13, “betting intermediary”: Captures the structural feature of prediction markets precisely, as they match contracts between users rather than taking direct positions themselves.
Section 65(4): Allows the licensing categories to be adjusted by ministerial order, giving the framework the capacity to absorb new market models without separate legislation.

In February 2026, the Gambling Commission clarified that prediction market platforms fall within the “betting intermediary” category and must obtain the corresponding license. Rather than a blanket prohibition, this constituted a clearly defined entry path, with strict penalties for unlicensed operation on one side and an open registration window on the other.

Despite this established framework, the major global platforms have been cautious about entering the UK market, for reasons rooted in their US litigation strategy.

Both Kalshi and Polymarket have staked considerable legal argument on the position that prediction contracts are financial derivatives rather than gambling. Obtaining a UK “betting intermediary” license would formally designate them as gambling operators, which would undermine their legal position in ongoing US proceedings.

This gave the UK a market environment shaped differently from the global standard, one that in practice created ideal conditions for UK-local operators to build their business. Matchbook, an existing betting exchange, drew on its betting intermediary license to launch “Matchbook Predictions” in January 2026, and Versus, a newer entrant, obtained a UKGC general betting license and launched its own prediction market.

2.3. Europe: Dual Closure Under Financial and Gambling Regulation

The regulatory landscape on the European continent combines financial regulation under MiFID II with individual national gambling laws to form a two-layer barrier.

Any contract classified as a financial instrument immediately encounters the binary options prohibition.
Any contract that escapes that classification then faces strict national gambling definitions.

In July 2026, the European Securities and Markets Authority (ESMA) made the financial regulation dimension explicit in an official statement, which stated that the binary payout structure of event contracts falls squarely within the scope of the binary options ban. This effectively closed the financial product route into the European market.

Prediction markets face equally difficult conditions under gambling law. France is the clearest illustration: the Autorité Nationale des Jeux (ANJ) implemented a phased enforcement escalation that concluded by classifying prediction market operations as illegal gambling.

The one exception is Gibraltar. In July 2026, Gibraltar designed a dedicated legislative framework, the Prediction Market Regulations, that defines prediction markets as a distinct “third category.” This is a strategy of creating a new pathway rather than working within the existing frameworks, but as Gibraltar is not an EU member state, the approach has the limitation of not being subject to mutual recognition within Europe.

The closed structure in Europe is not necessarily permanent, however. The European Commission has currently made the legal treatment of prediction markets a formal item under review as part of its Markets in Crypto-Assets Regulation (MiCA) review process. Depending on the conclusions of the report due in June 2027, the door remains open to a shift toward a new institutional framework for accommodating prediction markets.

3. Asia: The Present State of Institutional Absence

Asian jurisdictions have two structural obstacles that do not exist in the same form in Western markets.

State-controlled gambling licensing: There is no general-purpose licensing framework capable of accommodating private sector innovation in the manner of the UK’s “betting intermediary” category. Licensing authority is allocated through state-controlled monopoly structures.
Constraints on financial product classification: The financial laws of South Korea and Japan use closed, positive-list definitions of underlying assets, which makes the kind of broad reclassification the US achieved through the concept of “non-financial contingent events”, legally unavailable.

As the Western cases demonstrate, whether a prediction market takes hold depends on which path defines it, either existing financial product architecture or gambling regulation. The fundamental constraint facing Asian markets, however, is that neither classification system offers an institutional foundation capable of accommodating this new business model.

Legal betting markets already exist across Asia, in Japan, South Korea, Singapore, and Hong Kong, so any view that denies the market on grounds of emotional resistance or cultural specificity diverges considerably from the actual situation.

The central question, then, is not whether the market is socially accepted, but how a regulatory foundation could be designed to accommodate this new market model.

3.1. South Korea: Absent Architecture and Criminal Enforcement as the Default

Domestic discussion of prediction markets has not reached the stage of debating their legal status or social value. The existing regulatory framework treats them as speculative products by default, which cuts off substantive deliberation before it can begin.

The relevant statutory provisions are already in conflict with how prediction markets operate. The Act on Special Cases Concerning Regulation and Punishment of Speculative Acts covers “prize businesses,” defined as businesses that distribute money or property in exchange for correctly predicting the outcome of a specific event. This is structurally similar to what prediction markets do.

The legal question is not fully resolved, however. Prize business law presupposes a casino-style structure in which the operator directly controls the stake pool. Modern platforms such as Polymarket use a matching architecture in which the operator facilitates contracts between users rather than holding funds directly. No judicial interpretation has yet addressed how this structural difference would be treated under existing statutes.

The financial regulatory route is also closed. The Capital Markets Act uses a positive-list approach to defining underlying assets. While financial indicators are covered, there is no explicit basis for classifying non-financial variables such as election outcomes as derivatives.

Because the right to operate betting businesses is in any case reserved for state-monopoly entities, private platforms cannot enter the market through this channel either.

3.2. Japan: Sophisticated Workarounds and the Limits of an Informal Practice

Prediction markets in Japan have followed a pattern of regulatory workaround rather than institutional incorporation.

The method local platforms have adopted resembles the three-shop system, a mechanism that originated in the pachinko industry, in that it physically severs the direct cash flow within the operating process.

Platform operator: The platform blocks direct cash deposits and instead runs a free reward model based on activities such as watching advertisements. It also eliminates any cash exchange function within the platform itself, which removes “gain or loss through property” as a defining element of gambling.
Reward issuer: A third party independent of the platform issues the reward, such as a gift certificate, for a successful prediction. Separating the platform operator from the issuing entity removes the legal risk of the operator becoming a direct party to the exchange of rewards for cash.
External cash-out market: A peer-to-peer transfer market and affiliated merchants outside the platform form the ecosystem where the reward is actually spent or converted into cash. Because the operating platform does not participate in this distribution process, the structure remains independent and avoids meeting the legal elements of the offense of gambling.

This is ultimately an informal commercial practice that emerged in a regulatory grey zone rather than a structure built on firm legal footing. Global platforms are either blocked from the Japanese market or operating under strict constraints through cryptocurrency exchanges. The substantive level of policy discussion in Japan is not materially different from that in South Korea.

4. What Asian Markets Are Forgoing

The absence of institutional architecture in Asia does not mean that the market does not exist. More than $52 million (approximately ₩72.8 billion) in liquidity flowed into prediction markets tied to South Korea’s June 2026 local elections, demonstrating that user participation in offshore platforms has already crossed a meaningful threshold even without a domestic regulatory framework. These transactions fall outside the tax system, consumer protection mechanisms are absent, and market integrity oversight is impossible.

Regulators face three available responses:

Extend existing criminal statutes to impose sanctions (the current South Korean approach).
Use technical means to block platform access entirely (the Singapore model).
Bring prediction markets within the regulatory perimeter, capturing tax revenue and supervisory authority in the process.

Only the third option can precisely achieve the practical regulatory objectives of tax collection, consumer protection, and market transparency.

Global annual transaction volume in prediction markets is projected to exceed $200 billion in 2026. Assuming conservatively that South Korean domestic users account for 1% of that volume, transaction volume attributable to any given Asian market would reach $2 billion. Depending on the tax model adopted, that would generate estimated new annual tax revenue of between $4 million and $43.2 million.

The more important point is not the size of these figures in isolation. Without regulatory accommodation, these transactions will not disappear; they will continue in an unregulated environment. Regulators will forgo both tax and supervisory authority while continuing to bear administrative and criminal enforcement costs.

5. Reframing the Regulatory Approach to Prediction Markets

As noted above, the institutional accommodation of prediction markets depends on which existing regulatory architecture, gambling or financial product, is used to define them.

Gambling regulatory framework: This path adapts existing Asian models for state-approved speculative activities, such as sports betting pools or integrated resort casinos. It is consistent with the state monopoly structure and can be justified through the public fund rationale, but it has inherent limitations in accommodating the business models of private platforms.
Derivatives regulatory framework: This represents the most operationally viable path with the least legal friction. It would involve fine-tuning the definition of financial products, drawing on precedents such as the acceptance of non-financial variables under Japan’s Financial Instruments and Exchange Act (FIEA) or on the language of “economic risk” in Korea’s Capital Markets Act. This approach avoids direct conflict with existing state gambling monopolies while pre-empting concerns about speculation and market manipulation by limiting eligible underlying assets to publicly verifiable statistical variables.
Creation of a standalone third category: This involves designing a dedicated legislative framework, as Gibraltar has done. It allows for the most precise regulatory calibration but carries the highest legislative and political costs, given the absence of precedent.

It is worth noting that this is a long-term institutional undertaking rather than a near-term outcome. In many Asian jurisdictions, basic public discourse on the legal identity of prediction markets has not yet formed. Securing the legislative momentum necessary for any of these paths requires first establishing a public deliberative process and building broad social consensus on the value of prediction markets.

One point worth noting is that prediction markets remain an unfamiliar concept across Asia, and no entity has taken the lead in shaping discourse around the prediction market. As a result, even the most basic agenda items have yet to be discussed.

Precisely analyzing how prediction markets function overall requires a formal public forum, such as a public-private roundtable, built around the core issues raised above, and establishing one is now an urgent priority.

Even once that level of discussion is set, an entity capable of carrying it onto the actual policy table is essential. Specialized research organizations such as Limitless Research demonstrate data-driven forecasting models in practice, and in doing so play a central role in establishing the market’s value system and shaping public discourse.

The process by which organizations with specialized analytical capacity, beginning with Limitless Research, demonstrate the reliability and public value of their data will be the decisive catalyst that elevates the fragmented discourse on prediction markets into a core agenda item within the institutional system.

Prediction markets carry distinct benefits and risks, though reaching an institutional conclusion before that debate has even taken place would be a hasty approach that overlooks the core issue. What is needed now is the constructive discourse that has not yet occurred.

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Disclaimer

This report was partially funded by Limitless. It was independently produced by our researchers using credible sources. The findings, recommendations, and opinions are based on information available at publication time and may change without notice. We disclaim liability for any losses from using this report or its contents and do not warrant its accuracy or completeness. The information may differ from others’ views. This report is for informational purposes only and is not legal, business, investment, or tax advice. References to securities or digital assets are for illustration only, not investment advice or offers. This material is not intended for investors.

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Crypto Hacks/Exploits Through The Years 2016-2026

2026-08-07T03:08:12Z

Since 2016, DeFi projects and crypto exchanges have lost over $14.27B to hacks and exploits. This figure is conservative — it does not account for individual wallet hacks or the secondary damage caused by an erosion of trust and liquidity across the ecosystem.

2022 remains the single costliest year on record at $2.77B, narrowly ahead of 2021's $2.66B. 2026 has logged 164 separate incidents through early August, more than any full prior year (2025's 97 is the next-highest). Some of that is likely better detection and tracking rather than a stark increase in attacks, though anecdotally, the pace has felt faster in recent years too with talks of AI being major contributing factors.

2023 and 2024 saw a decline in hacks amid the post-FTX bear market, before a sharp uptick in 2025 as crypto recovered, driven in large part by the infamous $1.4B North Korea-linked hack of crypto exchange Bybit.

2026 Hacks In a Nutshell

In 2026, April alone accounted for $644.9M, more than half of everything lost to hacks in the first seven months of the year, and it happened almost consecutively one after the other. Drift Trade was hit first on April 1 ($295M), then Kelp followed just over two weeks later on April 18 ($293M). Though hit by separate hacking groups, both exploiters were allegedly linked to North Korean state hackers.

Of these two hacks, the Kelp exploit caused structural damage throughout DeFi. Attackers found a weakness in Kelp's LayerZero bridge, minted roughly $293M of unbacked rsETH out of thin air, and dumped it straight into Aave as collateral to borrow real assets. Aave's TVL fell from $25.93B on April 17 to $21.80B just two days later, and the damage didn't stop there. By July 21, Aave's TVL had continued sliding to $14.40B, a 44.5% decline from its pre-hack level, part of a broader wipeout of trust across DeFi lending that has yet to reverse.

What Happens to Governance Tokens Post-Hack?

Hacks create a second category of financial damage that falls on the holders of the affected protocol's governance token, who lose money on the market's reaction even if they had no direct exposure to the exploit itself. Step Finance is the worst-case example: its exploit left the protocol insolvent, Step Finance has since shut down entirely, and STEP is down 99.4%.

Drift* and Resolv are still operating, but their tokens haven't recovered either: DRIFT is down 80.2% since its April 1 exploit, and RESOLV is down 71.7% since March. BONK, the most recent hack on this list (July 6), shows that market reaction can be costlier than the exploit itself: BonkDAO's treasury was drained of $21.3M through a malicious governance vote, yet BONK's token lost $138.65M in market capitalization since.

Note: Drift has renamed to Velocity and has not yet relaunched their platform. It remains to be seen if the platform can bounce back from their massive hack

Methodology

Yearly totals (2016-2026) combine the DeFiWatch REKT Database (2018-2022) with DeFiLlama's hack tracker (2023-2026, snapshot taken August 5, 2026); 2026 figures are year-to-date through August 3-5, 2026, and not a complete-year total.

Monthly 2026 breakdowns are sourced entirely from the DeFiLlama snapshot; a second Verus-Ethereum Bridge incident in July ($7.53 million) has been folded into that month's "Others" total rather than shown separately, since May's Verus-Ethereum Bridge incident is the one specifically named in this analysis.

Governance token market cap figures use CoinGecko daily price and market cap data, with a pre-hack baseline calculated as the 7-day average market cap ending the day before each hack, compared against the most recent available data (August 4, 2026). Hacked protocols without an independently-tradeable governance token of their own (including exchanges, bridges without native tokens, and hardware wallets) are excluded from the token-level analysis (chart 3). KernelDAO's KERNEL was used in place of rsETH for the Kelp exploit specifically because this analysis measures governance-token market impact, not TVL or redemption flows.

If you cite these insights, we would appreciate a link credit to this article on CoinGecko, which allows us to keep supplying you with useful data-led content.

This study is for illustrative and informational purposes only, and is not financial advice.

Appendix: Raw Data

Year	Total Lost	Incidents
2016	$60M	n/a
2017	$157.7M	n/a
2018	$1.13B	n/a
2019	$390M	n/a
2020	$570M	17
2021	$2.66B	71
2022	$2.77B	67
2023	$1.52B	97
2024	$1.27B	94
2025	$2.55B	97
2026 (YTD)	$1.2B	164

The number of hacking incidents pre 2020 is marked as n/a as a reliable count of incidents cannot be established.

SEC Eyes DeFi Risk Curators as $25.9B Market Faces Scrutiny

2026-08-07T01:59:12Z

On July 22, 2026, SEC Commissioner Hester Peirce issued a statement titled "Headstands and Summervaults," identifying on-chain vaults and lending strategies as potential subjects of existing securities law. This report by Tiger Research examines the parties likely to be affected and how the industry is responding.

Key Takeaways

Applied broadly, the legal reasoning could extend beyond vaults and curators to discretionary products generally, a segment representing approximately $25.9 billion in TVL.
The SEC is not targeting code that operates outside its reach. It is targeting the human actors who exercise discretion over that code.
Teams building compliance-oriented DeFi protocols, including Steakhouse Financial and Maple Finance, have been anticipating and preparing for exactly this kind of regulatory attention.
Historical precedent suggests that only two outcomes have proven durable: full registration under existing securities law, or the creation of new statutory exemptions through legislation.
The responses currently available to market participants are, at best, interim measures. Only curators with sufficient capital to build post-action compliance infrastructure will retain their market position. Smaller curators without those resources will be displaced.

1. The SEC Is Targeting Discretion, Not Code

On July 22, 2026, SEC Commissioner Hester Peirce issued a statement titled “Headstands and Summervaults,” arguing that the Howey Test, the legal standard established by a 1946 Supreme Court decision, could be applied to on-chain vaults and lending strategies under existing securities law.

The Howey Test evaluates the economic substance of how capital is raised and managed. It does not require new legislation or regulatory rulemaking to be applied. It is a fact-based standard that has been consistently applied to new financial instruments regardless of their technical form. An on-chain vault or decentralized lending strategy, however sophisticated its blockchain architecture, could qualify as an investment contract under securities law if its structure satisfies the test’s three core criteria. When all three are met, the product is classified as a security.

The statement carries no immediate enforcement authority, as it reflects the view of a single commissioner. It is, however, the first instance in which the SEC Crypto Task Force’s developing framework has been mapped onto specific products, and it has prompted concern among relevant market participants.

MORPHO, the token of the vault infrastructure protocol Morpho, fell roughly 5% immediately after the announcement.

If this legal reasoning were to be applied in practice, the regulatory target would almost certainly not be the smart contracts that power the vaults. It would be the risk curators and the DeFi actors who exercise real discretion over how assets are deployed. The vault infrastructure that Morpho has built is a technical instrument for asset management, and code with no controlling party is not a natural subject of direct regulatory sanction.

2. Why Curators Are the Target

Curators determine how much capital is allocated across a vault and what level of risk that capital is exposed to. In that sense, they exercise genuine discretion over depositors’ assets. The vault itself is simply a tool through which curators manage those assets. Most vaults are built as smart contracts deployed without admin keys or upgrade permissions, meaning even the original deployer cannot halt their operation or alter their logic.

Financial regulation, as it has historically operated, presupposes the existence of an identifiable legal entity capable of receiving a subpoena, having assets frozen, or complying with a cease-and-desist order. Immutable code with no controlling party has no such administrator.

The regulatory consequence is that enforcement attention has moved from code to discretion. Earlier cases involving Tornado Cash and Uniswap Labs illustrate the pattern.

The Tornado Cash case turned on whether immutable code could constitute sanctionable property. The Uniswap Labs case asked whether the company operating a non-custodial interface had effectively functioned as an unregistered broker or exchange. Both cases focused on the legal status of code and the act of running a service. Neither reached the question of investment discretion as a basis for securities liability.

This case is different. The operative question is no longer who built the protocol but who selects which assets a depositor’s capital is exposed to, how much is allocated to each market, and how interest rate conditions and collateral parameters are adjusted to influence returns. Consider a curator that selects specific lending markets from a broader set, withdraws capital when risk rises, and shifts weight toward higher-yielding markets. Depositors place their capital with that curator because they trust its judgment, not because they trust the underlying smart contract. Returns and losses flow directly from the curator’s decisions. That pattern of professional discretion exercised on behalf of depositors is precisely what gives rise to the “expectation of profits from the efforts of others” that the Howey Test identifies as a defining feature of an investment contract.

The curator is the most clearly identifiable party exercising that discretion within the on-chain vault ecosystem. That is why it sits at the center of the regulatory frame.

3. Which Categories Fall Within Scope

If this legal reasoning is applied broadly, its reach does not stop at risk curators. The SEC’s analytical focus is on who is making investment decisions on behalf of users.

Liquid restaking operators decide which validators or actively validated services (AVSs) receive asset allocations. Yield aggregators compare returns and risk across lending and liquidity markets and move capital accordingly. On-chain asset allocation services adjust holdings and weights over time. Where a specific team or operator is making ongoing decisions about asset selection and reallocation, the function is materially similar to that of a curator.

The relevant scope is therefore wider than the vault product category alone. Whether any specific service falls within it depends on who, within that service, is selecting assets, changing allocations, and controlling exposure to loss. Aggregating potential exposure across categories defined by that criterion produces a total TVL of approximately $25.9 billion.

The legal standard is unlikely to be applied uniformly across all of these participants. Its intensity will vary with the structure of the discretion involved.

At higher risk, where regulatory scrutiny would be most intense, are structures in which discretion is exercised opaquely in ways depositors cannot verify on-chain in real time, such as off-chain delegation and undercollateralized lending.
At medium risk are standard vault curators and liquid restaking structures that exercise allocation discretion, with capital flows recorded transparently on-chain and constrained by governance mechanisms such as timelocks and guardian roles.
At lower risk, and closest to compliance, are immutable protocol deployments with no controlling party, and financial products already registered under securities law.

The parties most accurately positioned to assess their own legal exposure are the operators themselves. This is why curators and adjacent market participants began developing tailored responses, including investor qualification restrictions, third-party compliance arrangements, and formal private placement exemptions, before the commissioner’s statement was issued.

4. Four Design Approaches to Reducing Regulatory Exposure

The responses developed to date do not resolve the underlying legal question. They are focused primarily on reducing the probability of regulatory application and limiting the legal liability of the operating entity.

Two analytical axes separate the approaches: whether a recognized legal exemption has been obtained, and whether actual asset allocation authority has changed. Measured against those criteria, the market’s current responses fall into four types.

Direct investor qualification: advance verification and sales restricted to accredited or qualified investors.
Established regulated distribution channels: routing through exchanges or regulated entities that have completed KYC on their users.
Collateral-level whitelisting: controlling permitted collateral assets through coordination with asset issuers.
Structural separation of permissioned lending and permissionless yield tokens: bifurcating institutional lending execution from retail-accessible yield exposure.

4.1 Investor Qualification: Grove and GLDY

The most direct way to reduce regulatory exposure is to control investor eligibility before any capital is accepted.

Steakhouse Financial launched Grove in June 2025 as an institutional-only on-chain capital allocation channel. Access is restricted to institutional RWA investors who have passed advance qualification screening.

Orca, in May 2026, partnered with Streamex Corp (Nasdaq: STEX) to open the GLDY pool for accredited investors only. GLDY is a yield-bearing tokenized security backed by physical gold reserves, issued explicitly under Regulation D, Rule 506(c), the private placement exemption under U.S. securities law. Investor accounts begin with on-chain transfers frozen and are unlocked only after passing Streamex’s KYC and accredited investor verification.

Both approaches target institutional and accredited investors, establishing a logical basis for using the private placement exemption without full public registration.

Investor qualification, however, does not neutralize a product’s characterization as an investment contract under the Howey Test. Accredited investor status is more directly relevant to the distribution path than to the question of whether a security exists in the first place. This is a practical risk-management approach within the current legal framework, not a fundamental change in legal character.

The curator’s core function of selecting assets and setting allocation weights within the vault remains unchanged, which is the structural limitation these access controls cannot address.

4.2. Existing KYC and Compliance Infrastructure: Sentora

Rather than building its own qualification framework, Sentora combines existing KYC-based distribution channels with regulated asset issuance infrastructure.

Kraken’s DeFi Earn product is the clearest example. Veda provides the vault infrastructure; Chaos Labs manages the Balanced and Boosted vaults; Sentora serves as risk manager for the Advanced vault, overseeing capital allocation across on-chain protocols and managing risk and liquidity.

This arrangement has since been adopted more broadly. Coinbase has combined Morpho and Steakhouse Financial to launch USDC lending through Prime and High Yield vaults. Binance has connected its users to Morpho vaults managed by Steakhouse and Gauntlet.

Exchange-level KYC confirms user identity, and issuer compliance frameworks support reserve and redemption structures. Neither addresses who is deciding which assets and markets receive how much capital. External compliance infrastructure reduces risk at the asset and distribution level but does not absorb the regulatory exposure or legal liability of the risk manager making allocation decisions.

4.3 Asset-Level Whitelisting: Aave Horizon

Aave launched Aave Horizon in August 2025 as an institutional RWA lending market. The product is structurally separated from the core protocol and designed to the specifications required for institutional asset management.

Aave Horizon’s distinctive design choice is to share control over permitted collateral with asset issuers rather than restricting user access directly at the distribution stage. Whitelists for tokenized collateral assets are managed by the issuers themselves: Circle, Ripple, Superstate, and Centrifuge (which includes Janus Henderson products). The protocol itself remains permissionless for any wallet holding whitelisted assets.

The governing control is not who accesses the market but which assets are eligible. Risk parameters follow recommendations from LlamaRisk, and collateral valuations are supported by NAV data verified by Chainlink in real time. Aave Horizon builds on existing Aave lending infrastructure rather than constructing a new chain or independent protocol.

Sharing verification responsibility with asset issuers does not extinguish Aave Horizon’s own legal and operational liability for its risk parameter decisions.

4.4 Structural Separation of Permissioned Lending and Permissionless Yield: Maple Finance

In April 2024, Maple Finance converted its entire platform to a whitelist structure. All loans are now fully overcollateralized, and Maple Direct, its in-house credit team, conducts borrower underwriting, ongoing monitoring, and margin calls directly. Access is limited to approved institutional borrowers and lenders.

The most notable aspect of Maple’s design is the separation between the permissioned lending operation and permissionless yield access. In 2024, Maple launched the Syrup protocol, through which retail users can deposit USDC without KYC and receive SyrupUSDC in return. Those deposits flow into the same institutional lending pool that Maple Direct already manages with its accredited borrowers. The lending itself operates under rigorous institutional compliance. The right to receive the yield that lending generates is packaged into a permissionless token and made available to any user.

This structure relocates regulatory exposure rather than eliminating it. Maple Direct’s underwriting and management discretion, including borrower selection, collateral terms, and margin calls, remains intact. The arrangement by which institutional lending returns are passed to SyrupUSDC holders generates its own question of whether that token constitutes an investment contract under the Howey Test, together with separate distribution liability.

The structural separation of permissioned lending and permissionless yield is a deliberate repositioning of where regulatory scrutiny lands. It does not change the legal liability of the entities managing the capital or the fundamental nature of the product.

The cases above address different regulatory contact points but share a common limitation. They are operational defensive structures designed to manage regulatory exposure by separating investors, assets, and distribution channels. They are not final solutions that extinguish legal risk.

Mapped against the two analytical axes introduced earlier:

One approach has obtained an explicit legal exemption: the Orca/GLDY structure, which applies Regulation D, Rule 506(c) directly.
The remaining approaches manage and constrain regulatory exposure: Grove, Sentora, Aave Horizon, and Maple Finance, through a combination of institutional qualification restrictions, third-party compliance infrastructure, and collateral whitelisting.

Restricting distribution and filtering eligibility does not resolve the underlying legal liability that attaches to a curator or protocol’s discretionary asset selection and allocation decisions.

5. What History Shows Works

The future of the on-chain asset management market will be determined not by the surface appearance of the code but by the institutional frameworks established to govern the scope of discretion, the transparency of disclosure, and the allocation of legal liability.

The measures examined above reduce immediate regulatory exposure and provide room to use existing private placement exemptions. They do not answer the foundational questions of what criteria govern a curator’s allocation decisions and who bears responsibility when losses occur.

The historical record is consistent on one point: access restrictions alone have not produced durable institutionalization.

Closed-end funds in the 1920s and 1930s saw widespread abuse of “blind pool” structures in which managers did not disclose their investment targets. The Investment Company Act of 1940 resolved this not by restricting access but by institutionalizing the asset management function itself.
In 2008, when the SEC determined that LendingClub’s peer-to-peer loan notes were securities, the company suspended new registrations and restructured as an issuer of SEC-registered notes tied to its loans, eventually listing publicly in 2014.
In 2012, the crowdfunding industry’s demand for reduced fundraising restrictions led to the JOBS Act and the creation of Regulation Crowdfunding.

What the three cases share is that they did not stop at restricting investor access. They established the legal character of the product, the obligations of the operating entity, the scope of required disclosure, and the allocation of loss. Sustainable growth for new financial instruments requires that market participants be able to predict, in advance, both their rights and their legal responsibilities.

On-chain vaults and DeFi markets face the same institutionalization challenge. The available paths are:

Full registration under existing securities law.
Private placement exemptions targeting qualified investors.
Immutable protocol design that eliminates discretion entirely.
New regulatory exemptions specific to on-chain finance, such as those proposed to the SEC by Ava Labs and the Solana Policy Institute.

Whichever path is taken, the central task is the same: establishing who makes investment decisions, what disclosures are required, and where liability falls when outcomes are adverse.

6. Compliance Costs as a New Barrier to Entry

The factor that will ultimately determine competitive position in the on-chain asset management market is the capacity to absorb compliance costs structurally and to demonstrate legal accountability.

Because regulators cannot directly control code, the framework that holds human actors legally accountable for the discretion they exercise over it will only become more clearly defined. Regardless of how effectively a firm has positioned itself in the interim, formal registration or explicit exemption frameworks will eventually require every operator to demonstrate the legal basis for its management structure and the boundaries of its liability. At that point, compliance obligations, encompassing KYC infrastructure, legal review, on-chain asset valuation, bespoke institutional contracts, and loss-absorption structures, will cease to be administrative overhead. They will become an independent cost item requiring sustained capital investment.

The internalization of these compliance costs will drive a meaningful reordering of the curator market. Large curators with capital, operating scale, and established institutional relationships will be able to distribute compliance costs efficiently and consolidate their market position. Smaller curators, without the capital to fund independent infrastructure, will face a choice between bearing disproportionate costs and accepting consolidation into larger regulated protocols or distribution channels.

The real value of the grace period that interim strategies have secured will be determined by what is built during it. Those who use this time to design formal registration pathways, identify viable exemptions, and establish clear liability structures in advance will find that regulatory requirements become a source of competitive advantage rather than a barrier. For those who defer, mounting compliance costs will erode profitability and, ultimately, foreclose market participation.

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Disclaimer

This report has been prepared based on materials believed to be reliable. However, we do not expressly or impliedly warrant the accuracy, completeness, and suitability of the information. We disclaim any liability for any losses arising from the use of this report or its contents. The conclusions and recommendations in this report are based on information available at the time of preparation and are subject to change without notice. All projects, estimates, forecasts, objectives, opinions, and views expressed in this report are subject to change without notice and may differ from or be contrary to the opinions of others or other organizations.

This document is for informational purposes only and should not be considered legal, business, investment, or tax advice. Any references to securities or digital assets are for illustrative purposes only and do not constitute an investment recommendation or an offer to provide investment advisory services. This material is not directed at investors or potential investors.

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Top 6 Cold Wallets to Store Your Crypto

2026-08-05T00:35:46Z

Top Cold Wallets for Storing Cryptocurrencies

The top cold wallets for securely storing cryptocurrencies offline are:

OneKey

Ledger

Trezor

SafePal

Tangem

Ellipal

Key Points:

Cold wallets, also known as hardware wallets, are offline custody devices for crypto assets. They store private keys offline and connect to other devices via USB or Bluetooth rather than maintaining a constant internet connection like hot wallets.

This offline storage method provides the highest level of security for crypto assets. Keeping wallet keys offline significantly reduces the risk of private key theft and unauthorized access.

Ledger and Trezor dominate the hardware wallet market as the largest providers. The industry now offers diverse options, including card-based wallets and devices with advanced security features like the Smart Transaction Defense system from OneKey.

This article was updated in August 2026 by Vera Lim.

Cryptocurrency wallets are a key part of the crypto space, as you need them to manage your assets. These can be custodial or non-custodial, and the latter can be split into software (hot) or hardware (cold) wallets. Hot wallets like MetaMask and Trust Wallet have grown popular over the years, scoring high in terms of convenience. Meanwhile, cold wallets are focused on security, and are the recommended way for users to store long-term holdings.

What Are Cold Wallets?

Cold wallets are also called hardware wallets. Cold wallets are hardware devices resembling USB storage devices with connectivity features like USB, WIFI and Bluetooth. Cold wallets secure crypto assets held in a blockchain account by storing the wallet’s private keys offline, unlike hot wallets which are always connected to the internet.

This makes cold wallets more inconvenient to use, as signing transaction requests involves more steps. However, their reduced convenience is a key part of its rigid security structure. Some popular cold wallets include Trezor, Ledger, SafePal, and Tangem Wallet. The security level of cold wallets is usually rated according to the EAL metrics.

What Is the EAL rating?

EAL (Evaluation Assurance Level) rating is the security ranking standard for IT products like cryptocurrency cold wallets. It ranks tech products’ assurance levels from 1 to 7, where higher levels imply more rigorous security measures. The EAL rating system considers the product design, functional analysis, and performance in penetration testing, and accords an EAL score based on the average performance.

Most cold wallets have an EAL rating of 5 and above, where the qualification promises users a high level of independently assured security with a rigorous development approach.

Do note that the EAL level does not measure the security of the system itself, and it only states at what level (EAL1-7) the system was tested.

Now, let’s look at some of the notable cold wallets and their key features.

Open Source vs. Closed Source: Which Is More Secure?

Open-source cold wallets, like Trezor and OneKey, make their firmware code publicly available, allowing independent researchers to audit how the device generates keys and processes transactions rather than trusting the vendor's word alone. This transparency can lead to faster bug discovery and patching, since anyone can review the code.

Closed-source wallets, like Ledger and Tangem, keep their firmware private, arguing that concealing the implementation raises the cost of vulnerability research for attackers. This doesn't mean the code goes unchecked; closed-source firmware is still typically audited by independent third-party security firms and put through bug bounty programs, just privately rather than open to public review.

Neither approach guarantees security on its own — it comes down to how well each is executed, not just whether the code is public.

The Coldcard Incident

In July 2026, a firmware bug in Coinkite's open-source Coldcard wallets led to tens of millions of dollars in Bitcoin theft. The root cause was a 2021 update that used a weaker, software-based random number generator instead of a hardware-based one, allowing attackers to reconstruct private keys offline.

The bug had been sitting in publicly viewable code for five years before it was caught, which the industry has pointed to as a counterexample to the idea that open code gets bugs found and fixed faster. The incident shows that open source alone doesn't guarantee security; it's one factor among several, including engineering practices and entropy sourcing.

OneKey: Open-Source Security with Smart Transaction Defense and Wireless Connectivity

This section is brought to you by OneKey.

OneKey stands out in the hardware wallet space by combining top-tier security elements with a commitment to full transparency through open-source code. Founded in 2020, OneKey has quickly established itself, backed by industry leaders like Coinbase Ventures and Dragonfly.

As a fully open-source hardware wallet, both the firmware and the companion software are publicly auditable. OneKey devices are secured by EAL 6+ certified chips, offering the same level of banking-grade security found in government IDs and bank cards.

The OneKey ecosystem is managed via the native OneKey App (available on mobile, PC, Mac, and as a browser extension). This app allows users to track, send, receive, and swap assets across networks. OneKey supports over 100 blockchains and 30,000+ coins and tokens, including Bitcoin, Ethereum, Solana, and various NFTs.

A key security feature is SignGuard, which works across the devices and the app to block risky signatures and flag malicious contracts, phishing sites, or drainers in real-time before a transaction is confirmed. The hardware is also designed with a Quantum-Ready Architecture to address future cryptographic threats.

Here are some OneKey hardware wallet options:

OneKey Pro

The OneKey Pro is the flagship device, designed for advanced users prioritizing a full-feature experience and maximum physical isolation. It retails for $278.

Key Features: It is equipped with four separate EAL 6+ Secure Elements and offers multiple connectivity options, including Air-gapped signing (via a built-in camera for QR codes), Bluetooth, and USB-C.
Display & Interaction: It features a large 3.5-inch HD color touchscreen (480x800) and supports fast authentication via fingerprint recognition.
Power: It supports Qi wireless charging, making it the first air-gapped cold wallet with this capability.

OneKey Classic 1S

The Classic 1S provides a balance of high security and portability at an affordable price of $99.

Key Features: It uses a single EAL 6+ Secure Element and maintains a compact, thin form factor (5.2 mm).
Display & Interaction: The device uses a 1.54-inch monochrome OLED display and four physical navigation buttons for transaction confirmation.
Connectivity: It connects via USB-C and Bluetooth for full platform support (Windows, macOS, Linux, Android, and iOS).

OneKey Classic 1S Pure

Priced at $79, this model is tailored for long-term HODLers who prefer a battery-free device.

Key Features: Identical to the Classic 1S in terms of security and display, it uses a single EAL 6+ Secure Element and the same compact design.
Power: The "Pure" version is battery-free and requires a constant USB-C connection to operate, minimizing the risks associated with internal batteries and maximizing longevity.

Ledger: The Popular Hardware Wallet Classic

Ledger launched the Ledger Nano S, its first hardware wallet in 2016 as a safe storage medium for Bitcoin. Since then, it has released about five cold wallets including the Ledger Nano X, Ledger Flex, and Ledger Nano S Plus, and has grown its support for crypto assets, including NFTs. Ledger wallets store your private keys offline and connect to smart devices for advanced operations like staking and purchasing assets through Ledger Live – the software interface for the Ledger wallet.

You can manage your assets either through the native Ledger Live app, which supports 500 coins and Ethereum and Polygon NFTs, or through 50 supported third-party wallets like MetaMask, which supports over 5,000 coins and multi-blockchain NFTs.

Ledger Wallet also supports connection through third-party wallets like MetaMask. Through Ledger Live and third-party wallet connections, users can access DeFi platforms and dApps deployed on the supported networks.

For all Ledger devices, you can recover access to your assets through a 24-word secret recovery phrase, or you may opt for the controversial Ledger Recover, which allows users to retrieve lost private keys.

Here are some Ledger wallet options:

Ledger Nano S Plus

The Ledger Nano S Plus sells for as low as $79. It comes in a plastic body with a stainless steel swivel, a 1.09-inch screen display, and a USB-C connection. It has a security rating of EAL6+ and an ANSSI CSPN certification. The Ledger Nano S Plus is supported on the Ledger Live application and can connect to decentralized applications through third-party wallets. However, the Ledger Nano S Plus only works on desktop and Android.

Ledger Nano X

The Ledger Nano X tops the Nano S Plus device with a wider body but retains the 1.09 inch screen size. It has a battery with up to five hours of normal use, and offers additional iOS compatibility.The Ledger Nano S has a security rating of EAL5+ and an ANSSI CSPN certification, with USB-C connection and Bluetooth connectivity. At time of writing, the Ledger Nano X retails for $149.

Ledger Stax

The Ledger Stax is Ledger’s most advanced cryptocurrency cold wallet with an EAL6+ rating, and prices start at $399 at the time of writing. The Ledger Stax is equipped with a 3.7 inch curved screen, and a battery time of up to 10 hours or 150 transactions. In addition to the usual USB-C connection, the Ledger Stax also features Bluetooth and specialized NFC (Near Field Communication).

Trezor: Open Source Hardware Wallets

Trezor launched one of the earliest forms of contemporary cold wallets – the Trezor Model One on July 19, 2014, and followed up with the Model T about four years later. Trezor is an open source cold wallet for storing cryptocurrencies, and it combines the seed phrase with a non-stored passphrase that makes hacks of the physical device unlikely.

Trezor currently has three cold wallet options under its wing. Each wallet supports over 1,000 crypto assets and up to 80 blockchain networks. Trezor wallet mobile application, Trezor Suite, allows users to connect their devices to a smart device and perform advanced operations including trading assets and paying for daily essentials, where every transaction requires confirmation on the accompanying Trezor hardware wallet. Like other cold wallets, Trezor also supports DeFi transactions through third-party wallet connections.

However, note that Trezor only offers USB-C/USB-A connections, and is only compatible with MacOS, Windows, Linux, and Android, where iOS capabilities are limited to view-only.

Here are some Trezor wallets:

Trezor Safe 7

The soon to be released Trezor Safe 7 includes a transparent, auditable Secure Element (TROPIC01), open to anyone to audit and verify how it protects your crypto. The TROPIC01 chip is combined with an additional EAL6+ secure element. It also uses post-quantum cryptography to secure firmware updates, device authentication, and the boot process, protecting wallets against future quantum computing threats. It will also offer wireless charging and bluetooth connectivity. The Trezor Safe 7 will retail at $249, and preorders are open.

Trezor Safe 5

The Trezor Safe 5 was released on 14 June 2024; it is the latest Trezor wallet device and the most advanced yet. The Trezor Safe 5 retails at $169 and comes with a 1.54 Inch Gorilla Glass 3 color touchscreen. It has an EAL6+ security rating and is open-source like other Trezor wallets. Connectivity-wise, the Trezor Safe 5 utilizes a USB-C cable.

Trezor Safe 3

The Trezor Safe 3 was released on 12 October 2023, and is priced at $79 at the time of writing. It is equipped with a 0.96 inch monochromatic display and two control buttons. Like the Trezor Safe 5, the Trezor Safe 3 utilizes USB-C for connectivity.

Trezor Model One

The Trezor Model One is the earliest Trezor wallet device, and was released on 29 July 2014. It is priced at $49, and comes with a 0.96 inch monochromatic display and two control buttons. Unlike the other two Trezor models, it enables USB connectivity via a micro USB connection port.

SafePal: Extensive Support for Tokens and Chains

SafePal S1 – the first SafePal hardware wallet – was launched in May 2019. Since then, the firm has added two more hardware wallet devices to its product list. Safepal wallets support over 100 blockchain networks and millions of NFTs and tokens – to check if your token is supported and on what device, you can check out SafePal’s Supported Assets page.

SafePal’s hardware wallets are compatible with the SafePal hot wallet, allowing hardware wallet owners to perform advanced operations like interacting with decentralized applications with their wallets. The SafePal hot wallet is available as a native application for Android and iOS devices and as a browser extension for desktop devices.

SafePal’s hardware wallets also feature a self-destruct mechanism that triggers if the secure element is tampered with, during which the secure element will erase all wallet data.

SafePal S1/S1 pro

The S1 series features fully air-gapped and 100% offline hardware wallets – the SafePal S1 and the newer S1 Pro. The S1 Pro offers an improvement in battery life (S1 – 400mAh, S1 Pro – 500mAh) and uses more premium housing materials for the cold wallet. The S1 retails at $49.99, while the S1 Pro is priced at $89.99.

However, both wallets share many similarities. The S1 and S1 Pro have the same screen size and security features. Both wallets use a 100% air-gapped signing mechanism, with its secure chip having an EAL rating of 5+. These wallets also use QR codes for connection, although there is also a USB-C option.

SafePal X1

The SafePal X1 retails for $69.99, and comes with a 1.8 inch monochrome display screen, a 12-button control pad, and a 200mAh battery. It uses a high-speed Bluetooth 5.0 signing mechanism for improved efficiency, with its secure chip rated EAL5+. The SafePal X1 is also open source, with its code available on github for maximum trust and efficiency.

Tangem Wallet: Leveraging NFC Technology for One-Tap Convenience

Tangem Wallet uses chip technology and NFC (Near Field Communication) technology to develop a cold wallet for crypto assets. Tangem Wallets are cards with chips attached, and are equipped with NFC technology for connectivity. The communication technology is supported by mobile devices (Android 6.0 or higher and iOS 15.0 or higher).

The chip in the card generates a random private key that is never exposed, ensuring the wallet cannot be compromised, and each Tangem Wallet can contain up to three Tangem cards, all of which are tied to the same wallet. Each card holds a copy of the wallet keys, which are generated during the activation process and copied to each of the available cards. The Tangem 1.0 does not generate passphrases, but this can be done on the Tangem 2.0.

To transact using the Tangem Wallet, the user only needs to tap the card on their device to activate it. Tangem Wallets work with the Tangem App, which is available as a native app for Android and iOS devices. Through the app, users can manage their assets and perform DeFi transactions like swapping and staking.

Tangem also offers the Ring wallet. The Ring wallet works the same way as the card wallets, however, the chip is embedded in a ring for more portability, and will replace at least one card in a three-card Tangem wallet.

Tangem wallet supports over 61 blockchain networks and thousands of crypto assets including NFTs on these networks. The Tangem card wallet sells for $54.90 at the time of writing, while the Tangem Ring is $160.

Ellipal: The First 100% Air-Gapped Wallet

Ellipal claims to be the first cold wallet developer to produce a 100% air-gapped wallet. The Hong Kong-based wallet development firm was launched in 2018 and released their first cold wallet – Ellipal – the same year. This was followed by the Ellipal Titan about a year later. Ellipal wallets are EAL5+ rated and support over 10,000 crypto assets including tokens from over 80 blockchain networks and NFTs for Ethereum and other supported networks.

According to the team, the Ellipal wallet is completely disconnected from the internet and is equipped with an efficient QR Code scanner for connecting to third-party applications and running transactions. Ellipal wallet users can connect their wallet to the Ellipal App, a native mobile application that can be installed on Android and iOS devices to manage their assets and run advanced transactions like staking and swapping. Ellipal wallets are also compatible with hot wallets like the MetaMask Wallet. Through third-party connections, users can access decentralized applications. Ellipal has two flagship wallets; the Ellipal Titan Mini and Ellipal 2.0. Both wallets are tamper-proof and feature a self-destruct anti-hacking mechanism, and users can create up to 10 accounts and store NFTs on Ethereum and Polygon. The Titan Mini sells for $99 and features a 2.7 inch HD screen with a 600mAh battery. Ellipal 2.0 is Ellipal’s most advanced cold wallet yet, and retails at a significantly higher price of $169. It has a larger 4.0 inch screen and a 1400mAh battery. Like the Titan Mini, Ellipal 2.0 is compatible with the Ellipal App and third-party wallet. The Ellipal 2.0 also comes with a pattern PIN – a feature that is not available on the Titan Mini.

Comparison Table of Listed Cold Wallets

	EAL rating	Assets Supported	Devices supported	Price ($)
OneKey Pro	EAL6+	Over 100 blockchains and 30,000+ coins and tokens	Windows, macOS, Linux, Android, and iOS	$278
OneKey Classic 1S	EAL6+	Over 100 blockchains and 30,000+ coins and tokens	Windows, macOS, Linux, Android, and iOS	$99
OneKey Classic 1S Pure	EAL6+	Over 100 blockchains and 30,000+ coins and tokens	Windows, macOS, Linux, Android, and iOS	$79
Ledger Nano S Plus	EAL6+	Over 5,000 assets including NFTs from multiple blockchain networks	Windows, macOS, Linux, and Android devices	$79
Ledger Nano X	EAL5+	Over 5,000 assets including NFTs from multiple blockchain networks	Windows, macOS, Linux, Android and iOS devices	$149
Ledger Stax	EAL6+	Over 5,000 assets including NFTs from multiple blockchain networks	Windows, macOS, Linux, Android and iOS devices	$399
Trezor Safe 7	EAL6+	Over 1,000 cryptocurrencies including Bitcoin, Dogecoin, and Litecoin.	Windows, macOS, Linux, Android and iOS devices	$249
Trezor Safe 5	EAL6+	Over 1,000 cryptocurrencies including Bitcoin, Dogecoin, and Litecoin.	Windows, macOS, Linux, and Android devices	$169
Trezor Safe 3	EAL6+	Over 1,000 cryptocurrencies including Bitcoin, Dogecoin, and Litecoin.	Windows, macOS, Linux, and Android devices	$79
Trezor Model One	NA	Over 1,000 cryptocurrencies including Bitcoin, Dogecoin, and Litecoin.	Windows, macOS, Linux, and Android devices	$59
SafePal X1	EAL5+	Over 100 blockchains, unlimited tokens, and NFTs	Extension on Chrome, FireFox, and Edge. Android and iOS devices	$69.99
SafePal S1/S1 Pro	EAL5+	Over 100 blockchains, unlimited tokens, and NFTs	Extension on Chrome, FireFox, and Edge. Android and iOS devices	$49.99/$89.99
Tangem Wallet	EAL6+	Over 60 blockchain networks and thousands of crypto assets on supported networks	Android and iOS devices	From $54.90
Ellipal Titan Mini/2.0	EAL5+	Over 10,009 cryptocurrencies and over 80 blockchain networks.	Android and iOS devices	$99/$169

Final Thoughts

Storing your assets in cold wallets is the recommended safety practice. Despite the convenience of software (hot) crypto wallets, they have been implicated in several cases of crypto hacks as they are constantly connected to the internet. Cold wallets tackle this risk by disconnecting your blockchain wallet from the internet. However, this is not to discount the convenience of hot wallets, as it’s recommended for users to use a hot wallet for regular transactions, while using cold wallets for long-term storage and holding of crypto assets.

If you are looking to improve the security of your crypto investments using cold wallets, this article reviews some of the best cold wallets. It is important to consider the features of a cold wallet as they apply to you and choose one that serves your needs. Also, note that this article reviews cold wallets for educational purposes only and should not be taken as financial advice.

An earlier version of this article was written by Joel Agbo.

How Top Enterprises & Institutions Use Crypto Data APIs

2026-07-30T07:04:48Z

TL;DR

CoinGecko API is a leading crypto data API for enterprises and institutions, combining broad asset coverage, independent market data, and infrastructure designed for product development, trading, compliance, tax, and treasury workflows at scale.
Kraken, Crypto.com, and Variational integrate CoinGecko API data into their trading and token-discovery products, with Kraken reporting a 44% increase in user engagement after the integration.
Deblock, Europe’s first MiCA-regulated onchain bank, along with compliance leaders Elliptic and Chainalysis, rely on CoinGecko’s independent and auditable pricing data to support regulated workflows that require transparent and neutral market data sources.

Enterprises and institutions often have requirements that go beyond standard crypto data features, including reliability, data accuracy, transparency, and the ability to scale with their workflows. They need confidence that the data powering their products and operations can support use cases, from trading infrastructure and compliance workflows to treasury tracking, tax reporting, and wallet or portfolio applications.

This article explores how leading organizations across exchanges, wallets, institutional finance, DeFi infrastructure, taxation and accounting, data and analytics, and AI and autonomous agents use CoinGecko API in production. We also cover what enterprises and institutions look for in a crypto data provider and how to evaluate the right provider for your use case.

What Do Enterprises and Institutions Need From a Crypto Data API?

Enterprises and institutions require crypto data APIs that can support production-scale applications, provide broad asset and network coverage, deliver historical depth for analysis and audits, and meet the documentation standards required for internal reviews. These requirements typically fall into several key areas:

Uptime & reliability: Production trading, wallet, analytics, and compliance systems require consistent data availability, especially during periods of high market volatility.
Broad asset & network coverage: Organizations need comprehensive data across centralized exchanges, decentralized exchanges, and onchain markets without relying on multiple fragmented sources.
Historical data depth: Multi-year historical data supports use cases such as tax reporting, fund analysis, compliance reviews, and research.
Low-latency data delivery: Real-time access through WebSocket or webhook integrations, enabling faster data workflows beyond standard REST API requests.
Dedicated enterprise support: Organizations operating at scale benefit from knowledgeable support contacts who understand their integration and operational requirements.
Security, compliance readiness & data independence: Clear documentation supports internal reviews, and regulatory requirements. Beyond documentation, enterprises look for third-party attestations and certifications such as SOC 2 to validate a provider’s security and compliance practices. Transparent data aggregation methodologies and independence also further strengthen audits, risk assessments, and compliance efforts.

How Top Enterprises and Institutions Use CoinGecko's API

Enterprises and institutions use CoinGecko API to support products, analytics, and operational workflows that require reliable market data, pricing, and onchain coverage. The examples below highlight how organizations across industries use CoinGecko API to address specific data requirements and support their workflows at scale.

Exchanges and Trading Platforms
Wallets and Consumer Crypto Apps
Institutional Finance, Banking, and Compliance
Cross-Chain and DeFi Infrastructure
Taxation and Accounting
Data, Analytics, and Business Intelligence
AI & Autonomous Agents

Exchanges and Trading Platforms

Exchange and trading platforms require reliable market data for asset discovery, reference pricing, and trading operations. CoinGecko API provides aggregated pricing and market data that helps these platforms reduce the complexity of sourcing, normalizing, and maintaining crypto data at scale.

Kraken

Kraken is a global cryptocurrency exchange serving users across 190+ countries and integrated CoinGecko API to support real-time and historical pricing across Kraken.com and Kraken Pro. The integration supports asset-specific price pages, market cap and volume data, category comparisons, and spark charts. This resulted in a 44% increase in engagement and conversion across Kraken’s ecosystem, alongside improvements in uptime and data accuracy.

"The CoinGecko API enables us to deliver comprehensive, real-time information that empowers Kraken clients to research deeply, trade profitably, and invest with confidence. By equipping our users with the insights they need, it has become a key driver of growth and engagement at Kraken."

— Bill King, Head of Organic Growth at Kraken

Read the Kraken case study

Crypto.com

Crypto.com’s self-custodial wallet runs on CoinGecko API to power token discovery for 10M+ users, providing real-time price and market data across 11M+ tokens and 200+ networks. The integration supports discovery features such as hot, top, new, and trending tokens, alongside gainers and losers. The improved discovery surfaces drove an 86% increase in user clicks.

"CoinGecko API is well-organised and developer-friendly. Most importantly, CoinGecko's data is accurate and they support the trending tokens very quickly."

— Esther Wong, Onchain Product Lead at Crypto.com

Read the Crypto.com case study

Variational

Variational draws on CoinGecko’s coin and onchain endpoints to support market listings and pricing for its Omni perpetual futures exchange, covering 450+ markets without manual maintenance and reducing duplicate listings across assets deployed on multiple chains.

"CoinGecko’s API was a lifesaver while we were building Variational’s automated listing engine. Crypto data is often fragmented and inconsistent, so being able to use the CoinGecko API to avoid listing collisions and source key data like FDV reliably was essential."

— Max Bibeau, Head of Marketing, Variational

Read the Variational case study

Wallets and Consumer Crypto Apps

Wallets and consumer crypto apps require reliable market data, token metadata, and asset identification capabilities to deliver accurate portfolio valuations, token discovery, and user experiences across multiple chains.

Phantom

Phantom is a self-custodial wallet trusted by 15M+ users across Solana, Ethereum, Polygon, Sui, Monad, and Bitcoin. It relies on CoinGecko API as a source of token metadata to support token verification and reduce exposure to fraudulent assets within its wallet interface.

Read the Phantom case study

D'CENT

D’CENT is a biometric hardware wallet used by 700K+ people worldwide. It integrated CoinGecko API’s pricing endpoints to provide live prices and chart data across 4,600+ assets on 85+ networks, enabling users to access real-time market information directly within the wallet interface.

"CoinGecko’s data helps us give users the most accurate and up-to-date market information right inside the wallet. It’s become an important part of how we make on-chain activity easier and more intuitive for everyone."

— Wan Kyu Kim, Chief Business Officer, D’CENT Wallet

Read the D'CENT case study

Institutional Finance, Banking, and Compliance

Regulated financial institutions require crypto data that can withstand regulatory scrutiny and audits, with clear data provenance, reliability, and transparency.

Deblock

Deblock is Europe’s first fully MiCA-regulated onchain bank that combines a euro account, Visa debit card, and non-custodial crypto wallet into a single product. Deblock streams price updates through CoinGecko’s WebSocket to keep crypto balances, portfolio visualizations, and euro-to-crypto conversions accurate to the standards required by a regulated bank.

"CoinGecko’s robust data infrastructure is the silent engine behind our portfolio visualizations, allowing Deblock to transform raw onchain data into clear, actionable insights for our users. Their accurate real-time pricing and historical depth enable us to build a seamless bridge between everyday banking and the crypto economy."

— Mario Eguiluz, Cofounder & Chief Technology Officer at Deblock

Read the Deblock case study

Elliptic

Elliptic is a blockchain analytics and compliance firm serving financial institutions and regulators. It integrated CoinGecko API to extend its pricing coverage across millions of tokens, including tokenized real-world assets (RWAs), such as tokenized securities, funds, and other regulated instruments emerging onchain. As RWA tokenization gains regulatory adoption and oversight, this coverage helps Elliptic's compliance and financial crime teams accurately value newly listed and lower-liquidity assets.

Read the Elliptic announcement

Chainalysis

Chainalysis is a blockchain analytics and intelligence platform used by financial institutions and government agencies. They integrated CoinGecko’s API to provide pricing coverage for 10K+ tokens on EVM chains, Solana, and other blockchain ecosystems, supporting investigations and compliance workflows.

Read the Chainalysis announcement

Cross-Chain and DeFi Infrastructure

Cross-chain infrastructure providers need broad chain coverage, low-latency data freshness, and reliable asset discovery across multiple networks and contract addresses to support a growing multi-chain ecosystem.

0x

0x powers swap infrastructure for 500+ businesses and 9M users, including Coinbase Wallet, Phantom, MetaMask, and Robinhood Wallet. It sources pricing data for its swap and trade analytics workflows from CoinGecko API across 200K+ unique trading pairs. Today, 0x has processed 60M+ transactions and $154B+ in all-time trading volume.

"CoinGecko has been instrumental in allowing us to accurately price our internal data pipelines. In 2023, 0x saw about 30K unique trading pairs. Today we see upwards of 200K unique pairs, all of which need pricing from CoinGecko."

— Eric Wong, Product Manager at 0x

Read the 0x case study

LI.FI

LI.FI is a cross-chain liquidity layer serving 1,000+ B2B integrators, including MetaMask, Phantom, and Robinhood. It leans on CoinGecko’s REST and WebSocket APIs to price 2M+ tokens, with an eight-tier bucketing system that refreshes high-activity tokens every second and processes roughly one billion monthly price updates.

"We evaluated over a dozen token price oracles before choosing CoinGecko as our reference provider. Our token service architecture is designed to be provider-agnostic — we can integrate any oracle — but no other API matched CoinGecko's combination of coverage across 250+ chains, real-time WebSocket delivery, and the depth of onchain data we need for automated token discovery. CoinGecko's API is what allows us to deliver enterprise-grade price freshness to clients like Robinhood, Ledger, and MetaMask."

— Clément Bihorel, Product Lead at LI.FI

Read the LI.FI case study

Taxation and Accounting

Tax platforms require highly precise historical pricing data because they must determine the value of assets at the exact time transactions occurred, including transactions from years in the past.

Summ

Summ generates audit-ready tax reports for individuals, accountants, and businesses across 180+ countries. It relies on the CoinGecko API for 12+ years of historical and real-time pricing, along with exchange ticker data covering 3,500+ exchanges, wallets, and DeFi platforms, helping value over $21 trillion in onchain transactions.

"Since the start of Summ’s journey, CoinGecko has been an invaluable partner in providing reliable pricing feeds and comprehensive asset information across the entire cryptocurrency ecosystem. Their ability to keep pace with such a rapidly evolving space ensures we can deliver accurate calculations across thousands of protocols, chains, and long-tail assets."

— Timothy Brunette, Chief Technology Officer, Summ

Read the Summ case study

Awaken

Awaken automates crypto tax reporting for 25K users managing $3B+ in onchain assets across 500K+ wallets and exchange accounts. It pulls from CoinGecko’s historical price endpoints to value transactions at their exact timestamps, including long-tail Solana tokens commonly traded by memecoin communities.

"CoinGecko API powers every single price we show inside Awaken. Without it, our product simply wouldn’t work. Accurate pricing data that is reliable is hard to get. They’re an awesome team and we look forward to growing our business by leveraging the CoinGecko API to grow to millions of crypto users."

— Andrew Duca, Founder of Awaken Team

Read the Awaken case study

Data, Analytics, and Business Intelligence

Media, research, and analytics platforms use crypto data to inform market insights, reporting, and analysis rather than directly powering transactional products such as exchanges or wallets.

Statista

Statista is a global data and business intelligence platform used by financial professionals and analysts. It relies on CoinGecko API to power 100+ crypto charts on its site, including its Bitcoin Price Index and Top 100 Cryptocurrencies table.

Read the Statista case study

Stocktwits

Stocktwits uses CoinGecko API to expand Cryptotwits, its crypto sentiment product serving a community of 10M+ traders. The integration increased asset coverage by 200%, expanding support to 17K+ crypto assets with live pricing and market data, while crypto discussion activity on the platform increased by 20%.

Read the Stocktwits case study

Brave

Brave Search pulls in live prices, interactive charts, and wallet-holding valuations directly within search results and its browser. The integration supports coverage of 17,000+ cryptocurrencies for a search product serving roughly 2.4B monthly queries.

Read the Brave case study

AI & Autonomous Agents

Reliable market data is the foundation for grounding crypto AI agents enabling accurate insights for AI-driven trading, research, and decision-making.

ChainGPT

ChainGPT is a leading provider of AI-powered infrastructure for Web3 and crypto. It integrated six CoinGecko API endpoints covering live prices, market rankings, token metadata, and historical OHLCV into its AI Hub v2, replacing general-purpose LLMs that either declined to answer market questions or provided confident responses based on outdated data. Since adopting CoinGecko API, ChainGPT has seen a 32% increase in average user session length and 41% growth in daily active users on its AI Trading Assistant.

"In the world of AI, context is everything. CoinGecko’s API gives our models the eyes and ears they need to understand the market in real-time. It has been the missing link that transformed our Chatbot from a research tool into an indispensable daily market analyst for our users."

— Dastin, Senior AI Product Manager, ChainGPT

Read the ChainGPT case study

Paal AI

Paal AI is an AI-driven trading and automation ecosystem that serves 100K+ registered users building AI agents across 50+ blockchains. It uses CoinGecko's onchain endpoints for pool and token data by contract address alongside core price and market data endpoints to support live pricing, chart generation, and investment filtering across its tools. The platform has enabled access to AI-driven market data for 17M+ users and processed 5M+ API calls for real-time pricing.

Read the Paal AI case study

Why Enterprises Choose CoinGecko API

CoinGecko API is the most widely used crypto data API and enterprises choose it for several reasons, including breadth and independence of coverage, historical depth, real-time delivery, regulatory-grade compliance, and dedicated enterprise support. CoinGecko aggregates data across 42M+ assets & trading pairs, 250+ networks, and 1,900+ exchanges through a single API, allowing enterprise-grade products, wallets, and tax platforms to access broad asset coverage without managing multiple fragmented sources.

Beyond core market data, CoinGecko provides specialized datasets for institutional use cases, such as tracking public company and government data, as well as real world assets (RWA) and tokenized assets. CoinGecko also provides deep historical coverage across centralized and decentralized exchanges, with market data from 2013. This supports institutional use cases including backtesting, performance analysis, and historical transaction valuation.

Independence can also be assessed through transparent criteria and third-party verification. CoinGecko publishes its five-step price aggregation methodology, which calculates a volume-weighted reference price, filters for liquidity, removes statistical outliers, and re-weights the result by exchange volume, all without ownership ties or incentives to favor one trading venue over another. That transparency helps organizations address conflict-of-interest questions in compliance, risk, and audit workflows, including regulatory reporting under frameworks such as MiCA, CARF, and CLARITY. CoinGecko is also SOC 2 Type 2 certified and offers Enterprise plans with a 99.9% uptime SLA tracked through a public status page. Its independent Trust Score and GT Score metrics offer a separate layer of market integrity signals, assessing exchange liquidity, security, token and project quality to help users and partners gauge platform trustworthiness.

As for data delivery, CoinGecko offers multiple integration options, including REST APIs, sub-second WebSocket streaming, and webhooks, through a self-serve or custom Enterprise subscription model designed for cost efficiency with predictable billing.

Besides, enterprise clients get dedicated support through Customer Success Manager and priority assistance for large-scale integrations, with ongoing engagement to align on new endpoints, datasets, and evolving data requirements. When needs go beyond the standard offering, CoinGecko works directly with enterprise clients on tailored solutions, including but not limited to deeper historical coverage and custom data exports.

Choosing the Right Crypto Data API for Enterprise and Institutional Use Cases

The best crypto API for institutional use depends on the specific requirements of each workflow. Institutional needs vary widely, from valuing tokenized real-world assets and supporting hundreds of perpetual markets to reconstructing transaction prices at exact historical timestamps for tax reporting. These workflows require different provider capabilities, ranging from broad onchain coverage and historical depth to real-time data streaming.

Provider selection should therefore be based on the specific needs of each use case. For most institutions and enterprises building financial and crypto products, CoinGecko API is a preferred choice for its breadth of coverage, historical depth, reliable, and cost-efficient infrastructure. More specialized providers such as CoinAPI are for teams requiring deep L2/L3 order-book history and FIX connectivity, while CoinDesk Data supports teams needing regulated benchmark administration for indices. Teams weighing these options can explore a detailed comparison of CoinGecko and CoinAPI, while those considering a wider range of providers can also evaluate the best institutional crypto data APIs based on key factors such as compliance, coverage, latency, and cost.

Conclusion

CoinGecko API supports diverse institutional workflows across regulated finance, compliance, trading, and infrastructure. Across these use cases, organizations rely on broad coverage, deep historical data, and enterprise-ready infrastructure to support their data needs.

For organizations operating in regulated markets, these requirements are becoming increasingly important. Frameworks such as MiCA, CARF, and the CLARITY are increasing expectations for data quality, transparency, and infrastructure standards, making market data provider selection an important consideration for compliance, risk, and operational teams at exchanges and financial institutions.

If you are evaluating a crypto data API for an enterprise or institutional use case, the most direct way to assess fit is to test the data against your requirements. Start with a free Demo API plan to evaluate coverage, historical depth, and reliability, or contact CoinGecko’s sales team to discuss your specific use case. For higher rate limits, deeper historical access, WebSocket and webhook delivery, dedicated support, or custom datasets, CoinGecko can help configure a solution aligned with your workflow.

Get In Touch

Ready to supercharge your crypto project? Fill in the form below to connect with our API Sales team for a custom CoinGecko API plan tailored to enterprise needs.

Robinhood Chain: Built for RWA, Loved for Memes

2026-07-29T06:35:52Z

Memecoins Accounted for 79.2% of DEX Volume in July 2026

Launched on July 1, 2026, the Ethereum Layer 2 built on Arbitrum technology positioned itself as an RWA powerhouse, backed by the retail-friendly trading platform Robinhood. What came as a surprise was the explosion of memecoin activity on the chain, headlined by the breakout success of CASHCAT, which soared past $200M in market capitalization in just over a week.

Memecoins now dominate daily activity, accounting for 79.2% of Robinhood Chain's DEX volume as of July 27, while RWA and other trading (largely WETH, ETH, and stablecoin pairs) make up 9.69% and 11.1% respectively.

That said, RWA has a strong and growing presence on Robinhood Chain in its own right. Its share of daily volume climbed from 0.39% in the chain's first week to 8.58% in the most recent week (July 21 to July 27), roughly a 22-fold increase. While attention is now mainly focused on memecoins, Robinhood’s RWA sector has been quietly booming.

Robinhood Chain Launchpad Wars

Robinhood Chain's memecoin activity has also been a story of intense launchpad competition, reminiscent of Solana’s launchpad wars back in 2025. Noxa, the chain's first dominant launchpad, captured 65.8% of all tokens launched during its active window (June 30 to July 11), deploying close to 60,000 tokens and, for five consecutive days, out-earning Solana's Pump.fun in daily protocol fees.

Then it collapsed in the space of a week. On July 11, Noxa paused new launches, citing bot spam and copycat tokens overwhelming its infrastructure. Two days later its website went dark, initially blamed on a Cloudflare issue. On July 14, it resurfaced briefly with a message that "the cat has been liberated" and announced it would redirect 100% of future trading fees to token creators. By July 16, Noxa said its domain registrar had taken over or resold its domains outright, leaving only an ENS-hosted page as an interface. CASHCAT, Noxa's flagship memecoin, fell more than 30% in the aftermath.

Pons.family stepped into the vacuum almost immediately, capturing 37.2% of all tokens launched in the post-Noxa period (July 13 onward) and becoming the single largest launchpad on the chain by both token count and trading volume.

Given Robinhood Chain is only a month old, launchpad rankings here should be read as a snapshot rather than a settled hierarchy, and are likely to keep shifting quickly. For a live view of current standings, we recommend adam_tehc's The Robinhood Trenches dashboard on Dune.

RWA Meets Memecoins: The Rise of Memecoin/Stock Trading Pairs

"Memecoin × stock pairs", trades where a memecoin is paired directly against a tokenized stock rather than against ETH or a stablecoin, is the fastest-growing line item inside the RWA volume figure. It went from a rounding error in mid-July to $46.1M in a single day by July 23, temporarily becoming a bigger contributor to "RWA volume" than actual stock trading itself.

This is also where Robinhood Chain's two personalities collide in an unexpectedly literal way. On-chain data shows memecoin creators deliberately pairing their tokens against thematically matching stocks rather than picking pairs for liquidity reasons alone:

Stock	Memecoin(s) paired against it	Volume (USD)
NVDA	AI, CHIPS, JACKET, REAL, LONGSHOT, SWOGE	$34.3M+ (appears in 8 of top 25 pairs)
GME	GME, WSB, AMC	$26.8M + $1.9M + $1.7M
SPCX	MARSCOIN, SPACEHOOD, ASTEROID, MOON	$7.8M + $4.5M + $1.4M + $0.8M
AAPL	AP, AAPLCAT	$4.4M + $2.8M
MSFT	CLIPPY	$2.2M
TSLA	USEDTESLA	$1.6M

The GME/WSB/AMC grouping is the clearest example: three tickers that defined the 2021 "meme stock" saga on Wall Street, reconstructed as live, tradeable pairs on a chain built by the brokerage that was at the center of that saga. This is a genuinely novel behavior made possible only because memecoins and tokenized stocks are liquid on the same chain. It is not yet a consequential share of overall activity, but it's worth tracking as RWA-meme crossover volume continues to grow.

Methodology

Volume and token-count data covers June 29/30 through July 27, 2026, sourced from Dune Analytics via CoinGecko's internal queries and multiple queries built by Dune analyst adam_tehc.

"Memecoin" volume is a CoinGecko reclassification, not adam_tehc's original category. It is defined as any DEX trade that does not involve a tokenized stock, ETF, commodity, or treasury token, and is not a pure base-asset pair (WETH, ETH, USDG, USDC, WBTC, or USDT trading against another base asset). This broadens the meme figure beyond tokens attributable to a named launchpad, since a diagnostic check of the "Other" bucket on July 11 found it was overwhelmingly composed of legitimate memecoins (VEX, BOW, HOODIE, and similar) that simply weren't yet mapped to a launchpad in the registry, alongside a smaller share of genuine base-asset trading.

All volume figures exclude flagged bot and wash-trading wallets, defined as wallets averaging more than 5 trade legs per transaction, or more than 18 active hours per day across 3 or more active days. This wallet-flagging methodology is applied independently in CoinGecko's reclassification query and may not produce an identical flagged-wallet list to adam_tehc's original queries; the two totals reconcile to within approximately 3%.

"Unclassified" in the launchpad rankings reflects tokens whose deploying contract has not yet been mapped to a named launchpad in adam_tehc's tracking registry. This is a data coverage gap rather than a genuine 6th launchpad, and its true composition (which named or unnamed platforms it actually represents) is unconfirmed.

Noxa's reported 65.8% share differs from the ~75% cited in some press coverage, likely due to differing measurement windows; this has not been reconciled.

The Crypto Market's Shift: From Narrative to Product-Market Fit

2026-07-27T02:07:08Z

In the first half of 2026, no single narrative ran through the entire market. Even so, stablecoins, RWA, meme tokens, DeFi, and prediction markets each survived or grew despite the downturn. This report by Tiger Research looks at the 2026 crypto market as one that is no longer driven by a single narrative but is instead searching for product-market fit across a diversified set of sectors.

Key Takeaways

A single narrative once pulled the whole market along. The market now moves according to genuine demand.
Even in a depressed market, established sectors including stablecoins, DeFi, RWA, and meme tokens have continued to survive.
In the end, only projects that find product-market fit and generate real revenue from real users will survive.

1. The Narrative-Driven Crypto Market of the Past

In the crypto market, narrative has been the central force that concentrates participant attention and pulls in liquidity. Sectors that drove major market cycles, such as DeFi Summer, were each given a distinct narrative, and the market has repeated a cyclical pattern in which liquidity moves to the next narrative as soon as the previous one fades.

At a broad level, the crypto market has passed through four major cycles in which a single narrative dominated the entire market:

2020: DeFi
2021: NFT/P2E/GameFi
2022: L1/L2 competition
2024: Restaking

Among narrative-driven growth stories, GameFi produced the most extreme outcome.

Major traditional game publishers including Square Enix and Ubisoft entered the space, and the gaming sector drew $2.5 billion in inflows in the first quarter of 2022 alone. But sectors that could not demonstrate real product-market fit did not last. Axie Infinity, the sector’s flagship title, saw its average monthly player count fall 99.7%, from a peak of 2.8 million in January 2022 to roughly 8,000 in May 2026. It is a clear example of how quickly a narrative built mainly on speculation and capital can collapse.

2. The Narratives Consumed Last Year

As covered in our previous report, 2025 marked the peak of this pattern of narrative consumption. After the AI agent narrative, a new one emerged nearly every month, and the pace of rotation kept accelerating.

On the surface this looked inefficient, but it is hard to deny that this rapid churn of narratives was what kept retail investor attention engaged and, in doing so, became a core driver of the market as it stands today. Even so, the market’s underlying demand for these past narratives was directed at the token itself rather than at the problem the product was meant to solve.

3. Innovation in Supply Without Demand

One example illustrates how most past narratives developed.

A decentralized social media project appears, framed around the problem that existing platforms monopolize revenue and leave creators inadequately compensated. It presents a vision of lower fees and of returning content ownership and revenue to creators.

Token rewards: early participants receive token rewards, and as stories spread of people earning income simply by being active on the platform, market interest grows.
User inflow and expansion: similar projects follow, issuing tokens around a minimum viable product and drawing users in through airdrops and liquidity incentives, and the ecosystem’s market capitalization and trading volume expand quickly.
Stalled product development: the token price and the scale of rewards start to outpace the product itself. Once fundraising and the initial distribution are complete, development and user growth stall, and the original problem of creator compensation remains unresolved.
Liquidity exit: there was never a large enough user base that felt this problem acutely, and the capital that had flowed in was chasing price appreciation rather than the product, so once the narrative peaked, liquidity and users left just as quickly.

This pattern repeated across several narratives, and the market eventually came to recognize that innovation in supply without underlying demand carries little meaning. It began to confirm that only projects generating real revenue and holding onto a stable user base mattered, and it became clear that only projects demonstrating genuine product-market fit would survive.

4. 2026: The Era of PMF That Creates Demand

Where past narratives built and supplied solutions without underlying demand and tried to manufacture demand afterward, the PMF era works the other way around: products are built to match demand that already exists among customers. The market is moving toward genuine products in which user numbers and revenue grow alongside the product and the brand, rather than one in which only token market capitalization rises.

The five sectors covered here were selected based on three criteria: usage indicators such as trading volume and revenue over the first half of 2026, the trajectory of new players entering the space, and growth in market capitalization. These criteria matter because they are difficult to manufacture artificially, all at once and over a short period.

The sections below trace the problem each sector originally set out to solve and the direction in which its leading players are now expanding.

4.1. Stablecoins: From a Volatility-Free Payment Instrument to Cross-Border Settlement Infrastructure

Stablecoins are tokens pegged to the value of fiat currency and used as a means of payment and settlement. The category’s market capitalization stands at $304.2 billion, close to its all-time high of $321 billion.

Tether(USDT): market cap of $184.08 billion, monthly settlement volume of $1.79 trillion (up 63% month over month), $10.2 trillion in cumulative settlement over the past 12 months, more than $10 billion in net income in 2025, and $141 billion in Treasury holdings.
Circle(USDC): market cap of $73.25 billion, the default stablecoin across major exchanges such as Coinbase and institutional settlement channels.

Stablecoins started out as a way to trade crypto without exposure to volatility. Their role has since broadened to cross-border remittances and on-chain payment infrastructure.

Growth is now taking more varied forms. In June 2026, more than 140 traditional companies, including Visa, Mastercard, Stripe, Coinbase, and BlackRock, announced OUSD (Open USD, from Open Standard) as a consortium. Non-dollar stablecoins pegged to national currencies such as the Korean won, the Japanese yen, and the euro are also becoming more common. Their combined market cap remains small at $1.2 billion, but the number of wallets holding them grew thirtyfold, from 40,000 in January 2023 to 1.2 million in March 2026.

Stablecoins are no longer just a fixed-value payment instrument. They are evolving into settlement infrastructure that operates independent of borders and time zones.

4.2. DeFi: Built to Replace Banks, Now Part of Financial Infrastructure

DeFi refers to smart-contract-based finance that enables lending, trading, and derivatives without a centralized intermediary.

Aave: market cap of $1.397 billion, TVL of $14.53 billion, annual revenue of $119 million, the leading DeFi lending protocol.
Morpho: market cap of $1.302 billion, TVL of $7.497 billion, annual revenue of $0 (its $222 million in annual fees goes entirely to lenders), briefly overtook Aave in market cap from late May through June before Aave regained the lead in July.
Uniswap: market cap of $2.287 billion, TVL of $3.14 billion, annual revenue of $850 million, the leading decentralized exchange with $2.66 billion in 24-hour trading volume.
Hyperliquid: market cap of $13.47 billion, TVL of $6.07 billion, annual revenue of $874 million, accounting for about 76% of the perpetual futures DEX category’s market cap and roughly 20% of DeFi overall, with an on-chain perpetuals market share as high as 70%.

DeFi began in 2020 on the decentralized premise of returning the profits earned by intermediaries such as banks to users directly.

Today, it persists less on that ideology than on institutional demand for on-chain financial infrastructure. Morpho and Aave provide the vault risk management and lending infrastructure institutions want, Uniswap supports trading in the assets institutions want to trade, and Hyperliquid supports trading in traditional assets rather than crypto alone.

Each has moved in a direction somewhat different from its founding ideology, but it was precisely this willingness to pivot decisively toward real demand that allowed these protocols to survive and grow.

4.3. RWA: From Democratizing Traditional Assets to Efficiency

RWA refers to the tokenization and on-chain distribution of traditional real-world assets such as Treasuries and private credit. The category’s market cap is $65.2 billion, with tokenized Treasuries the largest subcategory at $13.4 billion.

Ondo Finance: TVL of $3.52 billion, ONDO market cap of $1.75 billion, a leading provider of tokenized Treasury infrastructure.
BlackRock BUIDL: AUM of $2.4 billion, with no market cap in the conventional sense since it is a NAV-linked fund token, the largest single tokenized Treasury fund.
Maple Finance: SYRUP market cap of $218 million, with $4 billion in private credit AUM, exceeding BlackRock BUIDL.

RWA set out to bring traditional asset management on-chain in order to improve settlement speed and accessibility. Its initial customer base was not institutional. The sector began with synthetic asset exchanges that used the fact that on-chain markets sat outside existing regulation to lower the barriers to trading real-world assets. Today, however, institutions make up the sector’s largest user base.

Tokenized equities are a development worth watching closely. Adoption by traditional institutions such as Securitize and the DTCC is increasing. In July 2026, the DTCC began live trading of tokenized securities with more than 50 institutions, and Securitize listed its own shares, SECZ, on the NYSE while simultaneously issuing tokenized shares across multiple chains, including Avalanche and Solana. Centralized exchanges such as Binance (bStocks) and Kraken (xStocks) are also expanding their tokenized equity offerings across various countries. The tokenized equity category’s market cap reached $2.3 billion in mid-July 2026, nearly double its level since first crossing $1 billion in March.

Trading volume for these assets on decentralized exchanges remains minimal compared with DeFi, and most collateral use still relies on permissioned, whitelisted structures. Deeper on-chain integration, comparable to DeFi’s money-lego composability, will likely take more time. For now, the sector is still in the stage of proving the usefulness of on-chain asset management.

4.4. Prediction Markets: From Simple Betting to a Market-Leading Trend

Prediction markets are on-chain contract markets in which participants bet on the outcomes of real-world events. The category’s market cap is $9.58 billion, the most recently formed of the five sectors covered here.

It is also worth noting that the two platforms that actually dominate the sector, Kalshi and Polymarket, do not yet have tokens.

Kalshi: has raised $2 billion in cumulative funding at a $22 billion valuation, an 11x multiple on funding raised. Its June trading volume of $31.5 billion (up 87.4% month over month) already exceeds that valuation.
Polymarket: has raised roughly $1.6 billion in cumulative funding at a $9 billion valuation. June trading volume on its main platform outside the U.S. reached $10.26 billion (up 45% month over month), and annualized revenue has exceeded $1 billion since it gained approval to operate in the U.S.

The World Cup was both an opportunity and a challenge for prediction market platforms. It drove a sharp surge in trading volume through June, but after the final on July 19, combined open interest across the two platforms fell nearly 20% from its early-July peak of roughly $2 billion. Since sports contracts accounted for roughly 80% of total trading volume during the tournament, volume is likely to stay soft until the next major event, the U.S. midterm elections.

Regulatory risk also remains active. On July 21, 2026, a Washington state court issued a preliminary injunction barring Kalshi from selling sports event contracts on the grounds that they constitute illegal gambling under state law.

Before 2024, prediction markets did not even exist as a distinct category. Today, they are the fastest-growing segment of the crypto market. What sets this sector apart is that its growth has been demonstrated not through token market cap or TVL, but through real trading volume and revenue generated by drawing users from outside crypto into the on-chain ecosystem. This stands as one of the clearest examples to date of blockchain technology becoming part of everyday use for a broad audience.

4.5. Meme Tokens: From Simple Speculative Assets to a Liquidity Bootstrapping Strategy

The last sector is meme tokens. Unlike the other sectors discussed above, meme tokens have no clear utility. Their value comes from community and attention. The category’s market cap is $25.68 billion, larger than that of prediction markets.

Dogecoin ranks first at $11.22 billion, followed by Shiba Inu at $2.5 billion. Together, these two tokens account for 53.4% of the entire meme token category’s market cap, showing that once a token claims a symbolic position within the sector, even loosely, it tends to hold that position.

Pump.fun and CASHCAT are highlighted here not for their market cap ranking but for their symbolic significance.

Pump.fun: Market cap of $806 million, notable for raising $600 million in its public sale in July 2025 in just 12 minutes.
CASHCAT (Robinhood chain): Its market cap rose more than 2,100% within a week of launch, peaking above $200 million before falling roughly 75% from that peak to $59 million by July 17.

As the Robinhood chain case in July 2026 shows, meme token narratives can still momentarily pull in liquidity across an entire chain, a pattern seen in past cycles. The Robinhood chain’s TVL expanded sharply, from $17 million on July 3 to $312 million on July 13, and daily DEX trading volume climbed as high as $846.8 million on July 10, driven largely by the meme token CASHCAT.

The practical value of meme tokens lies in attracting early users and easing onboarding. A new chain or application can use a meme token to build a community quickly and naturally encourage activity such as bridging assets or trading on a DEX. Some of the users drawn in this way go on to use other DeFi services or applications within the ecosystem and stay active there, making the meme token an effective entry point and marketing channel.

In the end, meme tokens function less as long-term holdings and more as an initial tool for quickly bringing together users and liquidity. Whether that early attention can be converted into genuine product usage and lasting retention within the ecosystem is what determines success or failure.

5. What It Takes for a Project to Survive

The projects that have survived to this point have secured genuine demand that brings users back repeatedly, and they have demonstrated it through clear performance indicators such as trading volume, TVL, and fee revenue.

Demand in the 2026 market is concentrated at two distinct ends of the spectrum. At one end is speculative demand seeking high volatility and immediate rewards. Meme tokens, perpetual futures DEXs, and prediction markets absorb this demand effectively through rapid trading cycles and high capital turnover. At the other end is genuine financial demand for the stable custody, transfer, and efficient management of assets. Stablecoins, RWA, and DeFi infrastructure are fulfilling these core financial functions of payment, collateral, yield generation, and risk management.

Real product-market fit forms when a sustainable revenue structure and network effects are added to this base. A token’s price can generate initial attention, but long-term survival is determined by usage frequency, retained capital, revenue, and operational capability.

KBW, taking place in late September 2026, will offer a close view of this shift as it unfolds. Bo Hines, CEO of Tether U.S., Jeff Yan, co-founder of Hyperliquid, Johann Kerbrat, SVP of Robinhood Crypto, and Christine Moy of Apollo are among the leading figures driving these changes who will appear on stage together. Through conversations with key leaders in stablecoins, perpetual futures DEXs, and asset tokenization and RWA, attendees will be able to see firsthand the shift that has so far only been visible in the data.

Tiger Research is the exclusive research content partner for KBW 2026.

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Best Crypto Prop Firms in 2026

2026-07-24T09:45:16Z

Overview of Best Crypto Prop Firms

The top crypto prop firms compared in this article are HyroTrader, FTMO, Crypto Fund Trader, Breakout Prop, Bitfunded, TradeXProp, and FundedNext.

Simulated capital: nearly every firm in this space, including some of the largest, funds evaluated traders through simulated or notionally-calculated capital rather than a live brokerage deposit.
Real capital after a track record: HyroTrader is the only firm in this comparison with a path to real capital at all, becoming eligible after consistent performance and minimum profit of 10% profit target within a minimum of 5 trading days, for the One Step Challenge using simulated funds.
Review volume isn't crypto depth: FundedNext holds the highest review volume of any prop firm on Trustpilot, over 72,000 reviews at 4.5/5, yet its own Help Center lists only 9 crypto pairs at flat 1:1 leverage.

What Are Crypto Prop Firms

A prop (proprietary trading) firm lets you trade with the firm's capital instead of your own, in exchange for a share of the profits. You pay an upfront fee to attempt an evaluation. If you pass, you move to a "funded" account and start earning performance-based payouts.

Simulated Capital, Real Hedging

Here's the part that surprises a lot of traders: at nearly every firm in this space, including some of the largest, that funded account still runs on simulated or notionally-calculated capital, not a live brokerage deposit. TradeXProp calls its funded capital "notional." Bitfunded's own name for the post-evaluation stage is "Live Simulated Account." Even Breakout Prop, now owned by Kraken with its market data and connectivity tied to Kraken's exchange, states plainly that "all trading account balances consist entirely of simulated capital."

That doesn't mean your trades disappear into a void. When you open a position on a funded account, the firm can choose to mirror, or hedge, that same position on a real exchange using its own capital. If you're up $500 on a notional balance, the firm can hold a matching real position that's also up $500, so your payout is covered by an actual market gain rather than paid purely out of pocket.

Whether or how consistently a given firm actually does this varies, and most don't publish real-time proof either way, but the mechanism is what allows a firm to offer "funded" trading without holding a segregated real-money account for every single trader.

Comparison Table of Crypto Prop Firms

Firm	Crypto Pairs	Leverage	Execution	Profit Split	Payout Speed & Currency
HyroTrader	700+ (Bybit)	Up to 1:100	Real exchange execution, scaling to $1m after consistent performance and minimum 10% profit in one-step challenge.	80% → 90%	~24h, USDT/USDC, on-chain verifiable
FTMO	31+	1:1–1:3.3	Spot CFD	80% → 90%	1–2 business days
Crypto Fund Trader	550+ (Bybit)	Up to 1:100	Multi-asset, fully demo	80% → 90%	15–30 day cadence, up to 3 days processing
Breakout Prop	58–62+	5x (BTC/ETH), 2x (alts)	Kraken-backed, simulated	80% → 90%	On-demand, ~24h, USDC
Bitfunded	100+	1x–5x	Fully simulated	80:20 → 90:10	Monthly, USDT
TradeXProp	Not disclosed	5:1 (BTC/ETH), 2:1 (alts)	DXtrade, notional	Up to 90%	Every 30 days
FundedNext	9	1:1 flat	CFD, weekdays only	Up to 95%	~24h guarantee

HyroTrader: Real Exchange Execution with Verifiable On-Chain Payouts

This section is brought to you by HyroTrader.

HyroTrader launched in Prague in 2022 with a specific angle: that crypto traders deserved infrastructure built for crypto, not a forex platform with some coins bolted on. It became the first crypto prop firm to integrate directly with a major exchange, replacing the standard MT5/cTrader model with real Bybit order-book pricing and execution via API.

Crypto coverage: You get access to over 700 tradable pairs through Bybit, or 500+ through CLEO, its terminal built on Binance market data, and leverage runs up to 1:100. Trading pairs, price feeds, and order execution all come from the exchange itself, not a proprietary simulation layer standing in for one.

The evaluation phase uses simulated data like the rest of the prop firms on this list, but what happens after you pass is where HyroTrader diverges: passing evaluation moves you to a simulated funded account (same as every other firm), and you become eligible for real capital after consistent performance and meeting a minimum profit target of 10% in the One Step Challenge.

Key features: Profit splits start at 80% and scale to 90%. Your evaluation fee is fully refunded with your first payout, at no extra cost. Payouts are on-demand and processed in roughly 24 hours, paid in USDT or USDC, and every payout is recorded on Solana and independently verifiable on-chain, a concrete answer to a problem that's common across this industry, where payout claims are typically self-reported and impossible for an outside trader to check.

Account sizes range from $5,000 to $200,000, with a scaling path to $1,000,000 for consistently profitable traders. Bot and algorithmic strategies are permitted without restriction, and a free trial lets you test the evaluation environment before paying anything.

Track Record: HyroTrader launched in 2022, so its track record and review volume are still smaller than long-established multi-asset firms like FTMO. That said, since launch, it has paid out more than $5 million to over 1,700 funded traders, with a community of over 35,000-plus.

FTMO: A Multi-Asset Firm with Narrow Crypto Leverage

FTMO has operated since 2015 and carries the deepest trust signal in this list: a 4.8/5 Trustpilot score across roughly 45,000 reviews. It's a multi-asset firm first, with forex, indices, commodities, stocks, and crypto all trading on the same infrastructure.

Crypto coverage: FTMO lists 31 confirmed crypto pairs, spanning majors alongside a reasonable spread of DeFi and NFT-adjacent tokens (AAVE, UNI, GRT, IMX). But every pair trades as a Spot CFD, and FTMO's own blog states crypto leverage is capped at 1:1 on Swing accounts and 1:3.3 on Normal accounts, against up to 1:100 on forex. Trading hours can also vary due to scheduled maintenance windows, an odd fit for an asset class that otherwise runs 24/7.

Key features: Profit split starts at 80% and scales to 90%. Payouts process in 1–2 business days, paid in BTC, ETH, LTC, USDC, or USDT. The fee refund depends on which product you buy: the 2-Step Challenge refunds your fee with your first reward; the 1-Step Challenge never refunds it, even after passing.

Crypto Leverage: FTMO's forex-first architecture shows up directly in the numbers: leverage on crypto sits at a fraction of what's available on its own forex pairs, which is a key consideration if crypto is your primary market rather than a side allocation.

Crypto Fund Trader: Broad Bybit-Powered Instrument Access

Crypto Fund Trader (CFT) offers evaluations across crypto, forex, indices, commodities, and stocks, with roughly 1,100 Trustpilot reviews.

Crypto coverage: CFT's FAQ confirms 550+ crypto futures pairs through Bybit, or 720+ total instruments across its Match-Trader/MT5 setup, offering broad coverage. Leverage on Bybit evaluations runs up to 1:100.

Key features: Profit split runs 80% to 90%. Individual evaluation accounts go up to $200,000, but traders can hold multiple funded accounts at once, up to a combined $300,000 in total live capital per user. Withdrawals are available after 15 days traded, or every 30 calendar days as an alternative, with processing taking up to roughly three days end-to-end. CFT states outright on its homepage: "It's all demo, no real capital involved."

Evaluation Refund Policy: CFT's evaluation refund policy is the least specific in this group. Its official refund page states refunds are "issued at our discretion," without the fixed payout milestone that FTMO, FundedNext, Bitfunded, and Breakout all publish.

Breakout Prop: Kraken-Backed Liquidity with Conservative Leverage

Breakout Prop was acquired by Kraken in September 2025, giving it the strongest crypto exchange pedigree of any crypto-native firm in this comparison, alongside roughly 950 Trustpilot reviews at a 4-star average.

Crypto coverage: Breakout offers 58 to 62-plus crypto pairs, with real liquidity sourced from major exchanges. Leverage is fixed at 5x on BTC and ETH, 2x on everything else, applied automatically. Markets run genuinely 24/7, including weekends.

Key features: Profit split defaults to 80%, with a permanent 90% upgrade available at checkout. Payouts are on-demand, processed in about 24 hours, paid in USDC, and the fee is fully refunded with the first payout. Breakout's own Program Rules confirm funded balances are simulated capital, and disclose that individual trade ideas may be routed to a real exchange or logged as an internal calculation, at the firm's discretion, though payouts are calculated identically either way.

Leverage Cap: Leverage is capped well below several peers, a deliberate risk-management choice rather than an oversight, and worth weighing against firms offering higher multiples.

Bitfunded: 100+ Crypto Pairs with a Conservative Leverage Model

Bitfunded is a crypto-only firm with more than 120,000 traders and roughly 162 Trustpilot reviews at a 4-star average.

Crypto coverage: Bitfunded offers 100+ crypto pairs plus 20+ traditional-finance instruments, with leverage capped between 1x and 5x, which Bitfunded frames explicitly as a design choice to reduce over-leveraging rather than a limitation.

Key features: The default split is 80:20, scaling to 90:10 through an Incentive Scaling Program requiring 10% net profit over four consecutive months. News and weekend trading are both allowed, which is unusual among firms with TradFi roots. Its refund policy is less consistent, though: Bitfunded's Refund and Cancellation Policy and its Terms of Use both state the fee is refunded on your first profit-split day, but its FAQ page states it's refunded on your third payout instead. Users considering Bitfunded may want to check in directly with support around which one currently applies.

Withdrawal Cadence: Withdrawals are processed monthly, a slower cadence than the 24-hour standard several crypto-native competitors offer.

TradeXProp: A Dedicated Crypto Challenge with Flexible Trading Hours

TradeXProp runs a dedicated crypto evaluation track, though with a considerably thinner track record (around 41 Trustpilot reviews) than most firms here.

Crypto coverage: Leverage runs 5:1 on BTC and ETH, 2:1 on everything else. Notably, TradeXProp doesn't publish an actual pair count anywhere on its site, only that it offers "any products streamed by the Liquidity Provider." Trading runs close to 24/7, and weekend holding is permitted.

Key features: Profit split reaches up to 90%. The funded stage is explicitly described as "notionally-funded," meaning actual capital may not match the account's nominal size. To date, TradeXProp has paid out $1.9 million-plus to more than 5,000 traders.

Refunds and Withdrawals: Two things stand out: fees are never refunded, even after passing, and withdrawals are limited to once every 30 days; both more restrictive than the rest of this list. TradeXProp also carries over a forex-style rule prohibiting trades within three minutes of a "News Event," a category the firm defines at its sole discretion.

FundedNext

FundedNext holds the highest review volume of any prop firm on Trustpilot (over 72,000 reviews at 4.5/5) and has paid out more than $300 million across its full product range since 2022.

Crypto coverage: FundedNext's own Help Center lists exactly 9 crypto pairs: DOGE, ADA, XLM, XRP, BTC, ETH, LINK, LTC, and XMR, notably excluding SOL and BNB, two of the largest coins by market cap. Crypto leverage is flat at 1:1, against up to 1:100 on forex, and crypto positions can only be opened or closed on weekdays, with the firm's own disclaimer confirming trades are CFD simulations rather than real asset purchases.

Key features: Profit split reaches up to 95% on CFD accounts, among the highest in the industry. FundedNext guarantees payouts within 24 hours, backed by a $1,000 penalty if it misses that window, with a median processing time of 4.74 hours. Fee refunds apply, though timing depends on the product: first payout for Stellar 2-Step, third payout for Stellar 1-Step and Stellar Lite as of a January 2026 policy update.

Narrow Pair Count: FundedNext is a genuinely well-reviewed, fast-paying firm, but its scale comes from forex and multi-asset trading, not crypto. A 9-pair, 1:1-leverage, weekdays-only crypto offering is a fraction of what dedicated crypto firms provide, making it a clear example of why review volume alone doesn't indicate crypto-specific depth.

How to Choose

If real exchange execution and eventual access to real capital matter most, HyroTrader is the only firm in this list that offers both. If you're prioritizing sheer instrument count, Crypto Fund Trader and Bitfunded both offer deep pair lists, though both remain fully simulated indefinitely. If Kraken’s ownership-backed infrastructure and fast on-demand payouts matter more than maximum leverage, Breakout is the strongest fit. And if you're evaluating any firm by Trustpilot volume alone, FundedNext is the clearest reminder to check the actual crypto instrument list first: a large review count says nothing about how deep, or how real, the crypto offering underneath it actually is.

The pattern across this list is consistent: a firm's crypto offering is only as serious as the infrastructure behind it. Pair counts, leverage limits, and refund policies all trace back to the same underlying question: whether crypto was the product the firm was built around, or an asset class added to an existing forex stack. Before committing an evaluation fee to any firm, it's worth checking that answer directly against the firm's own site rather than its review score.

Disclaimer: Rankings, comparisons, and commentary reflect independent research based on publicly available information from each firm's official website, help center, and terms of service as of the time of writing. Figures such as leverage limits, profit splits, pair counts, and payout policies are subject to change at each firm's discretion; readers should verify current terms directly with the provider before making a decision. This content is for informational purposes only and does not constitute financial, investment, or trading advice. Proprietary trading, and cryptocurrency trading more broadly, carries substantial risk, including the risk of losing your evaluation fee. CoinGecko does not endorse any prop trading firm and encourages readers to conduct their own research before participating in any evaluation program.

How to Track Tokenized Stocks & Real World Assets (RWAs) Across Solana, Ethereum, Robinhood & 200+ Chains

2026-07-24T07:17:46Z

TL;DR

CoinGecko API tracks tokenized stocks across major blockchains, using tokenized-stock categories for discovery and the /coins/markets endpoints to retrieve prices.
GeckoTerminal’s onchain endpoints provide deeper market insights, including liquidity, holder concentration, and daily OHLCV data for tokenized assets across Solana, Ethereum, Robinhood, and 200+ other chains.

Tokenized stocks such as the ones issued by xStocks, Ondo Finance, and bStocks can trade onchain across Solana, Ethereum, Robinhood, and many more chains. These tokens support continuous trading, allowing you to access price, liquidity, and trading activity at any time.

In this guide, you'll build a Python toolkit using the CoinGecko API to discover tokenized stocks, retrieve market, liquidity, holder, and historical data, and stream real-time updates via WebSockets.

What Are Tokenized Stocks and How Do You Track Them Onchain?

Tokenized stocks are blockchain tokens that represent exposure to real-world equities or ETFs. Issuers such as Backed (provider behind xStocks) hold the underlying assets and issue tokens designed to track their value, typically on a roughly 1:1 basis. These tokens are issued across multiple networks, including Solana as SPL tokens, Ethereum and other EVM-compatible chains as ERC-20 tokens, and the Robinhood chain. Because multiple issuers can tokenize the same equity across different blockchains, a single stock may exist as several distinct onchain tokens. For example, Tesla has separate tokenized versions from issuers including Backed, Ondo Finance, BTech Holdings, and Robinhood Europe.

Tokenized stocks offer several advantages compared to traditional equities, including 24/7 trading, fractional ownership that lowers the barrier to accessing higher-priced shares, and seamless integration with DeFi and other Web3 infrastructure. Their onchain settlement also enables them to be used as collateral, supplied to liquidity pools to earn trading fees, or deposited into lending protocols to mint stablecoins that can be staked for yield, and incorporated into decentralized applications.

Prerequisites & Setup

You'll need a CoinGecko API key. If you don't have one, follow the guide to get a free Demo API key.

Create a project folder with two files: requirements.txt lists the dependencies, and .env that stores your API key

requests
pandas
matplotlib
websocket-client
coingecko-sdk
python-dotenv

Install with pip.

pip install -r requirements.txt

1
2

COINGECKO_API_KEY=CG-your_api_key_here
COINGECKO_PLAN=demo

Next, set up a configuration module that reads your API key and plan from the environment, then builds the correct base URL and headers for each request.

import os
from dotenv import load_dotenv

load_dotenv()

API_KEY = os.getenv("COINGECKO_API_KEY", "")
# Switch to "pro" in your .env when you upgrade to a paid plan
PLAN = os.getenv("COINGECKO_PLAN", "demo").lower()

# Demo and paid plans use different base URLs and header names
if PLAN == "pro":
    BASE_URL = "https://pro-api.coingecko.com/api/v3"
    HEADERS = {"x-cg-pro-api-key": API_KEY}
else:
    BASE_URL = "https://api.coingecko.com/api/v3"
    HEADERS = {"x-cg-demo-api-key": API_KEY}

# Onchain (GeckoTerminal) endpoints live under the /onchain path on the same host
ONCHAIN_URL = f"{BASE_URL}/onchain"

Every endpoint in this guide can also be called using CoinGecko's official Python SDK or TypeScript SDK instead of raw HTTP requests. The SDKs handle the base URL, headers, and authentication for you.

How to Discover Tokenized Stock Tokens

CoinGecko API enables you to discover tokenized stocks using category filtering to identify relevant assets. Start with the Coins Categories List endpoint to identify category names and IDs, including xstocks-ecosystem for Backed’s xStocks, robinhood-chain-stocks-ecosystem for Robinhood’s tokenized stocks, and the broader tokenized-stock category. Pass the selected category ID to /coins/markets to retrieve token prices, market caps, and 24-hour volumes, with up to 250 tokens returned per page. Then use /coins/{id} to retrieve each token’s cross-chain contract addresses from the detail_platforms field for subsequent onchain queries.

import requests
from config import BASE_URL, HEADERS

def get_category_ids():
    url = f"{BASE_URL}/coins/categories/list"
    response = requests.get(url, headers=HEADERS)
    response.raise_for_status()
    return response.json()

# --- Optional: same request using the CoinGecko Python SDK ---
# Install it with: pip install coingecko-sdk
#
# from coingecko_sdk import Coingecko
#
# client = Coingecko(demo_api_key="YOUR_API_KEY", environment="demo")
# categories = client.coins.categories.get_list()
#
# On a paid plan, use: Coingecko(pro_api_key="YOUR_API_KEY", environment="pro")

def get_tokens_in_category(category_id):
    # per_page accepts up to 250; page through if a category is larger
    url = f"{BASE_URL}/coins/markets"
    params = {"vs_currency": "usd", "category": category_id, "per_page": 250, "page": 1}
    response = requests.get(url, headers=HEADERS, params=params)
    response.raise_for_status()
    return response.json()

# SDK equivalent: client.coins.markets.get(vs_currency="usd", category="xstocks-ecosystem")

def get_contract_addresses(coin_id):
    # tickers, market_data, community_data, and developer_data default to true
    # on this endpoint; disabling them keeps the response small
    url = f"{BASE_URL}/coins/{coin_id}"
    params = {"localization": "false", "tickers": "false", "market_data": "false",
              "community_data": "false", "developer_data": "false"}
    response = requests.get(url, headers=HEADERS, params=params)
    response.raise_for_status()
    return response.json().get("detail_platforms", {})

# SDK equivalent: client.coins.get_id("tesla-xstock", localization=False, tickers=False, market_data=False)

if __name__ == "__main__":
    # Step 1: find the category ID for the tokenized stocks you want
    categories = get_category_ids()
    for c in categories:
        if "stock" in c["category_id"]:
            print(c["category_id"], "-", c["name"])

    # Step 2: pull every token in that category, then resolve its contract addresses
    tokens = get_tokens_in_category("xstocks-ecosystem")
    rows = [
        {"symbol": t["symbol"].upper(), "coingecko_id": t["id"],
         "asset_platform": platform, "contract_address": details.get("contract_address")}
        for t in tokens[:10]
        for platform, details in get_contract_addresses(t["id"]).items()
    ]

    # Fixed-width print so columns line up regardless of address length
    print(f"{'SYMBOL':<8}{'COINGECKO_ID':<16}{'ASSET_PLATFORM':<16}{'CONTRACT_ADDRESS'}")
    print("-" * 90)
    for r in rows:
        print(f"{r['symbol']:<8}{r['coingecko_id']:<16}{r['asset_platform']:<16}{r['contract_address']}")

Running this script produces output like the following:

This same code also works for other tokenized real-world assets. Replace the category ID such as tokenized-commodities, tokenized-gold, or tokenized-exchange-traded-funds-etfs. For a deeper look at tokenized commodities, our guide on tracking gold, silver & tokenized commodities covers the topic in greater detail.

If you prefer working in spreadsheets, the same category IDs and logic work through CoinGecko's official Google Sheets and Excel add-ons. See our guides on pulling crypto prices into Google Sheets and tokenized stock prices into Excel to get started.

How to Get a Tokenized Stock's Price, Volume, and Liquidity Across Chains

CoinGecko’s aggregated market data endpoints provide price, market cap, and volume data, while GeckoTerminal provides onchain liquidity data through the same API credentials. The /coins/markets and /coins/{id} endpoints are the primary way to retrieve a tokenized stock’s price and market cap, as these figures are aggregated across all venues where the token trades. For a single token or short custom list, the /simple/price endpoint provides a simpler way to retrieve price data in a single request.

These endpoints work for any tokenized assets such as stocks, commodities, or ETF. The code below uses Tesla, Nvidia, and the S&P 500 ETF (SPYX). Simply replace the coin IDs with those identified during discovery.

import requests
from config import BASE_URL, HEADERS

def get_simple_price(coin_ids):
    # Lightweight price lookup for specific tokenized stocks by coin ID
    url = f"{BASE_URL}/simple/price"
    params = {
        "ids": ",".join(coin_ids),
        "vs_currencies": "usd",
        "include_market_cap": "true",
        "include_24hr_vol": "true",
        "include_24hr_change": "true",
    }
    response = requests.get(url, headers=HEADERS, params=params)
    response.raise_for_status()
    return response.json()

# SDK equivalent: client.simple.price.get(ids="tesla-xstock,nvidia-xstock,sp500-xstock", vs_currencies="usd", include_market_cap=True, include_24hr_vol=True, include_24hr_change=True)

if __name__ == "__main__":
    prices = get_simple_price(["tesla-xstock", "nvidia-xstock", "sp500-xstock"])
    for coin_id, data in prices.items():
        print(coin_id, f"${data['usd']:,.2f}", f"{data['usd_24h_change']:+.2f}% 24h",
              f"mcap ${data['usd_market_cap']:,.0f}", f"vol ${data['usd_24h_vol']:,.0f}")

Here is an example of how the output looks like:

Neither aggregated endpoint provides liquidity data, because liquidity is measured at the individual pool level. To see where a tokenized stock trades and the liquidity available on each chain, use the contract addresses from detail_platforms with the /onchain/networks/{network}/tokens/{token_address}/pools endpoint.

import requests
from config import HEADERS, ONCHAIN_URL

def build_network_map():
    # e.g. "ethereum" maps to "eth", "arbitrum-one" maps to "arbitrum"
    network_map = {}
    for page in range(1, 4):
        response = requests.get(f"{ONCHAIN_URL}/networks", headers=HEADERS, params={"page": page})
        response.raise_for_status()
        for net in response.json()["data"]:
            platform = net["attributes"].get("coingecko_asset_platform_id")
            if platform:
                network_map[platform] = net["id"]
    return network_map

# SDK equivalent: client.onchain.networks.get(page=1)

def get_pools_for_token(network_id, token_address):
    # ranked by a combination of liquidity and 24-hour volume
    url = f"{ONCHAIN_URL}/networks/{network_id}/tokens/{token_address}/pools"
    response = requests.get(url, headers=HEADERS)
    response.raise_for_status()
    return response.json()["data"]

# SDK equivalent: client.onchain.networks.tokens.pools.get(token_address, network=network_id)

def get_liquidity_across_chains(detail_platforms, network_map):
    rows = []
    for asset_platform, details in detail_platforms.items():
        network_id = network_map.get(asset_platform)
        if not network_id:
            continue
        for pool in get_pools_for_token(network_id, details["contract_address"]):
            rows.append({
                "network": network_id,
                "pool": pool["attributes"]["name"],
                "pool_address": pool["attributes"]["address"],
                # GeckoTerminal returns these as strings, cast to float and round for display
                "liquidity_usd": round(float(pool["attributes"]["reserve_in_usd"]), 2),
                "volume_24h": round(float(pool["attributes"]["volume_usd"]["h24"]), 2),
            })
    return rows

if __name__ == "__main__":
    # detail_platforms comes from get_contract_addresses() in the discovery step
    tesla_platforms = {
        "solana": {"contract_address": "XsDoVfqeBukxuZHWhdvWHBhgEHjGNst4MLodqsJHzoB"},
        "ethereum": {"contract_address": "0x8ad3c73f833d3f9a523ab01476625f269aeb7cf0"},
    }
    rows = get_liquidity_across_chains(tesla_platforms, build_network_map())

    print(f"{'NETWORK':<8}{'POOL':<18}{'POOL_ADDRESS':<16}{'LIQUIDITY_USD':>14}{'VOLUME_24H':>12}")
    print("-" * 68)
    for r in rows:
        # Truncate the address for a readable print; rows still holds the full value for reuse
        addr = r["pool_address"]
        short_addr = f"{addr[:6]}...{addr[-4:]}"
        print(f"{r['network']:<8}{r['pool']:<18}{short_addr:<16}{r['liquidity_usd']:>14,.2f}{r['volume_24h']:>12,.2f}")

The response returns the following output:

💡 Pro Tip: If you only need a token’s price and liquidity on a known chain, the /onchain/simple/networks/{network}/token_price/{addresses} endpoint returns price, 24-hour volume, 24-hour change, and total liquidity (with include_total_reserve_in_usd=true) in a single call, without requiring individual pool lookups.

How to Track Holders of a Tokenized Stock

CoinGecko’s Token Info by Token Address endpoint returns a holder snapshot, including the total holder count and a breakdown of token supply distribution among the top holders.

import requests
from config import HEADERS, ONCHAIN_URL

def get_holder_snapshot(network_id, token_address):
    url = f"{ONCHAIN_URL}/networks/{network_id}/tokens/{token_address}/info"
    response = requests.get(url, headers=HEADERS)
    response.raise_for_status()
    return response.json()["data"]["attributes"]["holders"]

# SDK equivalent: client.onchain.networks.tokens.info.get(token_address, network=network_id)

if __name__ == "__main__":
    holders = get_holder_snapshot("solana", "Xsc9qvGR1efVDFGLrVsmkzv3qi45LTBjeUKSPmx9qEh")  # Nvidia xStock; any tokenized stock works
    print("Total holders:", holders["count"])
    print("Distribution:", holders["distribution_percentage"])

Here is an example of how the output looks like:

For deeper holder, wallet, and trading analysis, the following endpoints are available on the Analyst plan and above:

Top Token Holders by Token Address: Ranked individual wallets with their balances and share of supply
Historical Token Holders Chart by Token Address: Holder count over time, for charting growth trends
Top Token Traders by Token Address: Wallets ranked by realized and unrealized profit
Past 24 Hour Trades by Token Address: Returns a token’s last 300 trades across all pools in the past 24 hours, including buy/sell direction, token amounts, and USD volume

import requests
from config import HEADERS, ONCHAIN_URL

def get_top_holders(network_id, token_address, limit=10):
    url = f"{ONCHAIN_URL}/networks/{network_id}/tokens/{token_address}/top_holders"
    response = requests.get(url, headers=HEADERS, params={"holders": limit})
    response.raise_for_status()
    return response.json()["data"]["attributes"]["holders"]

# SDK equivalent: client.onchain.networks.tokens.top_holders.get(token_address, network=network_id, holders="10")

def get_holders_chart(network_id, token_address, days="30"):
    url = f"{ONCHAIN_URL}/networks/{network_id}/tokens/{token_address}/holders_chart"
    response = requests.get(url, headers=HEADERS, params={"days": days})
    response.raise_for_status()
    return response.json()["data"]["attributes"]["token_holders_list"]

# SDK equivalent: client.onchain.networks.tokens.holders_chart.get(token_address, network=network_id, days="30")

def get_recent_trades(network_id, token_address, min_volume_usd=0):
    url = f"{ONCHAIN_URL}/networks/{network_id}/tokens/{token_address}/trades"
    params = {"trade_volume_in_usd_greater_than": min_volume_usd}
    response = requests.get(url, headers=HEADERS, params=params)
    response.raise_for_status()
    return response.json()["data"]

# SDK equivalent: client.onchain.networks.tokens.trades.get(token_address, network=network_id)

if __name__ == "__main__":
    # amount, percentage, and value come back as strings; round for display
    print(f"{'RANK':<6}{'ADDRESS':<16}{'AMOUNT':>14}{'PERCENTAGE':>12}{'VALUE_USD':>16}")
    print("-" * 64)
    for h in get_top_holders("solana", "Xsc9qvGR1efVDFGLrVsmkzv3qi45LTBjeUKSPmx9qEh"):
        addr = h["address"]
        short_addr = f"{addr[:6]}...{addr[-4:]}"
        pct = h["percentage"] + "%"
        value = f"${round(float(h['value']), 2):,.2f}"
        print(f"{h['rank']:<6}{short_addr:<16}{round(float(h['amount']), 2):>14,.2f}{pct:>12}{value:>16}")

    chart = get_holders_chart("solana", "Xsc9qvGR1efVDFGLrVsmkzv3qi45LTBjeUKSPmx9qEh", days="30")
    print(f"\n{'TIMESTAMP':<22}{'HOLDER_COUNT':>14}")
    print("-" * 36)
    for timestamp, holder_count in chart[-3:]:
        print(f"{timestamp:<22}{holder_count:>14}")

    print(f"\n{'KIND':<6}{'VOLUME_USD':>12}  {'TIMESTAMP':<22}{'POOL':<16}")
    print("-" * 60)
    for t in get_recent_trades("solana", "Xsc9qvGR1efVDFGLrVsmkzv3qi45LTBjeUKSPmx9qEh", min_volume_usd=1000)[:5]:
        attrs = t["attributes"]
        pool = attrs["pool_address"]
        short_pool = f"{pool[:6]}...{pool[-4:]}"
        print(f"{attrs['kind']:<6}{round(float(attrs['volume_in_usd']), 2):>12,.2f}  {attrs['block_timestamp']:<22}{short_pool:<16}")

Running this script produces output like the following:

How to Get Historical Price and OHLCV Data for a Tokenized Stock

To retrieve historical price, market cap, and volume data for a tokenized stock, /coins/{id}/market_chart returns aggregated market data over time for tokens listed on CoinGecko, making it useful for tracking historical performance.

Note: The free Demo plan supports up to 365 days of historical data. To access a token’s full available history from its first trading date, upgrade to the Analyst plan and above.

import pandas as pd
import requests
from config import BASE_URL, HEADERS

def get_historical_price(coin_id, days="30"):
    url = f"{BASE_URL}/coins/{coin_id}/market_chart"
    params = {"vs_currency": "usd", "days": days}
    response = requests.get(url, headers=HEADERS, params=params)
    response.raise_for_status()
    return response.json()

# SDK equivalent: client.coins.market_chart.get("tesla-xstock", vs_currency="usd", days="30")

if __name__ == "__main__":
    data = get_historical_price("tesla-xstock", days="30")
    df = pd.DataFrame(data["prices"], columns=["timestamp", "price"])
    df["date"] = pd.to_datetime(df["timestamp"], unit="ms")

    print(f"{'DATE':<18}{'PRICE':>10}")
    print("-" * 28)
    for _, row in df[["date", "price"]].tail().iterrows():
        print(f"{row['date'].strftime('%Y-%m-%d %H:%M'):<18}{row['price']:>10,.2f}")

The response returns the following output:

For candlestick charting, query the /onchain/networks/{network}/pools/{pool_address}/ohlcv/{timeframe} endpoint to retrieve OHLCV data for a selected pool. Resolve a token’s most liquid pool from its contract address using the /onchain/networks/{network}/tokens/{token_address}/pools endpoint. The response ranks pools by liquidity and 24-hour volume, with the first result representing the highest-ranked pool.

Each OHLCV candle includes a timestamp, open, high, low, close, and volume, allowing direct use in pandas for charting or indicator calculations. Instead of manually aggregating data, you can use timeframe and aggregate to request the candle interval needed. Each request returns up to 1,000 candles over a maximum six-month window, with before_timestamp available for retrieving older history.

import pandas as pd
import requests
from config import HEADERS, ONCHAIN_URL

def get_top_pool_address(network_id, token_address):
    url = f"{ONCHAIN_URL}/networks/{network_id}/tokens/{token_address}/pools"
    response = requests.get(url, headers=HEADERS)
    response.raise_for_status()
    pools = response.json()["data"]
    return pools[0]["attributes"]["address"] if pools else None  # sorted by liquidity + 24h volume, so the first is the most liquid

# SDK equivalent: client.onchain.networks.tokens.pools.get(token_address, network=network_id)

def get_pool_ohlcv(network_id, pool_address, timeframe="day", limit=30):
    url = f"{ONCHAIN_URL}/networks/{network_id}/pools/{pool_address}/ohlcv/{timeframe}"
    response = requests.get(url, headers=HEADERS, params={"limit": limit})
    response.raise_for_status()
    return response.json()["data"]["attributes"]["ohlcv_list"]

# SDK equivalent: client.onchain.networks.pools.ohlcv.get_timeframe("day", network=network_id, pool_address=pool_address, limit=limit)

if __name__ == "__main__":
    # Tesla xStock on Solana; resolve its most liquid pool from the token's contract address
    network_id, token_address = "solana", "XsDoVfqeBukxuZHWhdvWHBhgEHjGNst4MLodqsJHzoB"

    pool_address = get_top_pool_address(network_id, token_address)

    candles = get_pool_ohlcv(network_id, pool_address, timeframe="day", limit=30)
    df = pd.DataFrame(candles, columns=["timestamp", "open", "high", "low", "close", "volume"])
    df["date"] = pd.to_datetime(df["timestamp"], unit="s")

    print(f"{'DATE':<12}{'OPEN':>10}{'HIGH':>10}{'LOW':>10}{'CLOSE':>10}{'VOLUME':>14}")
    print("-" * 66)
    for _, row in df.tail().iterrows():
        print(f"{row['date'].strftime('%Y-%m-%d'):<12}{row['open']:>10,.2f}{row['high']:>10,.2f}{row['low']:>10,.2f}{row['close']:>10,.2f}{row['volume']:>14,.2f}")

Running this script produces output like the following:

Charting this response makes trends easier to interpret at a glance. The chart below plots the same pool OHLCV data retrieved by get_pool_ohlcv():

To simplify your workflow, you can skip the pool-resolution step entirely and query OHLCV data directly by token contract using the Token OHLCV Chart by Token Address endpoint. It supports the same timeframe, aggregate, limit, and before_timestamp parameters.

Note: This endpoint is available exclusively on the Analyst plan and above.

With this same OHLCV data, you can go beyond plotting it and calculate technical indicators such as RSI, MACD, and Bollinger Bands. Our guide on automating crypto technical analysis with Python walks through the setup in detail.

How to Stream Tokenized Stock Prices, OHLCV, and Trades via Websockets

CoinGecko's WebSocket streams real-time tokenized stock data by maintaining a persistent connection and pushing updates as they happen, instead of cached snapshots with REST API polling. It provides live price, trade, and candlestick updates with ultra-low latency, making it ideal for real-time dashboards, trading applications, and monitoring fast-moving tokenized assets.

Update as of June 2026: CoinGecko WebSockets are now available on the Basic plan starting at just $29/month.

Connect to wss://stream.coingecko.com/v1 with your API key, then subscribe to the channels and specify the tokens or pools you want to monitor. The example below subscribes to CGSimplePrice, OnchainOHLCV, and OnchainTrade in a single connection, streaming Tesla xStock's aggregated price, live candlesticks, and pool-level swaps on Solana all at once.

import json
import websocket
from config import API_KEY

NETWORK_ID = "solana"
POOL_ADDRESS = "8aDaBQkTrS6HVMjyc6EZebgdiaXhLYGriDWKWWp1NpFF"  # Tesla xStock / USDC
COIN_ID = "tesla-xstock"

def on_open(ws):
    # Subscribe to all three channels, then tell each one what to watch
    for channel in ("CGSimplePrice", "OnchainOHLCV", "OnchainTrade"):
        ws.send(json.dumps({"command": "subscribe", "identifier": json.dumps({"channel": channel})}))

    ws.send(json.dumps({
        "command": "message",
        "identifier": json.dumps({"channel": "CGSimplePrice"}),
        "data": json.dumps({"coin_id": [COIN_ID], "vs_currencies": ["usd"], "action": "set_tokens"}),
    }))
    ws.send(json.dumps({
        "command": "message",
        "identifier": json.dumps({"channel": "OnchainOHLCV"}),
        "data": json.dumps({
            "network_id:pool_addresses": [f"{NETWORK_ID}:{POOL_ADDRESS}"],
            "interval": "1m",
            "token": "base",
            "action": "set_pools",
        }),
    }))
    ws.send(json.dumps({
        "command": "message",
        "identifier": json.dumps({"channel": "OnchainTrade"}),
        "data": json.dumps({
            "network_id:pool_addresses": [f"{NETWORK_ID}:{POOL_ADDRESS}"],
            "action": "set_pools",
        }),
    }))

def on_message(ws, message):
    data = json.loads(message)
    # OnchainTrade payloads carry "ty" (b/s); OnchainOHLCV uses "ch" for channel type
    # (not "c"); CGSimplePrice uses "c":"C1". Checking in this order avoids key collisions.
    if "ty" in data:
        side = "BUY" if data["ty"] == "b" else "SELL"
        print(f"[TRADE] {side} {data['vo']:.2f} USD at ${data['pu']:.2f}  tx={data['tx'][:10]}...")
    elif "ch" in data:
        print(f"[OHLCV] {data['i']} candle  O:{data['o']:.2f} H:{data['h']:.2f} L:{data['l']:.2f} C:{data['c']:.2f}")
    elif data.get("c") == "C1":
        print(f"[PRICE] {data['i']} ${data['p']:.2f}  {data['pp']:+.2f}% 24h")
    else:
        print("Status:", data.get("message", data))

if __name__ == "__main__":
    url = f"wss://stream.coingecko.com/v1?x_cg_pro_api_key={API_KEY}"
    ws = websocket.WebSocketApp(url, on_open=on_open, on_message=on_message)
    ws.run_forever()

The response returns the following output:

This same feed is visualized in real time on GeckoTerminal's TSLAX pool:

Conclusion

With CoinGecko API, you can build a Python workflow for tracking tokenized stocks across the full data lifecycle from discovering assets and retrieving market data to mapping liquidity pools, analyzing holders, fetching historical data, and streaming real-time updates across various chains.

The same workflow extends to other tokenized real-world assets. You can swap the category ID to track tokenized commodities, treasuries, or ETFs, allowing a single codebase to support a broader range of RWA assets as more markets move onchain.

To build a user-facing application with this data, explore our guide on building a crypto portfolio dashboard in Python. For deeper holder analysis, our token holders deep dive covers concentration metrics in more detail.

Ready to start building? Get your free Demo API key and start exploring tokenized stock data today. As your needs grow, upgrade to an entry-level Basic plan (from $29/mo) to access the full suite of data delivery methods, includes REST APIs, webhook, WebSocket streams, and a commercial license, while the Analyst plan ($129/month) adds exclusive endpoints such as Pools Megafilter, more API call credits, and higher rate limits.

Best Crypto API for Institutional Data in 2026

2026-07-24T06:01:59Z

TL;DR: Which Crypto API for Institutional Data is the Best?

CoinGecko API is best suited for institutional teams and crypto applications that need broad, auditable market data, aggregated crypto intelligence, and unified access to centralized and decentralized market data through a single API. Its flat 1-credit-per-request pricing enables cost-efficient scaling across portfolio, treasury, RWA, and compliance workflows.
Teams with specialized needs may be better served by providers such as Kaiko or CoinDesk Data for regulated benchmarks and indices, CoinAPI for tick-level execution and HFT workflows, and Amberdata for options analytics.

An institutional-grade crypto API provides reliable, auditable data that meets the standards expected by regulators, auditors, and risk committees. What qualifies as institutional-grade depends on the specific workflow. Funds launching regulated BTC or ETH futures products may need licensed benchmarks for pricing and settlement, while trading desks prioritize deep order-book data and low-latency feeds. Meanwhile, many custodians, neobanks, fintech platforms, and digital asset applications prioritize broad, reliable, and verifiable reference pricing across extensive assets, exchanges, and networks, where aggregated market coverage and transparent methodologies are critical.

This guide compares five APIs against the criteria institutions actually evaluate, so you can match a provider to your workflow.

What Makes a Crypto Data API Institutional-Grade?

An institutional-grade crypto data API should provide the reliability, transparency, and data depth required for institutional use and meet compliance standards. Below are the key criteria to evaluate when selecting a crypto data provider:

Compliance and trust

Compliance and trust are not just about having accurate data, but about proving the data can be trusted by regulators, auditors, and risk committees. Providers need strong security and compliance controls like SOC 2 Type II, auditable pricing methodology, and regulated benchmark administrator status where required. As frameworks such as MiCA and CARF take effect, greater emphasis on market transparency, governance, and tax reporting is increasing the need for accurate, auditable pricing data.

Coverage breadth

The number of assets covered and the range of markets supported, from CEX, DEX, derivatives, and onchain to emerging categories such as RWAs, tokenized assets, and treasuries.

Granularity and historical depth

Granularity refers to the level of detail in a provider's market data, ranging from daily, hourly candles to tick-level trades and full L2/L3 order-book data. Historical depth refers to how far back those records extend. Research, valuation, and reporting rely on deep, clean historical datasets, while trading desks need real-time market depth from L2/L3 order-book data.

Reliability and uptime

Reliability and uptime measure how consistently an API remains available and delivers accurate data in production. An SLA and transparent uptime reporting demonstrate a provider's commitment to that consistency. This matters because institutional systems such as pricing engines, customer-facing valuations, and risk and compliance reporting depend on reliable, uninterrupted data to support critical operations and meet regulatory reporting requirements.

Delivery methods and latency

Data delivery refers to how data reaches your systems and how quickly updates become available. No single delivery method is inherently superior. The right choice depends on your workflow, latency requirements, data volume, and integration needs.

Cost efficiency and pricing transparency

Cost efficiency measures how effectively costs align with data requirements and how predictably they scale as usage grows. Transparent pricing means having published rates and a clear pricing model (e.g., per call, per data point, or per request rate), which lets institutions forecast costs, compare providers, and keep spending under control as they scale.

Support

Support is the assistance a provider offers beyond standard documentation and endpoints, including committed response times, dedicated contacts, and bespoke data delivery for custom requirements. Institutional needs grow and change over time, so teams value reliable escalation paths, responsive support, and the flexibility to support requirements beyond the standard product.

Institutional Crypto Data API At a Glance

CoinGecko API leads in breadth and auditable coverage through a single API. For specialized use cases such as regulated benchmarks, tick-level execution data, and options analytics, Kaiko, CoinDesk Data, CoinAPI, and Amberdata are better suited.

Here is a quick side-by-side of how the five leading institutional crypto data API providers compare across the core factors mentioned above:

Criterion	CoinGecko API	Kaiko API	CoinDesk Data API	Amberdata API	CoinAPI
Compliance and trust	SOC 2 Type II certified Auditable 5-step Price Methodology Independently verifiable aggregated data that support MiCA, CARF, CLARITY regulatory requirements Trust Score & GT Score integrity signals	SOC 2 Type II EU BMR-compliant benchmark administrator Fair Market Value Pricing Methodology	SOC 2 Type II ISO 27001 EU BMR-compliant benchmarks	SOC 2 Type II Reference Rates Methodology	SOC 2-aligned only (no attestation report) 3-step Price Methodology (aggregation, quality filtering, VWAP calculation)
Coverage breadth	42M+ assets & trading pairs, 250+ networks, 1,700+ exchanges CEX, DEX, derivatives, and onchain markets Public company and government treasury data, RWAs, and tokenized assets	4K+ coins and 30K+ tokens, 100+ exchanges, 70+ networks CEX-focused coverage with limited onchain data, alongside derivatives and index data	7K+ assets, 300+ exchanges, 10+ networks CEX and onchain markets for BTC, ETH, and EVM chains only.	500K+ trading pairs, 1K+ exchanges, 20+ networks Derivatives and options analytics, DeFi and wallet intelligence.	18K+ coins, 400+ exchanges (CEX only) <10 DEX venue coverage with no unified cross-chain index
Granularity and historical depth	Daily market data since 2013 Hourly and 5-minute intervals since 2018 Onchain OHLCV down to 1-second intervals since 2021 Liquidity depth metrics include bid-ask spread and market depth	Second-level, hourly, and daily market data granularity Tick-level trade and L1/L2 order-book history, with spot trade data from 2010	Historical market data coverage since 2010, including tick-level trades and L2 order-book snapshots with high-precision timestamps	L1/L2 order-book data, depth, and slippage analytics across 30+ supported venues Historical coverage varies by dataset and venue, with selected exchange order-book datasets since 2011 Historical REST API data availability to ~18 months	Tick-by-tick trades and L2/L3 order book history since 2010 at 1-second granularity
Reliability and uptime	99.9% uptime SLA on Enterprise Public status page	No publicly specified SLA commitments Public status page	99.9% uptime SLA on Enterprise Public status page	No publicly specified SLA commitments, uptime percentage, or public status page	99.9% SLA on selected plans Public status page
Delivery methods and latency	REST API: real-time and historical market data WebSocket: sub-second streaming of aggregated prices, tick-level onchain trades, & 1-second OHLCV. Webhooks: event notifications	REST API: trade, order-book, and reference data WebSocket: real-time tick-level trades, and order-book updates. Flat files: daily CSV delivery	REST API: real-time and historical market data (JSON/CSV) WebSocket: low-latency tick-by-tick streaming Flat-file and cloud delivery: custom pipelines to S3, Azure Blob, or GCS for bulk history	REST API: market, derivatives, and onchain data WebSocket: low-latency streaming for spot trades, DEX data, and onchain events Cloud delivery: Parquet files via S3 and a Snowflake Marketplace integration	REST API: real-time and historical market data WebSocket: sub-second streaming of single-exchange trades, quotes, OHLCV, & L2/L3 order books FIX: low-latency market-data feed
Cost efficiency and pricing transparency	Flat Credit Model: 1 credit = 1 API call, regardless of payload size Plans starting from $35/month with commercial license included, 100K call credits, 300 RPM	No public pricing	No public pricing	Public pricing is available only for spot market data at $600/month per exchange (~$30,600/month for the full 51-exchange catalog) No public pricing is available for broader data offerings beyond spot market data.	Metered pricing, with separate billing for each product: Market Data API: 1 credit / 100 data points, available from $79/month Exchange Rates API: Per rate (from $0.50/100) Indexes API: Pay as you go Flat Files: Per request ($10/1k) + data by GB
Enterprise Support	Priority email and Slack support with 24/7 availability Dedicated Customer Success Manager Integration guidance and implementation support Custom data requirements and dataset support	24/7 support with dedicated client support	24/7 Slack support with dedicated Customer Success Manager	24/7 monitoring and onboarding assistance	Slack support with Customer Success representation and integration assistance

Best Crypto API for Institutional Data

CoinGecko API

CoinGecko API is the most trusted and widely used crypto data API, and the largest independent crypto data aggregator by asset coverage. Its proprietary aggregation methodology produces independently verifiable market data trusted by leading platforms such as MetaMask, Coinbase and Etherscan, and by regulated institutions including Kraken, Deblock, Elliptic, and Chainalysis.

Deblock relies on CoinGecko’s auditable, real-time pricing to support its MiCA-compliant onchain banking platform, while Elliptic and Chainalysis use CoinGecko pricing across extensive token coverage for institutional transaction monitoring, sanctions screening, and valuation workflows.

Pros

Broadest coverage: CoinGecko covers 42M+ crypto assets, 1,700+ exchanges, and 250+ networks across CEX, DEX, onchain, and derivatives markets. It also offers RWAs, tokenized assets, public company and government treasury data
Highly cost-efficient at scale: A flat credit pricing model charges one credit per API call regardless of response size. Batched endpoints, pagination, and multi-currency conversions therefore remain cost-efficient, with costs scaling by the number of API calls rather than the amount of data returned. Public self-serve plans start at $35 per month and include a commercial license, making costs transparent and predictable.
Unique Data Endpoints: The Pools Megafilter screens and ranks 45M+ DEX pools using 30+ filters and safety signals, including honeypot checks and GT Score. CoinGecko API also enables sector-level market data queries using over 700+ categories and delivers real-time crypto news from 100+ publishers via News endpoint, alongside AI-powered Coin Insights for curated, coin-level market context.
Enterprise Support Experience: Alongside 24/7 support and access to a dedicated account manager via Slack, CoinGecko provides ongoing customer engagement to align on new endpoints, datasets, and evolving requirements. For example, when enterprise clients require additional historical data or custom API enhancements beyond the standard offering, CoinGecko works directly with them to deliver tailored solutions, including deeper historical coverage and custom data exports.

Cons

No full L2/L3 order-book coverage: CoinGecko provides aggregated pricing and broad market analytics, including spread and market depth metrics for market monitoring and analysis.
No raw multi-year CEX tick archive: CoinGecko does not maintain raw tick-by-tick archives. Its historical coverage (daily OHLCV since 2013 and onchain OHLCV down to 1-second intervals) supports most reporting, valuation, and compliance use cases.

Best For

Institutional funds, custodians, exchanges, neobanks, fintechs, risk and compliance, and treasury teams require broad, auditable market data across CEXs and DEXs through a single API. Common use cases include building market and financial applications, portfolio and NAV valuation, fiat-to-crypto conversion rates, treasury and RWA tracking, alongside exchange and counterparty risk assessment, compliance, and regulatory reporting.

Kaiko API

Kaiko focuses on institutional exchange data, benchmark services, and compliance workflows, with deep historical market coverage including spot trade data dating back to 2010. However, the lack of publicly available pricing can make cost evaluation more difficult, as prospective users must engage with Kaiko's sales team for pricing and enquiries.

Pros

Regulated benchmark services: Kaiko Indices provides licensed benchmark and index administration under the EU Benchmark Regulation (BMR).
Market surveillance and compliance: Dedicated market surveillance and AML/CFT solutions alongside its market data offerings.

Cons

Limited long-tail asset coverage: Covers 4,000+ CEX coins and 30K+ DEX tokens only, with a narrower asset universe compared to other providers.
No public pricing transparency: Kaiko does not publish pricing, rate card, or a pricing model that buyers can evaluate independently before engaging sales. Costs are determined through custom quotes based on specific data requirements and usage needs, which can make upfront cost comparison and budgeting more difficult.
Limited public SLA detail: Kaiko does not publish uptime targets or SLA commitments. While it provides a public status page with incident history, buyers have limited visibility into reliability guarantees and support commitments before engaging with sales.

Best For

Exchanges, asset managers, and institutional teams requiring regulated benchmarks, market surveillance, liquidity analytics, and normalized CEX/DEX market data.

CoinDesk Data API

CoinDesk Data API (formerly CryptoCompare and CCData) focuses on granular exchange-level market data, including tick-level trades and order book data for quantitative trading workflows. It also provides institutional benchmark products and reference rates for teams requiring granular CEX market data and benchmark capabilities, alongside a news endpoint covering ~50 publishers.

Pros

Regulated benchmarks and reference rates: FCA-regulated and EU BMR-compliant benchmarks designed for institutional valuation and regulated financial products.
Granular trade and order-book data: The API provides tick-level trades, L2 order-book data, and over 10 years of historical market data, supporting quantitative research and market analysis.

Cons

Limited onchain and multi-chain coverage: The onchain coverage is focused on Bitcoin, Ethereum, and EVM networks only, so teams requiring broad DeFi and long-tail network coverage may need additional providers.
No self-serve evaluation or public pricing: CoinDesk Data API does not publish pricing or offer a free self-serve tier. Every paid plan requires a sales process, adding friction for teams to evaluate the API independently and forecast costs.

Best For

Asset managers and index providers require institutional reference rates, benchmarks, TradFi distribution, and digital asset market data for research.

Amberdata API

Amberdata is a digital asset data provider focused on derivatives, DeFi, and onchain analytics. Its platform combines options analytics, onchain intelligence, wallet analytics, and market data.

Pros

Dedicated options analytics: Amberdata's GVOL platform delivers options-specific analytics, including implied volatility, Greeks, and options market data, alongside DeFi, and wallet intelligence.
Cloud and warehouse delivery: Data is available through the Snowflake Marketplace and Amazon S3, suited to large-scale data-engineering and quant workflows.

Cons

Limited REST history: REST-accessible historical data is limited to ~18 months. Deeper archives require a separate bulk or cloud warehouse license, increasing the total cost of ownership for large-scale backtesting.
Uneven coverage by data type: Order-book depth varies by exchange, and some smaller venues provide only OHLCV data, so coverage is not consistent across markets.
Limited pricing transparency: Amberdata’s spot data pricing is exchange-based, starting at $600/month for each exchange. This scales to ~$30,600/month across all 51 spot exchanges, before adding options, futures, or other data products. Beyond these, pricing for other plans and data offerings is not publicly disclosed.

Best For

Quantitative trading, risk, and institutional teams requiring options analytics, order-book data, and onchain intelligence.

CoinAPI

CoinAPI is built for developers who come from traditional finance and specifically need institutional-grade CEX infrastructure. It focuses on normalized tick data, deep historical market data, order-book feeds, and execution-oriented connectivity for quantitative trading, algorithmic research, and institutional workflows.

Pros

Deep historical market data: 14+ years of backfilled trades, quotes, and L1/L2 depth data, with L3 order-by-order data limited to select venues such as Coinbase and Bitso.
FIX connectivity: Supports the FIX protocol for institutional order workflows, secured with mutual TLS authentication and regional endpoints across NCSA, EMEA, and APAC for lower latency.
Execution infrastructure beyond market data: CoinAPI’s Execution Management System (EMS) provides smart order routing capabilities, extending its offering into institutional execution workflows.

Cons

Limited onchain coverage: Limited DEX and onchain coverage, supporting only select pools and venues, which results in narrower coverage across DEX ecosystems and blockchain networks.
Fragmented pricing model with overage risk: Each CoinAPI product has its own subscription model, so costs can compound as teams add more data services. Pricing also varies by product rather than following a simple per-call structure.

For example, the Market Data REST API charges per 100 data points returned, the Exchange Rates API charges per individual rate included in the response, and the Flat Files S3 endpoint charges $250 per 1,000 OHLCV download requests. Usage beyond plan allowances is billed as overages by default, which can add unexpected costs if not accounted for.

Best For

Market makers and algorithmic trading firms requiring deep tick-level CEX history, order-book data, and FIX connectivity for execution, HFT workflows, backtesting, and market microstructure analysis.

Which Institutional Crypto Data Provider Should You Choose?

For most institutional teams, CoinGecko API is the best choice for building crypto products and data workflows that require broad market coverage, aggregated crypto intelligence, and unified access to centralized and decentralized data through a single API.

For more specialised needs such as regulated benchmark rates and indices, tick-level execution and L2/L3 order books, the table below summarizes the best fit according to each use case.

Use Cases	Recommendation	Why
Crypto & fintech application development	CoinGecko	CoinGecko provides broad crypto market coverage and auditable pricing methodology to let wallets, neobanks, exchanges, and payment apps meet strict regulatory requirements. For example, Deblock relies on CoinGecko API’s real-time pricing to meet MiCA's strict requirements for accurate valuations and reporting as Europe's first MiCA-compliant onchain bank, delivering banking-grade pricing across 100+ digital assets that powers portfolio valuations and euro-to-crypto conversions. It also provides discovery data such as coin categories, top gainers and losers, along with coin metadata such as images and descriptions, to power user-facing features like token search, trending lists, and coin detail pages.
Staking & yield-bearing asset infrastructure	CoinGecko	CoinGecko API directly powers staking and restaking platforms through aggregated reference pricing for long-tail LST/LRT tokens, coin metadata with verified contract addresses for canonical token identification, liquidity pool discovery via the Top Pools by Token Address endpoint, and historical market data for calculating performance metrics such as PnL and impermanent loss.
Crypto treasury tracking	CoinGecko	CoinGecko provides access to Crypto Treasuries data that tracks corporate and government digital asset holdings by entity, with historical holding charts and per-entity transaction history to monitor accumulation and distribution trends over time.
Exchange & counterparty risk assessment	CoinGecko	CoinGecko’s Trust Score provides a 1–10 exchange risk signal based on liquidity, regulatory status, cybersecurity, past incidents, and proof of reserves. The methodology includes a dedicated Regulation Score and peer-relative scoring, giving institutions a standardized way to evaluate centralized exchange counterparty risks.
Compliance, tax & regulatory reporting	CoinGecko	CoinGecko’s documented aggregation methodology and 12+ years of historical data support fair market value reconstruction for cost-basis and tax accounting. Pricing inputs are traceable from source venues to reported prices, providing auditability.
Reference pricing for RWAs & tokenized assets	CoinGecko	CoinGecko provides dedicated RWA and Tokenized Assets categories with live price, market cap and volume for underlying tokens.
Regulated benchmark rates, indices & ETF/fund NAV valuation	Kaiko, CoinDesk Data	Kaiko operates as an EU BMR-registered benchmark administrator, which focuses on crypto-native reference rates and derivatives settlement workflows. CoinDesk Data provides FCA-regulated and EU BMR-compliant benchmark and index products with stronger TradFi distribution and market recognition.
HFT & execution engines	CoinAPI	CoinAPI provides deep L2/L3 order-book history, FIX connectivity, and smart order routing capabilities, purpose-built for quantitative trading and institutional execution workflows.
Market surveillance, AML/CFT monitoring & manipulation detection	Kaiko	Kaiko offers dedicated surveillance and financial-crime monitoring products. CoinGecko complements these workflows with adjacent onchain risk signals such as GT Score, honeypot detection, and liquidity metrics.

Conclusion

The best institutional crypto data API depends on the product you are building and the workflows you need to support. There is no single provider that is best for every use case, as requirements vary across market coverage, data depth, infrastructure needs, and cost considerations. Specialized providers such as CoinAPI, Kaiko, CoinDesk Data, and Amberdata are suited for quantitative trading and market infrastructure workflows requiring offerings in areas such as market microstructure, derivatives, execution, and regulated benchmarks.

For most institutional crypto applications, CoinGecko API is the best fit for teams that need broad market coverage, asset intelligence, and unified access to centralized and decentralized data through a single API. It supports use cases including wallets, exchanges, fintech applications, portfolio platforms, Web3 infrastructure, RWA products, and institutional reporting workflows without requiring teams to manage multiple data providers.

Beyond coverage, CoinGecko’s flat credit-based pricing model supports cost-efficient scaling, charging 1 credit per API call rather than metering usage by data point or exchange. For example, CoinGecko API is ~180x more cost efficient than CoinAPI for equivalent workloads, as its costs do not scale with the number of data points requested. It also supports institutional requirements with SOC 2 Type II certification, documented data methodologies, and is relied on by industry-leading organizations such as Kraken, Deblock, Elliptic, and Chainalysis.

Ready to start building? Get your CoinGecko API key today and power your applications with crypto's most trusted and comprehensive market data provider.

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Bitcoin Price Predictions 2026: Analysts Forecast $38K to $250K

2026-07-23T09:44:19Z

Where Is Bitcoin Headed In 2026?

2026 Bitcoin predictions are highly divergent, ranging from bearish scenarios of $38,000 - $39,000 to bullish projections of $200,000 - $250,000, reflecting deepening uncertainty as Bitcoin trades near 21-month lows.

Citigroup, Standard Chartered, and Bernstein have all cut their 2026 Bitcoin targets since the start of the year — Citi twice, from $143,000 to $82,000. No major bank has raised its target.
NYDIG has floated a scenario where Bitcoin bottoms near $38,000–$39,000 by October if the current drawdown matches the depth of the 2014, 2018, and 2022 bear markets — though the firm stresses this is a scenario, not a forecast.
The "Lame Year" cycle-intact camp (Fidelity, Peter Brandt) is currently winning the debate against the "Institutional Era" cycle-broken camp (Grayscale, Bitwise), as Bitcoin's roughly 50% drawdown from its October 2025 peak tracks closer to historical bear-market patterns than bulls expected.
Tom Lee remains the most prominent holdout on a six-figure-plus year-end target ($200,000–$250,000), even as Standard Chartered's Geoff Kendrick and Bernstein have both cut their own targets while still calling for a recovery toward $100,000–$150,000.

What's Changed Since Our Last Update

Bitcoin started 2026 above $93,000. By the end of June, it had posted a fresh 21-month low near $58,000 — a decline of more than half from its October 2025 peak. Unlike Bitcoin's previous crashes, this one arrived without a clear villain: no exchange failed, no major stablecoin broke its peg, and the US Strategic Bitcoin Reserve stayed in place. Instead, the damage has come almost entirely from two forces — a cautious Federal Reserve and sustained outflows from spot Bitcoin ETFs.

June alone saw roughly $4 billion in ETF outflows, the worst month on record for the products. Bitcoin ended the first half of 2026 down nearly 33%, a particularly stark divergence given that tech stocks and the Nasdaq 100 both posted double-digit gains over the same period — evidence, according to several analysts, that this is a crypto-specific unwind rather than a broad risk-off move.

As of mid-July, Bitcoin trades in the $58,000–$65,000 range, with the market's attention fixed on the Federal Reserve's July 28–29 FOMC meeting as the next major catalyst.

Disclaimer: This article is for informational purposes only. Cryptocurrency markets are highly speculative. CoinGecko does not provide any financial advice.

Rounding Up The Updated Price Predictions

Why are Bitcoin predictions the most sought-after? Is it because other coins don't matter? Not at all. Historic trends show that when BTC rallies strongly, altcoins often experience larger percentage gains. However, this relationship isn't guaranteed, and can vary significantly across market cycles.

As of July 2026, the range of predictions has widened considerably compared to where things stood at the start of the year. On the bearish end, the floor has dropped out from under what used to count as a "conservative" call: NYDIG has floated a scenario where Bitcoin bottoms near $38,000–$39,000 by October, and Citigroup's own bear case now sits at $53,000 — well below the $60,000–$75,000 consolidation range that Fidelity and others framed as the cautious view just a few months ago (and which, notably, BTC has already traded through).

The table below reflects the current state of major institutional and individual forecasts, with revisions noted where a firm has changed its call since our original coverage.

Analyst/Firm	Current Prediction	Previous Prediction	Target Date	Status / Rationale
Citigroup	Base: $82,000 Bear: $53,000	Base: $143,000 Bull: $189,000 Bear: $78,500	12 months (mid-2027)	Cut twice in 2026 — $143K→$112K in March, then $112K→$82K in July. Now models zero net ETF inflows over the next year, down from a prior $10B estimate, after June's record outflows.
Standard Chartered	$100,000	$150,000	End of 2026	Cut twice — $150K (Dec 2025) → $100K (Feb 2026), held since. Kendrick calls BTC near $64K "a screaming buy" and attributes recent weakness to a "communication challenge" around Strategy's shift toward using BTC as collateral, not a broken thesis. Long-term $500K target pushed from 2026 to 2030.
Bernstein	$150,000	$200,000	End of 2026	Cut from $200K to $150K in June 2026, reiterated July 6. Notes the ~54% drawdown is milder than the 75–90% crashes of prior cycles, calling it a sign of market maturity rather than a broken bull case.
NYDIG (new)	$38,000–$39,000	—	~October 2026	New entrant. A scenario, not a base-case forecast — models a ~70% peak-to-trough decline (in line with 2022) applied to the $126,080 ATH. NYDIG flags that 2025's record-low volatility could produce a shallower landing than history suggests.
Fidelity (Jurrien Timmer)	$65,000–$75,000	—	2026 (Consolidation)	Unchanged, and increasingly validated. Maintains the four-year cycle is intact and October 2025 was the cycle top.
JPMorgan	$150,000–$170,000	—	2026	Roughly steady; sees a floor near $94,000 (now breached) and expects ETF growth to eventually revive momentum.
Grayscale	New All-Time High (>$126,000)	—	H1 2026 (missed)	Original H1 2026 timeline has passed without a new high; no public revision found. "Dawn of the Institutional Era" thesis is under pressure given the scale of the drawdown.
Bitwise	New ATH above $126,000	—	2026	No public revision found; "four-year cycle is dead" thesis increasingly contested by price action.
Galaxy Digital (Alex Thorn)	$250,000 / 2026 highly uncertain	—	End of 2027	No update found. Original framing ("too chaotic to predict") looks prescient.
Tom Lee (Fundstrat)	$200,000–$250,000	—	End of 2026	The real outlier. Holding a short/medium-horizon target firm through a 50% drawdown — unlike the banks below, this is a call that is supposed to be sensitive to 2026 price action, and it hasn't moved. Argues the sell-off wiped out excess leverage and sets up a stronger H2.
Sean Farrell (Fundstrat)	Year-end target ~$115,000	$60,000–$65,000, H1 2026	H1 2026 (hit) / year-end	His H1 call played out almost exactly — BTC hit a 21-month low near $58,000 in late June.
Peter Brandt	As low as $25,000	—	2026	No new statement found, but the "Death Cross" he flagged did materialize on the daily chart following the Q4 2025 sell-off, and the bearish technical case has broadly played out.
Bitfinex	$80,000–$100,000	—	2026	Range already breached to the downside; no public revision found.

Long-Horizon Structural Targets

These aren't 2026 price forecasts in the same sense — they're multi-year or multi-decade adoption theses that were never sensitive to a single year's drawdown, so "unchanged" doesn't mean much here one way or the other:

Analyst/Firm	Target	Target Date	Note
Michael Saylor (Strategy)	$21,000,000	2046	Strategy has kept accumulating (~845,000+ BTC) through the drawdown, alongside a new framework using BTC as collateral for preferred stock (STRC).
Cathie Wood (ARK Invest)	$1,200,000	2030	Unchanged.
Brian Armstrong (Coinbase CEO)	$1,000,000	2030	Unchanged.
JPMorgan (Nikolaos Panigirtzoglou)	~$266,000 (theoretical, volatility-adjusted)	Long-term, no set date	In a Feb. 5, 2026 note, JPMorgan argued Bitcoin's volatility relative to gold fell to a record low (a 1.5 ratio), and that matching gold's total private-sector investment on a volatility-adjusted basis implies a theoretical price near $266,000. JPMorgan explicitly calls this "unrealistic... for this year" — an upside case for once sentiment recovers, not a 2026 forecast.

Note on the NYDIG Scenario

NYDIG's $38,000–$39,000 figure comes from its Q2 2026 review, "Leverage Not Spot Demand Is Driving Bitcoin While Value and Momentum Buyers Wait." The logic: prior four-year cycle bottoms (2014, 2018, 2022) saw peak-to-trough declines of 75–85%. Applying a milder, 2022-style ~70% decline to the $126,080 ATH lands almost exactly in the $38K–$39K range, with timing pointing to October 2026 — four years after the last cycle's low. NYDIG explicitly frames this as a scenario rather than a forecast, and notes that 2025's unusually low volatility could compress the drawdown.

Not everyone reads the technicals the same way. K33's Head of Research, Vetle Lunde, published a note in mid-June ("Stabilizing Coin") observing that after Bitcoin broke below its 200-week moving average to a new cycle low, ETF outflows eased, trading volume fell to yearly lows, and BTC rebounded roughly 6% — a pattern Lunde characterized as typical of "late stage Bitcoin bear markets." That's a narrower, more technical observation than a firm price call, but it points in a less bearish direction than NYDIG's scenario.

Cuts, Not Raises: Why the Revisions Only Move One Direction

Among the forecasters whose targets are actually built to respond to this year's price action — Citigroup, Standard Chartered, Bernstein — every single revision made in 2026 has been downward. Citi cut twice ($143K→$112K→$82K), Standard Chartered cut twice ($150K→$100K), Bernstein cut once ($200K→$150K). We found no institutional bank that raised a 2026 Bitcoin target this year.

That's a fairly unremarkable fact in a falling market; nobody upgrades into a 50% drawdown. What's more interesting is the flip side: Tom Lee is the one prominent case of a short/medium-horizon forecaster holding a target steady through the entire decline, rather than either cutting it or being a long-horizon thesis that was never meant to respond to a single year in the first place. That makes him worth watching as a genuine test case — either the H2 rebound he's calling for materializes, or his target becomes the next one to move.

Key Drivers Behind Diverging 2026 Predictions

At the start of the year, the question was whether Bitcoin had transcended its historical four-year cycle or was merely following it with a lag. Six months and a 50% drawdown later, it's become a question of how closely price action actually matches the old playbook, and the answer is showing up in real revisions: banks resetting ETF-flow assumptions, price targets getting cut in real time, and a corporate treasury strategy that was supposed to be immune to the cycle now facing its own pressures.

The Four-Year Cycle Debate: The Traditionalists Are Winning (For Now)

Our earlier coverage framed this as an open question between Fidelity's "cycle intact" view and Grayscale/Bitwise's "cycle broken" view. Six months on, price action has moved decisively toward the traditionalist camp. Bitcoin's decline from the October 2025 peak has now lasted roughly 268 days and reached nearly 50–54%, edging into the range NYDIG associates with historical cycle bottoms, even if it hasn't yet matched the full 75–85% drawdowns of 2014, 2018, and 2022.

The "Institutional Era" thesis, that persistent ETF and treasury-company demand would override the old boom-bust pattern, has taken a direct hit from the data that thesis relied on most: ETF flows. Spot Bitcoin ETFs recorded their worst month on record in June, and Citigroup's decision to reset its net-inflow assumption to zero for the next 12 months (from a prior $10 billion estimate) is perhaps the clearest signal yet that Wall Street's confidence in the "ETFs override the cycle" thesis has weakened.

Strategy's Shift Adds a New Wrinkle

Strategy (formerly MicroStrategy) has begun shifting away from its long-standing "never sell Bitcoin" posture. The company is repositioning its ~845,000+ BTC holdings as collateral backing STRC, a perpetual preferred stock paying a 12% dividend, rather than relying solely on at-the-market equity raises to fund purchases. A small liquidation associated with this shift contributed to June's sell-off and briefly pushed STRC below its $100 par value.

Standard Chartered's Kendrick has characterized this as "a communication challenge, nothing more," arguing that clearer signaling around the new framework — similar to a central bank's "whatever it takes" credibility — would remove the need for further sales. Not all analysts share this reading; the shift has introduced a new source of uncertainty around the largest corporate holder's behavior that didn't exist when the original forecasts were made.

Market Maturation Signals: A Thesis Under Stress

Our original coverage cited Galaxy Digital's Alex Thorn on Bitcoin's "market maturation" — declining long-term volatility, options behavior resembling traditional macro assets, and roughly equal odds priced on extreme outcomes ($50K or $250K by year-end 2026). That thesis has had a rough six months. A 50% drawdown is, on its face, hard to square with a "dampening swings" narrative.

That said, there's a version of the thesis that's held up: Bernstein points out the ~54% decline is still milder than the 75–90% peak-to-trough crashes of 2014, 2018, and 2022, which could be read as partial vindication — large moves still happen, just less extreme than history. What has clearly broken down is the "equal odds" pricing: prediction markets have shifted to a meaningfully bearish skew (68% odds on $65,000 by late July, under 20% on $90,000 by year-end), a far cry from the coin-flip uncertainty Thorn described in December.

Historical Cycle Pattern: Where This Cycle Actually Sits

Bitcoin's four-year halving cycle has historically produced peaks 12–18 months post-halving, followed by drawdowns in the 76–85% range lasting 12–18 months. The October 2025 peak arrived squarely within that historical window, which is what made the "cycle intact" case plausible in the first place. The subsequent decline — now roughly 268 days old and 50–54% deep — is on pace with historical timing but has so far been shallower than historical depth. That gap is exactly what NYDIG's scenario addresses: extrapolating a full 2022-style ~70% decline from the ATH would bring Bitcoin down to the $38,000–$39,000 zone, much closer to (though still short of) the historical norm. Separately, the Death Cross that Peter Brandt flagged as a risk in our original coverage has since been confirmed on the daily chart — a technical signal that, in prior cycles, has often preceded further downside rather than marking a bottom.

Evolving Macroeconomic Conditions

The regulatory tailwinds our original coverage cited — the GENIUS Act's stablecoin framework, the 401(k) executive order, the SEC's Project Crypto — are all still in place, but none delivered a fresh catalyst in H1 2026; if anything, the Digital Asset Market Clarity Act that Citigroup's original $143K case leaned on has stalled, with Polymarket odds on year-end passage sitting around a coin flip.

Monetary policy, meanwhile, has moved in a more hawkish direction than the original piece anticipated. The Fed held rates at 3.50%–3.75% through an unusually divided April meeting (an 8–4 vote, the most split FOMC since October 1992), then held again at the June 16–17 meeting — notable as the first meeting run by new Fed Chair Kevin Warsh, who succeeded Jerome Powell on May 15. The June Summary of Economic Projections told its own story: the median dot moved from pricing in one rate cut for 2026 (as of March) to pricing in zero cuts, alongside an upward revision to core PCE inflation (to 3.3%). Cleveland Fed President Beth Hammack — now a voting FOMC member in 2026, as flagged in our original coverage — has continued to argue for holding rates steady, reinforcing the tighter-for-longer backdrop Bitcoin has had to contend with all year.

The Fed Meeting Is Now the Key Near-Term Catalyst

With ETF flows and ATH-era catalysts (the Clarity Act, 401(k) access, Project Crypto) already priced in and delivering less upside than bulls expected, the market's attention has shifted almost entirely to monetary policy. The Federal Reserve's July 28–29 meeting is widely viewed as the pivotal near-term event: a hawkish surprise would likely pressure Bitcoin further toward the $50,000–$55,000 zone several banks now cite as downside risk, while a softer tone could support a relief rally back toward the low-to-mid $60,000s.

Quantitative Models and Frameworks

Every experienced Bitcoin trader and analyst has preferred models for understanding Bitcoin's price trajectory. While not definitive, these frameworks help anchor expectations and make sense of volatile price action. The most referenced approaches are Stock-to-Flow (S2F), cycle-based predictions, and technical indicators.

Stock-to-Flow (S2F): Scarcity as a Signal

The S2F model, popularized by PlanB, measures how scarce an asset is by dividing its total supply (stock) by annual new supply (flow). It's done reasonably well in prior bull cycles (2013, 2017, 2021), but has struggled since the 2021 peak, and this cycle hasn't helped its case: Bitcoin's current price sits well below what S2F's band would suggest, adding another data point to the model's post-2021 track record of over-predicting price relative to actual outcomes.

Cycle-Based Predictions: History Repeating

The four-year halving cycle has historically shown diminishing returns each cycle — roughly 50x in 2013, 20x in 2017, 7x in 2021. This cycle's October 2025 peak of $126,080 represented only about a 1.8x gain from the prior cycle's ~$69,000 high, continuing that diminishing-returns pattern and lending some support to the idea that this cycle topped on schedule rather than being disrupted by institutional demand.

Technical Indicators: Short and Mid-Term Navigation

Technical indicators provide insight into momentum and trend strength:

Relative Strength Index (RSI): The 2017 and 2021 peaks both coincided with weekly RSI readings above 90 — a level this cycle's October 2025 peak never reached, another point the "cycle intact but muted" camp has cited. More significantly, Bitcoin's June low broke below its 200-week moving average for the first time this cycle — a level Bitcoin has historically not closed below for extended periods, and one that K33's Vetle Lunde flagged directly in his June note
Support/resistance structure: Bitcoin near $60,000 sits below its 50-month exponential moving average around $65,600 — a level that has flipped from support to resistance — while remaining above its 100-month average near $40,000, which keeps the broader multi-year uptrend structurally intact even amid the current weakness.
Prediction markets: Traders have assigned roughly a 68% probability of Bitcoin reaching $65,000 by late July, a 64% chance of $60,000 holding as support, and under 20% odds of reaching $90,000 by year-end.
Death Cross confirmed: The bearish 50-day/200-day moving average crossover that Peter Brandt flagged as a risk in our original coverage has materialized on the daily chart.

How to Evaluate Bitcoin Price Predictions

With forecasts ranging from $25,000 to $250,000 for 2026, how can investors make sense of the noise? Here are four helpful approaches:

Understanding Analyst Track Records

A forecast from an independent trader on X shouldn't carry the same weight as one from a macro strategist at a global bank — but banks aren't always right either, and this year has been a real test of who adapts versus who digs in. Standard Chartered's Geoff Kendrick remains a useful case study of the first type: he initially called $120,000 for mid-2025, publicly acknowledged underestimating the rally once Bitcoin blew past it, revised up to $200,000 — and has since cut twice as the market reversed, landing at $100,000 while still calling current prices "a screaming buy." Whether you read that as admirable intellectual honesty or as a target that's moved three times in eight months depends on your priors, but it's a clearer track record than most.

The gap between public commentary and internal positioning has become one of this cycle's more interesting stories in its own right. Fundstrat's Tom Lee has maintained a public $200,000–$250,000 target throughout the crash, while the firm's own Head of Digital Asset Strategy, Sean Farrell, had already called for the $60,000–$65,000 range that materialized in June, and has held his $115,000 year-end target since. Fundstrat has characterized this as reflecting different mandates and time horizons rather than internal disagreement, but it's a useful reminder for readers: a firm's most bullish public spokesperson and its risk-management desk can hold very different views simultaneously, and it's worth knowing which one a given headline number is coming from.

More broadly, the analysts who have adjusted their targets in response to changing ETF flow data (Citigroup, Standard Chartered, Bernstein) have generally moved in the same direction — down — while those anchored to longer-term structural theses (Saylor, Wood, Armstrong, JPMorgan) have left their targets unchanged, since those calls were never particularly sensitive to a single year's price action in the first place.

Distinguishing Analysis Types

Quantitative Models: Frameworks using mathematical inputs like Stock-to-Flow, cycle analysis, or on-chain metrics. These provide probabilistic ranges, not certainties.
Fundamental Analysis: Examination of adoption trends, regulatory developments, and macroeconomic factors, which are useful for understanding long-term value drivers.
Technical Analysis: Chart-based analysis using patterns, indicators, and market behavior, mainly used for timing and trend identification.
Speculation: Predictions without disclosed methodology, based on gut feeling or attention-seeking.

Managing Risk Around Uncertainty: DCA vs. Market Timing

Even the best models can break due to regulatory shocks, macro liquidity squeezes, or black swan events. Seasoned investors focus on how they position themselves around different scenarios:

Limit allocation size so one bad call doesn't ruin your portfolio
Hold dry powder for unexpected volatility or opportunities
Use protective stops or hedges if trading actively.

There are two popular approaches when investing in Bitcoin:

Dollar-Cost Averaging (DCA): Buying small amounts regularly, regardless of price. This reduces emotional stress of timing and has historically worked well for long-term holders.
Market Timing: Market timing based on cycle or technical signals can outperform if done right, but this year is a good illustration of the risk: several professional forecasters who called for a rough patch still didn't anticipate the depth or speed of the June decline.

Unless you're tracking on-chain flows and Fed odds daily, DCA remains the more defensible default for most investors.

Risk Factors Going Into H2 2026

The Fed decision (July 28–29): Now the single most-watched near-term catalyst. A hawkish hold, or signal of "higher for longer," is the most cited risk across current forecasts.
ETF outflow persistence: June's record $4B outflow month raises the question of whether outflows stabilize or continue. Citigroup's zero-inflow assumption for the next 12 months represents a meaningfully more conservative baseline than banks were using at the start of the year.
Strategy's STRC framework: The shift from pure accumulation to using BTC as loan collateral introduces a new, less-tested source of potential selling pressure tied to preferred-stock dynamics rather than simple treasury strategy.
The NYDIG scenario: Not a base case, but worth monitoring — a further ~35–40% decline from current levels would bring BTC into the $38,000–$39,000 zone by October, matching the depth and timing of the 2018 and 2022 cycle bottoms.
Regulatory stagnation: Delays to the Digital Asset Market Clarity Act remain a live risk; Polymarket odds on passage by year-end have hovered around 50%.
Divergent institutional views: With Citi, Standard Chartered, and Bernstein all having cut targets in 2026, and Tom Lee the main holdout on a firm near-term bullish number, the center of gravity among mainstream forecasters has shifted meaningfully bearish since the start of the year. JPMorgan's $266,000 figure is a long-term theoretical case, not a competing 2026 target, so it sits outside that comparison.

Additional Risks and Considerations

Beyond the risk factors outlined above, several additional considerations remain:

Market volatility: A $143,000 target once looked compelling on its own terms, but the intervening six months are the better illustration of the point: Bitcoin didn't just risk a 30% pullback on the way to a bull target, it fell more than 50% from its October 2025 peak of $126,000 to a 21-month low near $58,000. Whatever target an analyst is calling for, the path there is unlikely to be a straight line.
Regulatory uncertainty: Policy shifts can still accelerate adoption or freeze momentum overnight. The Clarity Act's stalled progress this year is a live example — a catalyst that looked close to certain in December 2025 and still hasn't landed by July.
Black swan events: Bitcoin's history includes shocks no model accounted for in advance — Mt. Gox (2014), China's mining ban (2021), FTX (2022). Notably, 2026's drawdown hasn't had one of these: no exchange has failed and no stablecoin has broken its peg, which is part of why several analysts describe this as a "clean" macro-driven decline rather than a crisis-driven one — arguably a different, and more concerning, kind of bearish signal, since it suggests demand simply isn't there rather than being disrupted by a one-off event.
Historical correction patterns: Steep corrections remain the expectation after cycle peaks, not the exception. Prior bear markets saw 76–85% drawdowns lasting 12–18 months; this cycle's ~50–54% decline over roughly 268 days is on pace with historical timing but has so far been shallower than historical depth — which is precisely the gap NYDIG's $38,000–$39,000 scenario is testing.
2026 as consolidation or crypto winter: The "Lame Year" thesis this section originally flagged as a risk has, six months later, largely become the base case rather than a tail scenario. The open question is no longer whether 2026 disappoints, but how much further the decline runs and how long a recovery takes.

Conclusion

Six months ago, the debate was whether 2026 would be a "Lame Year" consolidation or the start of a new institutionally-driven bull leg. That debate has been substantially resolved by price action: Bitcoin's ~50% drawdown from its October 2025 peak, a record month of ETF outflows, and a confirmed Death Cross have vindicated the cycle-intact camp far faster and more sharply than most forecasters expected in December 2025.

The new question is how much further this goes. On one end, NYDIG's scenario analysis places a potential bottom near $38,000–$39,000 by October if history repeats exactly; on the other, Standard Chartered and Bernstein — while both cutting their targets — still see a path back to $100,000–$150,000 by year-end, and K33's read of the recent stabilization in ETF flows and volume points toward a less severe outcome than NYDIG's scenario, even without naming its own number. Tom Lee remains the most prominent holdout for a return to six figures and beyond.

As always, the spread between the most bearish and most bullish calls remains enormous, and the Fed's late-July decision is likely to be the next major catalyst that narrows it.

Disclaimer: This article is only for informational purposes and should not be taken as financial or investment advice. Always do your own research, and note that cryptocurrency prices (including Bitcoin) are extremely volatile.

An earlier version of this article was written by Sankrit K.

Expert forecasts are one way to predict prices. For a market-driven perspective, see CoinGecko's Bitcoin Price Prediction, powered by real-money prediction markets on Polymarket.

Safe: The Multisig Wallet Standard for Self-Custody

2026-07-23T00:00:00Z

What Is Safe?

Safe (formerly Gnosis Safe) is a smart contract wallet that requires a minimum number of designated signers to approve a transaction before it executes (an "M-of-N" setup).

Safe has become one of the most widely used pieces of infrastructure in crypto, with well over a trillion dollars in transaction volume processed and tens of millions of Safe accounts deployed across chains.
Because Safe accounts are onchain smart contracts rather than single private keys, they remove the single point of failure that comes with standard wallets, while giving owners full self-custody.

The Problem With Single-Key Wallets

Most people's first crypto wallet is a single-key wallet, also called an externally owned account, or EOA. MetaMask, Trust Wallet, and Exodus are common examples. These wallets are secured by one seed phrase, which doubles as the private key. If that phrase is lost, stolen, or mishandled, whoever holds it controls the funds outright — there's no second check and no way to intervene.

That's a manageable risk for personal spending money. It's a much bigger problem the moment more than one person has a stake in the funds. A single employee, co-founder, or teammate with sole access to a treasury key can drain it by accident or on purpose, and there's no way to stop them after the fact. Even a solo founder managing their own funds through one key is still exposed to that same single point of failure — lose the phrase, lose everything.

This is the gap Safe is built to close.

What Is Safe (Formerly Gnosis Safe)?

Safe is a smart contract wallet — often called a "smart account" — that runs on Ethereum and a wide range of other EVM-compatible networks. Instead of one private key controlling the funds, a Safe account is configured with a group of signer addresses and a threshold, such as 2-of-3 or 5-of-9, that must approve a transaction before it can be executed.

If a business has three core stakeholders, for example, the Safe can be set up so any two of them must sign off before funds move. No single person, however senior, can act alone. This same structure works whether the account belongs to a DAO treasury with dozens of signers, a startup with two co-founders, or an individual who wants redundancy across their own devices.

Because the wallet's logic lives in an audited, open-source smart contract rather than in a centralized custodian, users keep full self-custody throughout. There's no company holding the keys and no product team that can freeze the account — only the signers the account owner has chosen.

Gnosis originally built the project as the Gnosis Multisig, then rebuilt it as Gnosis Safe. In 2022 it spun out from Gnosis and rebranded as Safe, which is the name it operates under today, alongside the product name Safe{Wallet}.

How Safe Works

Ethereum accounts fall into two categories: externally owned accounts (EOAs), which are controlled by a single private key, and contract accounts, which are governed by code rather than a key. Safe is built as a contract account, meaning the rules for approving and executing a transaction are enforced onchain rather than by a single piece of hardware or software that could be lost or compromised.

A signer can approve a pending Safe transaction from a connected EOA wallet (like MetaMask or a hardware wallet), from the Safe web app, or from the Safe mobile app. Once enough signers have approved a transaction to meet the account's threshold, anyone can trigger its execution on the network.

This structure gives Safe users three practical advantages:

Safer fund management — a transaction only goes through once the required number of signers agree, so no single person can move funds unilaterally.
Accountability for sensitive transactions — meaningful transfers, contract upgrades, or treasury decisions require sign-off from multiple trusted parties.
Redundancy — if one signer loses access to their key, the remaining signers can still operate the account and can replace the missing signer entirely.

Key Features

Multisignature control: Owners define exactly how many approvals are required before any transaction — including changes to the Safe's own configuration — can execute, which prevents any minority of signers from acting alone.

Transaction scanning and simulation: Safe can simulate a transaction and surface risk signals before it's signed, so signers can see what a transaction will actually do rather than approving blind.

Spending limits and roles: Safe supports daily spending limits and role-based permissions, so day-to-day operational spending doesn't require a full multisig approval every time, while larger transactions still do.

Multichain treasury management: Teams can deploy and track Safe accounts across many networks and manage them from a single interface.

Transaction Builder: Multiple actions can be bundled into a single transaction and a single signing step, which cuts down on repeated approvals and gas costs.

Safe Shield: Built with security partner Hypernative, Safe Shield adds automated transaction guards, custom security policies, and a monitoring dashboard, giving organizations enterprise-grade controls for blocking malicious or policy-violating transactions before they execute.

Which Networks Does Safe Support?

Safe is deployed on Ethereum mainnet and a broad and growing set of EVM-compatible networks, with new networks added regularly. The current, up-to-date list of supported chains is maintained on the Safe Help Center.

How to Create a Safe

Setting up a Safe account takes only a couple of minutes, according to Safe's own documentation:

1. Open the web app. Go to app.safe.global.

2. Connect a signer wallet. Safe supports a wide range of signer wallets. If you're deploying on a network that isn't fully gasless, make sure your wallet holds enough of that network's native token to cover deployment fees.

3. Name your Safe and choose signers. Give the account a name (stored only locally, never shared), then add signer addresses or ENS names. The wallet you connected is suggested as the first signer by default, and you can add or remove others.

4. Set the confirmation threshold. Decide how many of your signers must approve a transaction — or a change to the Safe's own settings — before it goes through. It's worth double-checking that you (or your organization) can realistically reach that threshold; if you can't, you risk locking yourself out of your own funds.

5. Review and deploy. You can either deploy immediately by paying gas ("Pay now"), or use a gasless setup that only requires payment when the first real transaction is sent ("Pay later"). Deployment itself typically takes well under a minute.

Note that a true multisignature Safe (more than one required signer) currently has to be deployed with an onchain transaction; only single-signer Safes can be created fully gaslessly.

Security and Trust

Safe's smart contracts are open source and have gone through multiple rounds of audits from firms including OpenZeppelin, Certora, Runtime Verification, and Ackee Blockchain, and the contracts are widely considered among the most battle-tested account infrastructure on Ethereum. Safe also emphasizes that it holds no admin backdoor over user funds — recovery options, like nominating a trusted guardian, are opt-in and controlled entirely by the account owner.

At the scale Safe now operates, security is treated as core infrastructure rather than an add-on: Safe Shield exists specifically because the platform now secures tens of billions of dollars in assets on behalf of DAOs, foundations, protocols, and individual power users, and a single compromised transaction at that scale can be catastrophic.

SAFE Token and Governance

Following its 2022 spin-out from Gnosis, Safe transitioned governance to a community-run body, SafeDAO, with control formalized in 2023. The SAFE token is used for governance decisions over the protocol's direction. For current tokenomics detail, allocation, and governance mechanics, Safe's own governance page and blog are the most reliable sources, since token distribution schedules and DAO structure have evolved since the token's original launch.

Conclusion

Secure, flexible custody is foundational to crypto actually working at scale — for individuals and even more so for organizations managing shared funds. Safe has spent years building toward that goal, evolving from an early Gnosis side project into what is now widely described as core infrastructure for onchain treasuries, DAOs, and protocols, with major players across the ecosystem — from the Ethereum Foundation to large DeFi protocols — relying on it to manage funds without handing custody to a third party.

The Age of Control: Crypto Venture Capital in H1 2026

2026-07-21T02:18:54Z

Capital in the crypto market is undergoing a paradigm shift, concentrating into specific sectors and companies. Tiger Research and RootData examined this shift in capital markets using data on 9,416 investment deals recorded from 2018 through the first half of 2026.

Key Takeaways

Capital inflows in the first half of 2026 reached $13.3 billion, already comparable to the $13.2 billion recorded for all of 2024, even as the number of funding rounds fell to just 435, a 78% decline from the 2022 peak of 1,978.
The market is now split between a small number of large, crypto-native venture capital firms that concentrate on lead investments and exchange-affiliated venture arms that compete on liquidity, while mid-sized firms without a clear competitive edge are being pushed out of the market at a rapid pace.
The number of funding rounds in the gaming sector fell 96%, from 141 in 2024 to just 5 in the first half of 2026.
Capital inflows into the payments and stablecoin sector and the centralized exchange (CEX) sector were driven entirely by mergers and acquisitions.
Traditional financial institutions took part in 54.5% of all investment deals recorded in the first half of 2026.

1. The 2021 Market: Speed and Diversification as Strategy

The core strategy in the 2021 crypto investment market was speed and portfolio diversification. Investors executed 1,750 deals that year, including seed rounds, and competition over speed was intense enough that AU21 Capital alone closed more than 13 deals a month on average.

Investment decisions at the time were reduced to simple criteria such as the token generation event (TGE) schedule and tokenomics, the structure governing how a project’s tokens are issued and distributed. Because token issuance alone could generate returns without any real product development, venture investors largely pursued a “spray and pray” strategy, spreading capital across dozens or even hundreds of projects regardless of valuation.

Speed of execution took priority over thorough due diligence. New rounds closed almost instantly, and VCs that missed a round often chased the next one at a higher valuation, a pattern of FOMO that repeated across the industry.

Many VCs that ran this strategy did not survive the bear market that followed, while the ones that did survive fundamentally changed their approach.

2. Which VCs Survived: A Changed Landscape

2.1. Lead Investment, Then and Now

The first metric to examine is lead investment, the rounds that major VCs have historically directed.

Some VCs remain active in leading deals today, while others have disappeared entirely or emerged only recently. Because leading a round has always required the reputation and scale of capital that only large VCs possess, the firms that led major rounds in the past have proven resilient, and most still rank among the top ten today.

2.2. How Surviving VCs Diverged

Looking at data from 2024 through 2026 as the most recent period, crypto-native VCs and established large firms are concentrating their resources on lead investments, engaging more deeply in individual deals. They have shifted their business model toward doing fewer deals overall while raising the bar on due diligence and securing board seats and greater influence over governance.

A different pattern emerges, however, in the cumulative count of round participation outside of lead investments.

Among the top 15 VCs by round participation from 2024 through the first half of 2026, exchange-affiliated firms account for a large share. Exchanges have been more active in joining rounds than in leading them. Coinbase Ventures ranked first with 140 deals, OKX Ventures second with 94, and YZi Labs third with 92. YZi Labs is the organization that resulted when Binance Labs rebranded in January 2025.

HashKey Capital, ranked seventh, is the venture arm of the Hong Kong exchange HashKey Exchange, and Mirana Ventures, ranked fourteenth, is the venture arm of Bybit. Five major exchanges appear in the top 15 through their respective venture arms alone. Large VCs that focus on leading rounds, such as Polychain and Pantera Capital, rank lower by this measure of overall round participation.

CEX-affiliated VCs have established themselves as core participants in major rounds by leading with the liquidity and marketing support their platforms can provide. Mid-sized VCs that lack a clear, defensible advantage, whether economies of scale, brand recognition, or exchange-level liquidity support, are being squeezed out of the market quickly as capital pressure and failed exits reinforce each other.

2.3. The VCs That Left: The End of Spray and Pray

Most VCs that built broad portfolios during the last bull market by relying on quick token liquidation have since disappeared. AU21 Capital, LD Capital, and Shima Capital saw their deal counts fall by as much as 98.9% and effectively lost their influence in the market. A strategy built on riding short-term narratives no longer worked once a prolonged bear market and tighter regulation set in.

Their failure to develop any real differentiation was the main cause, but it is also worth noting that the broader flow of crypto capital has shifted toward projects that have already reached some degree of maturity, and few new projects requiring early-stage funding are emerging. In other words, the kind of opportunity these VCs depended on has stopped appearing in the market.

3. Investment Rounds: Buying the Fruit, Not the Seed

3.1. The Seed Collapse

Seed-stage deals totaled 81 in the first half of 2026, down 88% from 694 in 2022. The market’s aversion to early-stage projects with unproven business models and higher risk is clearly evident. This decline also shows up in the overall structure of funding rounds: seed rounds accounted for 35.3% of all deals in 2022, a share that fell to 18.7% by the first half of 2026.

The decline in seed rounds can be read as reflecting both investor aversion and a simple shortage of new early-stage projects seeking seed funding. It is a metric that captures market contraction and market maturity at the same time.

3.2. Capital Concentrating in Later Stages

Measured by capital allocation, later-stage rounds, Series A and beyond, now account for 75.2% of total investment in funding rounds. Seed-stage investment briefly held a majority share during the 2023 bear market, but capital quickly reallocated toward well-capitalized companies once the market entered recovery.

In the first half of 2026, total Series A funding ($745 million) exceeded all seed-stage capital raised ($423 million), making it the largest category of any round.

Average deal size rises in a clear step pattern from one stage to the next: $5.4 million at seed, $22.4 million at Series A, $127 million at Series C, and $202 million at Series E. The sample size shrinks at later stages, but .companies that reach those stages have already seen their revenue and valuation increase, so each round involves a correspondingly larger amount of capital.

4. The Market Overall: Capital Concentrates as Deal Count Falls

4.1. Capital and Deal Count Diverge

Total capital inflows reached $13.3 billion in the first half of 2026, while the total deal count of 435 amounted to only 22% of the 1,978 deals recorded in 2022, the year with the highest annual deal count. From 2024 to 2026, capital volume held steady or rose even as it concentrated into a much smaller number of deals.

Small, diversified bets from VCs chasing short-term returns around token liquidity events have declined, while large direct investments from traditional financial institutions have increased. Institutions apply stricter criteria, evaluating not token listing schedules or market narratives but whether a company has an auditable revenue structure and the necessary regulatory licenses.

Deals of $100 million or more totaled 32 in the first half of 2026, accounting for 7.4% of all deals, up sharply from 1.1% in 2024. Over the same period, the average deal size roughly quadrupled, from $11.7 million in 2024 to $47.4 million in the first half of 2026.

This rise in share came from two directions at once. The number of large deals itself increased, while the total deal count fell as small deals, including seed rounds, disappeared. A small group of surviving projects began to dominate the market, and as small deals vanished, the already limited pool of large deals also came to represent a larger relative share.

4.2. Direct Participation in Venture Rounds

The share of investment deals involving traditional financial institutions rose from 29.2% in 2018 and first crossed the majority mark, reaching 53.9%, in 2021. Their participation dipped to 45.2% in 2023 during the last downturn, rebounded to 54.4% in 2024 as regulation became more defined, fell back to 50.9% in 2025, and reached 54.5% in the first half of 2026. Participation has remained near its highs ever since first crossing the majority mark in 2021.

In one example, a16z led the $355 million round for Digital Asset, the developer of Canton Network, but core institutional players, including BNP Paribas, HSBC, S&P Global, and Hanwha Investment & Securities, invested directly rather than through a venture subsidiary.

Where investment once entered mostly at the earliest stage, the growth of crypto VC firms and the entry of traditional investors have shifted more capital toward companies that have already reached some degree of maturity.

5. Sectors: Surviving a Changed Environment

2024 was the year spot bitcoin ETF approval coincided with a more favorable regulatory environment, producing the first clear sector-level capital flows since the bear market, and this analysis uses it as the baseline year for sector comparisons.

In 2024, the year bitcoin ETFs were approved, the infrastructure sector held a majority share of total investment capital at 50.9%. That share had fallen sharply to 14.8% by the first half of 2026. Payments and stablecoins (25.3%), centralized exchanges (18.2%), and prediction markets (17.5%) took the lead instead, reshaping the sector landscape entirely.

This shift suggests that blockchain infrastructure has changed character, from a standalone investment target to a practical platform that institutional businesses put to use. Representative examples include Robinhood running its own layer built on Arbitrum, and Securitize adopting Solana and Avalanche as settlement layers around the same time it listed on the New York Stock Exchange. In other words, the current capital market’s core demand has moved past building new protocol infrastructure from scratch, toward actually operating real-world financial services on top of existing infrastructure layers.

5.1. The Laggards: Gaming, NFTs, and Social

All three sectors saw deal counts fall sharply. Gaming dropped from 141 deals to 5, NFTs from 27 to 2, and social and entertainment from 74 to 11.

Capital inflows followed the same downward path in all three. Gaming capital fell from $758.6 million to $44.8 million, NFT capital from $114.9 million to $14.7 million, and social and entertainment capital from $512.1 million to $70.1 million.

Gaming showed the steepest decline of the three. The earlier GameFi model, which combined gaming with token-based rewards, tended to lean too heavily on token issuance for financial returns rather than building sustainable gameplay. As soon as new user growth slowed, this model fell into what is known as a death spiral, a structural cycle in which falling token value and user attrition reinforce each other, and it never found a way out. As a result, user traffic data, once a key metric in due diligence, lost its reliability, and capital inflows into the sector were effectively cut off.

5.2. DeFi: Quiet but Steady

Deal count in the decentralized finance (DeFi) sector fell 71%, but total investment declined by only about 34%. Average deal size actually rose, from $4.5 million in 2024 to $10.4 million in the first half of 2026, showing that as overall deal count contracted, capital concentrated in a small number of large deals.

The main driver of this concentration was a token sale round by the lending protocol Morpho, aimed at institutions and investment firms. Morpho, which used its modular lending protocol to open the DeFi vault market to institutions and redefine DeFi risk standards, raised $175 million in a token round led by a16z crypto, Paradigm, and Ribbit Capital on June 9, 2026. That single round accounted for 17.7% of all DeFi investment in the first half of 2026, a clear reflection of how concentrated the market has become.

The DeFi sector, in other words, has moved away from broad-based ecosystem growth, with capital instead shifting toward a small number of protocols that the market has already validated.

5.3. Payments and Stablecoins: The Fastest-Rising Sector

Deal count in the payments and stablecoin sector has kept accelerating on a monthly average basis. Total investment over the same period jumped roughly twentyfold, from $143.9 million to $2.85 billion in the first half of 2026. Much of this increase, however, is attributable to a handful of large M&A transactions.

The largest deal in the first half of 2026 was Mastercard’s acquisition of BVNK for $1.8 billion in March, followed by Payward’s (Kraken’s parent company) acquisition of Reap for $600 million in May. These two transactions alone accounted for about 84% of total sector investment in the first half of 2026. Cross-border payment and crypto card issuers, including Rain ($250 million) and KAST ($80 million), also raised capital steadily, supporting the sector’s growth.

These recent large-scale M&A deals indicate that traditional payment companies and major Web3 institutions have moved beyond simple business partnerships and are now acquiring and directly controlling stablecoin infrastructure. Stripe offers the clearest example of this race to set the ecosystem standard, beginning with its acquisition of Bridge in October 2024.

After acquiring Bridge, Stripe partnered with Paradigm to build Tempo, a blockchain dedicated to stablecoin payments, and successfully launched its mainnet in March 2026. That June, Bridge co-founder Zach Abrams became interim head of the entity operating Open USD (OUSD), a global consortium stablecoin project with more than 140 participating companies.

The OUSD project has adopted Bridge, which Stripe acquired and continues to develop, and Tempo, which Stripe is building, as its core initial infrastructure. The technology and talent Stripe gained through acquisition now control both pillars at once: its own proprietary platform and the industry consortium meant to set the standard. This shows that competition over stablecoin infrastructure has moved fully past company-level acquisitions and into a contest over setting the global standard for the entire market.

5.4. CEX: Venture Capital No Longer Needed

The centralized exchange (CEX) sector’s share of total investment jumped from 3.0% in 2024 to 18.2% in the first half of 2026. This increase, however, is difficult to read as an expansion of traditional venture investment into new exchanges, since M&A alone accounted for 75.5% of all CEX sector investment recorded from 2024 through the first half of 2026. That share climbed from 58.8% in 2024 to 78.9% in 2025, reflecting an overwhelming degree of concentration.

Overall capital inflows declined from the prior year’s peak of $19.4 billion, when large M&A deals were concentrated, but remained more than six times the 2024 level of $340 million. Deal count has not slowed either, holding a steady pace on a half-year basis. The 23 deals recorded in the first half of 2026 averaged 3.8 per month, faster than the pace of 2.8 per month in 2024 and 3.0 per month in 2025.

What the CEX investment market is showing, in other words, is a reshuffling centered on a small number of large operators. Naver’s acquisition of a stake in Dunamu remains under regulatory review but was the largest deal announced during the period, followed by Coinbase’s acquisition of Deribit for $2.9 billion and Kraken’s acquisition of NinjaTrader for $1.5 billion.

Abu Dhabi’s sovereign wealth fund MGX’s $2 billion strategic investment in Binance fits the same pattern. At the same time, venture arms of existing large exchanges, such as OKX Ventures and HashKey Capital, are participating more actively in investment rounds and acquisitions of their own. As a result, CEX players are increasingly taking on a dual role, acting as both investment targets and strategic investors.

5.5. Prediction Markets: A New Sector Emerges

Prediction markets have emerged as a sector that provides liquidity for real-world macro indicators such as economic data, elections, and policy decisions. The trigger for the sector’s growth was formal regulatory approval from the Commodity Futures Trading Commission (CFTC) in May 2025, which opened the door for large-scale capital inflows from hedge funds and asset managers as the sector entered the regulated mainstream.

Kalshi surpassed $100 billion in cumulative trading volume in June 2026. It had already raised $1 billion in a round led by Paradigm in December 2025, followed by another $1 billion led by Coatue.

Polymarket raised capital from Intercontinental Exchange (ICE), the operator of major traditional exchanges. In October 2025, ICE committed up to $2 billion, of which it actually deployed $1 billion, and it added another $600 million in March 2026, bringing its cumulative investment to about $1.6 billion.

Rather than a field of many competing new projects, the prediction market sector is settling into a structure in which traditional financial institutions and top-tier institutional capital repeatedly funnel large rounds into the two players that secured regulatory approval first.

5.6. Custody: Quiet but Powerful

The custody sector grew fifteenfold, from $20.4 million in 2024 to $317.1 million in the first half of 2026. In the first half of 2026, Anchorage raised a $100 million strategic investment, meaning Anchorage alone accounted for roughly a third of all sector investment during that period.

For institutional asset managers to hold crypto directly, custody infrastructure that meets regulatory requirements is essential. This sector grew alongside rising institutional demand for asset management and crypto custody services.

The sectors discussed above share one common thread: each has kept a stable base of capital flow through the funding rounds described here, and in every case, that infrastructure demand was created by institutions’ need to enter the market.

6. A New Standard for Crypto Capital: From Betting to Control

Overall, the center of gravity in crypto investment has shifted from planting short-term seeds to owning a stake in infrastructure and protocols.

Before bitcoin ETF approval and the improved regulatory environment of 2024, the crypto market was a realm of indiscriminate betting, dominated by small, narrative-driven investments spread across many projects. That strategy ultimately led to the collapse of the gaming and NFT sectors and the elimination of the VCs that kept pursuing it.

Today’s capital, by contrast, aims not at short-term bets but at gaining long-term control over both its investment targets and on-chain infrastructure. It concentrates large sums in a small number of targets that have secured auditable revenue structures and regulatory licenses, or it acquires equity outright to control the infrastructure itself.

In the past, an investment in an early-stage project functioned as a signal a VC sent to the market. The act of investing was read as smart money moving in, which lifted token prices or drew retail users to participate early. Today’s structural capital, which acquires infrastructure directly and secures licenses, sends no such signal for retail to follow.

Retail investors no longer react strongly to news of VC investment, fundamentally because market capital itself has undergone this structural change. Retail investors, too, now need to weigh potential investments with the same caution VCs now apply. The old betting strategy no longer serves either retail investors or VCs.

About RootData

RootData is a Web3 asset data platform launched in early 2022 that provides a systematic investment and funding database for crypto investors and founders. It now processes more than 3.4 million search queries a month and is used by more than 2 million crypto users. RootData’s data and research have been cited by major media outlets and institutions, including The Wall Street Journal, Cointelegraph, Binance Research, and The Block. The platform structures the information investors need for decision-making, from discovering crypto projects to tracking funding and profiling investors.

Dive deep into Asia’s Web3 market with Tiger Research.
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CoinGecko API vs CoinAPI: Which Crypto Data API Is Better?

2026-07-20T05:58:29Z

Is CoinGecko or CoinAPI Better?

CoinGecko API is the more versatile choice for most crypto products and businesses, combining extensive market coverage, comprehensive data, and flexible access options across a wide range of use cases. While CoinAPI is suitable for a defined set of use cases, including high-frequency trading and quantitative microstructure research.

Coverage: CoinGecko brings CEX, onchain DEX, derivatives, category, and treasury data together in a single API, enabling applications to access the broader crypto ecosystem without stitching together multiple data sources. CoinAPI provides CEX market data, such as trades, quotes, and full L2/L3 order books, across separate products.
Cost efficiency: CoinAPI is typically ~180x more expensive than CoinGecko API for equivalent data workloads. This is because CoinGecko uses a highly efficient flat credit charge model with a lower cost per API call, CoinAPI uses a data-point-based credit model with higher credit consumption as data volume increases.
Best fit: For the majority of crypto data use cases, CoinGecko API is a better fit as it offers broader coverage across wallets, exchanges, and regulated fintechs and neobanks under a highly cost efficient pricing model. CoinAPI is well suited if your workload requires CEX L2/L3 order books, EMS Trading API-based order execution with FIX connectivity, or multi-year raw-tick CEX history for HFT and quantitative research.

CoinGecko API and CoinAPI both deliver real-time and historical market data, including tick-level and ultra-low-latency feeds, but they are built for different use cases. CoinGecko API is a unified crypto data platform covering broad and comprehensive crypto market data across CEX and DEX, alongside ecosystem datasets such as categories, news, and treasury data through a single API. It also supports asset discovery and treasury-data tracking, enabling institutional and fintech teams to monitor the cryptocurrency holdings of public companies and governments alongside core market data.

Meanwhile, CoinAPI focuses on CEX market data, providing normalized trades, quotes, full L2 order books (L3 on select venues), and OHLCV from individual exchanges, supported by a deep multi-year tick archive and FIX connectivity.

This guide compares CoinGecko API and CoinAPI across the key factors that matter, including coverage, cost predictability, historical depth, real-time delivery, onchain data, compliance readiness, and developer experience to help you determine which data provider is the best fit for your specific use case.

Full disclosure: We built the CoinGecko API. This comparison is based on publicly available documentation, pricing, and direct API testing, including credit consumption measurements for equivalent queries on both platforms.

CoinGecko API vs CoinAPI at a Glance

CoinGecko API specializes in Volume-Weighted Average Price (VWAP) aggregated market data while offering the broadest crypto data coverage, flexible delivery methods, and a more cost effective credit and pricing model. Meanwhile, CoinAPI specializes on exchange-level market data, including CEX order-book depth and raw tick data.

The following overview compares the core features and capabilities that developers and enterprises typically evaluate:

Dimension	CoinGecko API	CoinAPI
Asset coverage	17K+ coins, 42M+ tokens	18K+ coins
Endpoints	80+ endpoints (CEX & DEX)	35+ endpoints (CEX only)
Exchange & network coverage	1,700+ exchanges (CEX & DEX) 250+ networks with unified cross-chain coverage	400+ exchanges (CEX only) <10 DEX venue coverage with no unified cross-chain index
Historical depth	Daily market data since 2013 Hourly and 5-minute intervals since 2018 Onchain OHLCV down to 1-second intervals since 2021	Tick-by-tick trades and L2/L3 order book history since 2010 at 1-second granularity (typically more expensive due to high credits required)
Real-time delivery	WebSocket: sub-second streaming of aggregated prices. tick-level onchain trades, & 1-second OHLCV. Webhooks: event notifications	WebSocket: sub-second streaming of single-exchange trades, quotes, OHLCV, & L2/L3 order books FIX: low-latency market-data feed
Billing model	Flat Credit Model: 1 credit = 1 API call, regardless of payload size One subscription with one predictable billing and built-in spend controls	Metered pricing, with separate billing for each product: Market Data API: 1 credit / 100 data points Exchange Rates API: Per rate (from $0.50/100) Indexes API: Per API call Flat Files: Per request ($10/1k) + data by GB
Entry pricing	Keyless access + Free API key Basic plan ($35/mo): commercial license included, 100K call credits, 300 RPM	One-time $25 signup credit Market Data API — Startup plan ($79/mo): 1K REST credits/day Exchange Rates, Indexes & Flat Files: No fixed monthly plan with pay-as-you-go pricing based on usage
Compliance & data integrity	SOC 2 Type II attested Auditable 5-step Price Methodology Independently verifiable aggregated data that support MiCA, CARF, CLARITY regulatory requirements Trust Score & GT Score integrity signals 99.9% Enterprise SLA	SOC 2-aligned only (no attestation report) 3-step Price Methodology (aggregation, quality filtering, VWAP calculation) 99.9% SLA on selected plans
Developer & AI surface	AI Integrations, SDKs, MCP, CLI, Agent Skills, x402, Spreadsheet add-ons (Google Sheets & Excel)	SDKs & MCP

Which API Should You Use: CoinGecko or CoinAPI?

CoinGecko API provides a unified access point for crypto market data across centralized and decentralized ecosystems, supporting teams building a wide range of applications and products. CoinAPI is well suited for advanced trading workflows, including CEX execution and market microstructure analysis, with its exchange-level order books, quotes, and tick-level historical data.

Use case	Recommended	Why
Wallets, portfolio trackers & explorers	CoinGecko	CoinGecko provides the broadest coverage for consumer apps, with 42M+ tokens across 250+ networks, combined with comprehensive data including batch pricing, coin metadata, market discovery data, news, categories, and treasury holdings data through one integration.
Exchanges & trading apps	CoinGecko	CoinGecko provides unified CEX and DEX reference pricing, coin/token search, and discovery features including trending assets, top gainers/losers, and categories. This helps exchanges deliver both pricing and discovery experiences.
DeFi, DEX analytics & onchain apps	CoinGecko	CoinGecko provides real-time onchain data and ultra-low-latency streams, including advanced multi-chain pool filtering across 260+ networks through Pools Megafilter, tick-level trade data through OnChainTrade WebSocket and onchain OHLCV. It also supports trader and holder analytics through dedicated endpoints. By comparison, CoinAPI's DEX and onchain coverage is limited to <10 individual venues, with no unified cross-chain view.
AI agents & MCP builds	CoinGecko	CoinGecko’s MCP server, CLI, x402 endpoints, official SDKs, and Agent Skills enable AI agents and copilots to access crypto data directly using natural language. CoinAPI also offers AI integrations through MCP, though this is currently limited to its CEX market-data products.
HFT & execution engines	CoinAPI	CoinAPI provides full L2/L3 order-book depth and EMS Trading API for order execution, including smart order routing and TWAP/VWAP strategies via REST and FIX. CoinGecko complements market discovery signals such as top gainers and losers, sector-level category analysis, and sub-second onchain data streams.
Market-microstructure research & multi-year raw-tick CEX backtesting	CoinAPI	CoinAPI focuses on raw CEX market microstructure, providing continuous tick-by-tick trades and L2/L3 order-book history since 2010, with large Flat File archives.

Is CoinAPI More Expensive Than CoinGecko API?

Yes, CoinAPI is approximately 180x more expensive than CoinGecko API for an equivalent data request. CoinAPI generally requires more credits per request and each credit costs more.

Credits per request: CoinAPI requires 8x - 24x more credits than CoinGecko for equivalent data requests.
Cost per credit: Each CoinAPI credit costs approximately 7.5x more than a CoinGecko credit at entry-tier pricing.
Combined impact: The effective cost of equivalent workloads is approximately 180x higher for typical hourly data requests.

Credits alone do not show the full picture because each provider defines credits differently. CoinGecko charges 1 credit per API call, while CoinAPI charges 1 credit per 100 data points. This means CoinAPI’s credit usage increases with the amount of data returned, on top of its higher cost per credit.

CoinGecko Basic plan with 100K monthly credits costs ~$0.00035 per credit, while CoinAPI Startup plan with 30K monthly credits costs ~$0.00263 per credit, making it roughly 7.5x higher per credit. The more relevant comparison is therefore the actual dollar cost of retrieving the same dataset.

Operation	Data points	CoinGecko (Basic, $35/mo)	CoinAPI (Startup, $79/mo)	How much more CoinAPI costs
Full daily history (past 2 years)	~730	1 credit = $0.00035	8 credits = $0.0211	~60x more
100 days of hourly OHLCV (1 coin)	2,400	1 credit = $0.00035	24 credits = $0.0632	~180x more
100 days of hourly OHLCV data (100 coins)	240,000	100 credits = $0.035	2,400 credits = $6.32	~180x more

Use the interactive cost comparison below to explore costs across different workload scenarios:

CoinGecko API: Flat Credit Model on a Single Plan

CoinGecko charges 1 credit per REST API call, regardless of how many data points are returned.

The entry-level Basic plan ($35/month) already includes a commercial license, WebSocket streams, and webhooks, while the Analyst plan ($129/month) offers exclusive endpoints, higher API credits, and increased rate limits. All paid plans use a single subscription model, with access to CoinGecko's available data products through one API platform and a unified credit-based pricing system.

CoinAPI: Usage-Based Pricing Across Five Products

CoinAPI separates market data, exchange rates, index data, bulk files, and EMS order execution into five separately priced products, with most products billed based on data usage. The Market Data API is the only product with fixed monthly tiers, while the remaining products use usage-based pricing with no flat monthly plan.

CoinAPI Products	CoinAPI Pricings	CoinGecko API Availability (Under One Unified Plan)
Market Data API (CEX trades, quotes, L2/L3 order books, OHLCV)	Startup ($79/month): 1000 credits/day Streamer ($249/month) Pro ($599/month) Usage model: 1 credit per 100 data points. Overage pricing starts at $5.26 per 1,000 credits and tapers with volume.	Real-time data, historical OHLCV, ticker bid-ask spreads, up to 2% market depth, and tick-level DEX trade streaming via WebSocket are all available under CoinGecko's single unified plan.
Exchange Rates API (Aggregated VWAP reference prices)	Usage-metered: $0.50 per 100 rates, decreasing with volume	VWAP-aggregated market pricing is available through CoinGecko API.
Indexes API (Index / benchmark data)	Usage-metered: per API call	Category and sector-level market data are available via the categories endpoint, but not as a dedicated index.
Flat Files (Bulk historical downloads)	Usage-metered: $10 per 1000 requests + $1–$3 per GB	CoinGecko does not offer bulk flat-file downloads, though its historical data is accessible cost-effectively.
EMS Trading API (Multi-exchange execution such as smart routing, TWAP/VWAP, REST/FIX)	Separate EMS Pro product ($999+/month)	CoinGecko API does not provide order execution

CoinAPI’s metered pricing models can be suitable for targeted use cases, particularly when teams require specific data products or highly granular market coverage. The trade-off is that costs increase alongside data volume, making forecasting more complex as workloads grow. CoinGecko’s unified credit-based pricing model simplifies this process by providing a consistent way to access available data products across different use cases.

Tip: CoinAPI users may incur unexpected overage charges when usage exceeds plan credit allotments, as overages are billed rather than hard-capped. Consider setting usage limits or enabling spend controls to avoid unexpected costs.

Source: G2

CoinGecko API vs CoinAPI: Feature Comparison

Assets, Exchanges, and Network Coverage

CoinGecko indexes 17K+ coins and 40M+ onchain tokens across 1,700+ CEX and DEX venues and 260+ networks. CoinAPI covers 18,000+ assets across 400+ centralized exchanges, with limited DEX coverage.

For products that need broad asset discovery and pricing across multiple chains, beyond a defined set of CEX-listed pairs, CoinGecko’s network-wide coverage provides a more consolidated data source through a single integration. It also provides additional data categories, including derivatives, categories, and treasury data, which can reduce the need to combine multiple specialised providers.

Historical Data Access

CoinGecko’s historical data approach focuses on coverage breadth and accessibility. It provides daily historical data from 2013, hourly and 5-minute OHLC data from 2018, and onchain OHLCV down to 1-second intervals from 2021 across a broader universe of coins and tokens. This data is available through endpoints such as /coins/{id}/market_chart and /coins/{id}/ohlc. With a flat 1-credit-per-call model, accessing this historical data can be more cost-efficient for large-scale multi-asset analysis.

CoinAPI provides centralized-exchange market microstructure data, including continuous, per-exchange tick-by-tick and L2/L3 order-book archive dating to 2010, at 1-second granularity, and large Flat File datasets. This makes it suitable for use cases requiring deep CEX-level market data, such as quantitative research and microstructure analysis.

In practice, the decision depends on the workload. Teams focused on broad asset coverage, backtesting, charting, indicator calculation, and lifecycle analysis across many assets can benefit from CoinGecko’s wider historical coverage and cost-efficient pricing model, while teams requiring pre-2013 data or CEX tick and order-book-level granularity can complement with CoinAPI’s depth.

Real-Time Data and Delivery Methods

CoinGecko API and CoinAPI offer ultra-low-latency data delivery. The key difference is whether the real-time data arrives as an aggregated, ready-to-use view or as raw venue-level feeds that require further processing.

CoinGecko API provides ultra-low-latency access to aggregated, market-wide pricing data. It streams cacheless VWAP across CEX and DEX markets, providing a consolidated real-time price without requiring users to connect to multiple venues and reconcile prices themselves. Beyond aggregated pricing, CoinGecko also provides sub-second tick-level onchain trades through the OnchainTrade WebSocket, with updates at ~0.1 seconds for active pools. The Past 24 Hour Trades endpoint returns recent pool-level trade data, while the WebSocket provides DEX token prices and OHLCV candles, alongside event-driven Webhooks. These capabilities cover both sides of real-time crypto data needs, aggregated cross-market pricing and granular onchain trade-level data.

Update as of June 2026: CoinGecko WebSockets and webhook are now available on the Basic plan starting at just $29/month.

CoinAPI provides ultra-low-latency for single-exchange data. Its focus is raw, per-venue data, including tick-by-tick feeds and full order books sourced directly from individual exchanges. This includes L2 market depth broadly and L3 order-by-order data on select venues such as Coinbase and Bitso. These feeds are delivered on a venue-by-venue basis, so users requiring an aggregated market-wide view must collect data across exchanges and perform their own aggregation and weighting.

Onchain and DEX Data

CoinGecko API provides a unified, aggregated, multi-chain DEX data layer, giving users a ready-to-use market view. It allows users to access pool discovery and screening via the Pools Megafilter (30+ criteria including liquidity, volume, FDV, pool age, and safety signals), trading insights such as top traders, top holders, new and trending pools, and security indicators. This enables developers to easily build rug-detection and screening tools, smart-money analytics, holder-distribution analysis, and multi-chain dashboards without having to build and maintain their own data layer.

CoinAPI's DEX and onchain coverage is limited to select pools and venues, with comparatively narrow coverage across DEX ecosystems and blockchain networks.

Developer Ecosystem and AI Integrations

CoinGecko API and CoinAPI offer developer and AI access layers, including official SDKs and MCP servers for connecting AI agents to their data.

CoinGecko extends this access beyond traditional developer workflows with an MCP server for AI agents such as Claude, Codex, and Cursor, Agent Skills, CLI, x402 endpoints, Python and TypeScript SDKs, no-code Google Sheets and Excel add-ons. This makes CoinGecko faster and easier to adopt by reducing the technical barriers for engineers, AI/agent builders, analysts, and non-developers.

Enterprise Reliability and Compliance

CoinGecko API and CoinAPI are enterprise-grade data infrastructure that exchanges, custodians, fintechs, and regulated organizations rely on for valuation, reporting, and compliance workflows.

CoinGecko API holds an independently audited SOC 2 Type II attestation, whereas CoinAPI references SOC 2-aligned practices but has no public SOC 2 attestation report or independent compliance verification. Its penetration tests and security audits validate specific security controls but do not provide the assurance of a formal third-party compliance attestation.

Which API Is Better for Institutional Needs: CoinGecko API vs CoinAPI?

CoinGecko API is the better overall choice for most institutional needs, offering a more cost-effective solution across compliance, reporting, treasury, and data infrastructure workflows. While CoinAPI is well-suited for trading execution and market-microstructure use cases, institutional requirements often extend beyond execution into broader operational needs.

This broader coverage enables CoinGecko to support a wider range of institutional workflows, including compliant product development, RWA valuation, treasury dashboards, portfolio monitoring, and reporting infrastructure. Through a single platform, institutions can access market data, onchain analytics, and market-integrity signals to support research, treasury, risk, and compliance teams. It also provides stronger cost efficiency at scale, as cost differences grow with expanding institutional data requirements across teams and use cases.

Supporting these workflows is CoinGecko's data infrastructure, built on a proprietary 5-step Price Methodology that aggregates primary market and onchain inputs, filters outliers, and reconstructs historical data to normalize and verify market data as a reliable foundation for institutional applications:

By comparison, CoinAPI is purpose-built for institutional trading desks and quant funds requiring specialized market data infrastructure. Its EMS Trading API, FIX connectivity, and multi-year tick and order-book archive are valuable for HFT and market-microstructure workflows requiring raw execution infrastructure.

However, these capabilities are primarily optimized for trading-specific requirements rather than broader institutional workflows such as compliance, reporting, custody-adjacent workflows, and other operational requirements. For institutions seeking a comprehensive data foundation beyond trading execution, CoinGecko offers a more complete fit.

What Are Institutions & Enterprises Building with CoinGecko API?

Institutions and enterprises across exchanges, consumer wallets, cross-chain infrastructure, regulated banking, and compliance rely on CoinGecko API’s data infrastructure. Here are examples of industry-leading products built on CoinGecko at scale:

Kraken: Built on CoinGecko Market Data Infrastructure

Kraken relies on CoinGecko API to power real-time prices, comprehensive market metrics, and historical sparkline charts across Kraken.com and Kraken Pro. With 10M+ users across 190 countries, Kraken switched to CoinGecko for greater data accuracy and uptime, resulting in a 44% increase in engagement and conversion across its asset discovery experiences.

“The CoinGecko API enables us to deliver comprehensive, real-time information that empowers Kraken clients to research deeply, trade profitably, and invest with confidence. By equipping our users with the insights they need, it has become a key driver of growth and engagement at Kraken.”

— Bill King, Head of Organic Growth, Kraken

Read the Kraken case study

Deblock: Built on CoinGecko Banking-Grade Pricing Infrastructure

Deblock (Europe's first MiCA-compliant onchain bank) relies on CoinGecko API’s auditable, real-time pricing infrastructure to help meet MiCA’s strict requirements for accurate valuations and reporting, delivering banking-grade pricing across more than 100 digital assets that powers portfolio valuations, euro-to-crypto conversions, and account balance calculations.

“CoinGecko’s robust data infrastructure is the silent engine behind our portfolio visualizations, allowing Deblock to transform raw onchain data into clear, actionable insights for our users. Their accurate real-time pricing and historical depth enable us to build a seamless bridge between everyday banking and the crypto economy.”

— Mario Eguiluz, Cofounder & CTO, Deblock

Read the Deblock case study

LI.FI: Built on CoinGecko Cross-Chain Pricing Infrastructure

LI.FI relies on CoinGecko API to deliver real-time token pricing at scale. It uses CoinGecko for batch price and market data across more than 2 million tokens, alongside WebSocket for per-second updates on high-activity assets. By combining an eight-tier data bucketing architecture with CoinGecko's APIs, LI.FI processes approximately 1 billion price updates per month while reducing API calls by more than 80% compared with uniform polling.

“We evaluated over a dozen token price oracles before choosing CoinGecko as our reference provider. Our token service architecture is designed to be provider-agnostic — we can integrate any oracle — but no other API matches CoinGecko's combination of coverage across 250+ chains, real-time WebSocket delivery, and the depth of onchain data we need for automated token discovery. CoinGecko's API is what allows us to deliver enterprise-grade price freshness to clients like Robinhood, Ledger, and MetaMask.”

— Clément Bihorel, Product Lead, LI.FI

Read the LI.FI case study

Elliptic: Built on CoinGecko’s Institutional-Grade Token Pricing Infrastructure

Elliptic, a blockchain analytics and compliance firm serving financial institutions and regulators, relies on CoinGecko API to extend its pricing coverage across millions of tokens, including tokenized real-world assets (RWAs). This helps institutions understand the value of onchain assets for compliance and risk assessment workflows.

Read the Elliptic announcement

Chainalysis: Built on CoinGecko Pricing Infrastructure

Chainalysis integrated CoinGecko's price feed into its platform to provide accurate pricing for 10K+ tokens across EVM chains, Solana, and other blockchain ecosystems. The integration improves pricing accuracy across its investigations, compliance, and security products, highlighting CoinGecko's ability to support regulated, institutional-grade blockchain intelligence workflows.

Read the Chainalysis announcement

Is CoinGecko API Better Than CoinAPI?

Yes. For the majority of crypto data use cases, CoinGecko API is the more comprehensive all-round choice. It covers a broader share of the crypto market, offers more ways to access data, and brings CEX, DEX, onchain, derivatives, category, and treasury data together under a single predictable flat credit-based pricing model. It is also the more cost-effective provider for most institutional use cases, including RWA valuation, treasury dashboards, and compliance and portfolio-monitoring workflows. Compared with CoinGecko, CoinAPI can cost up to ~180x more for equivalent workloads as data requirements scale, due to differences in credit consumption and pricing models.

CoinGecko also complements execution-focused workflows with real-time cacheless aggregated market data, DEX trade ticks, 1-second onchain OHLCV, and market signals such as sector trends and top movers. These capabilities become increasingly valuable as quantitative trading expands beyond centralized exchanges into DEXs and tokenized real-world assets (RWAs). For organizations whose primary requirement is raw CEX market microstructure such as L2/L3 order books, FIX connectivity, or multi-year raw tick history, CoinAPI is suited to these execution-focused workflows.

Ultimately, the right provider depends on your workload. While CoinGecko API is the most trusted and widely used crypto data APIs in the world, trusted by leading enterprises and institutions across trading, wallets, compliance, DeFi, tax, analytics, and AI agents. For a broader comparison, see our roundup of CoinAPI alternatives for crypto data.

If you're ready to start building on the most trusted crypto data provider used by thousands of developers and companies worldwide, get a free CoinGecko API key to get started and explore the CoinGecko API documentation.

Book A Complimentary Data Consultation

Choosing the right crypto data setup goes beyond comparing APIs on paper. Different products require different combinations of data coverage, latency, infrastructure, and licensing – especially as you scale.

In this complimentary consultation, our team will walk through your specific use case, recommend the most relevant endpoints and data delivery methods (REST, WebSocket, or Webhook), and help you design a setup that’s reliable, scalable, and cost-efficient from day one.

How Brave Built a Better Crypto Search UX

2026-07-19T19:28:51Z

Brave Search is a privacy-focused search engine that doesn’t profile users, and delivers results from its own, independent index of the Web. It’s used by millions of people worldwide, and is the default search for many of the Brave browser’s 120+ million users. To support its crypto-aware audience, Brave Search integrates CoinGecko’s API to display real-time cryptocurrency data directly in the search engine results page (SERP). This market data also supports the answering of market-related crypto questions in Brave’s AI experiences, including Ask Brave (search) and Leo (browser assistant).

Key Metrics at a Glance

Brave Search has integrated the CoinGecko API to surface real-time, interactive crypto price charts and currency converters for 17,000+ cryptocurrencies. This integration also supports market valuations for assets shown in blockchain explorer results, and market data charts in Brave’s AI-powered answer experiences.
Brave Search serves over 80 million daily queries and 2.4 billion monthly queries.

Delivering Upfront Value: Crypto Data in Search Results

Traditional search engines generally require users to initiate a search, then navigate through results to find the information they need. Brave has taken a different approach to deliver actionable crypto data directly within its search results page.

When users search for cryptocurrency tickers or prices, Brave surfaces live prices, conversion rates, and price charts in its UI, without requiring the user to leave the search results page. The same search-first experience also extends into Brave’s AI-powered surfaces. Ask Brave brings AI-powered answers into Brave Search, while Leo is Brave’s browser-native AI assistant. For market-related crypto prompts, CoinGecko data helps Brave surface timely price data and charts within these answer experiences, eliminating the need to open separate tabs or visit third-party websites to check crypto prices or market data. Overall this reduces user friction, and enables quicker access to key information.

For instance, when a user searches for "BTC to USD" or prompts “What is BTC’s price performance in the past 30 days?”, Brave Search displays:

Live price updates
Interactive inline price charts
On-page conversion tools

Brave Search results displaying Bitcoin price chart.

Leo AI prompt response displaying Bitcoin price chart.

These features are powered by a direct integration with CoinGecko’s API, which supplies both real-time and historical cryptocurrency data. The /coins/markets endpoint delivers live prices, market capitalization, and 24-hour trading volume. For historical price data, Brave uses the /coins/{id}/market_chart endpoint to display inline price charts within the search UI.

Additionally, the /simple/price endpoint enables seamless conversion between cryptocurrencies and fiat currencies.

This setup allows Brave to display accurate market data for over 17,000 tokens across global fiat pairs, without requiring users to leave the search results page.

Extending Crypto Search to Wallet Holdings

Brave also extends this crypto search experience to wallet lookups. When users search an ENS domain, EVM address, or Solana address, Brave can surface a wallet’s top asset holdings directly in the search results.

CoinGecko’s broad token and market coverage helps Brave display real-time prices and market valuations to the assets shown, allowing users to understand wallet balances in market terms. This gives users a faster way to assess asset exposure, without needing to open separate tabs or manually cross-reference token balances with market prices.

ENS domain Brave Search results with live asset holdings and valuation.

Brave Search results for a Solana wallet address, with live asset holdings and valuation.

Why This Matters

By incorporating crypto market data across search results, wallet lookups, and AI-powered answer experiences, Brave is significantly enhancing the utility of its products for users active in digital assets. This integration is particularly strategic given Brave's crypto-native ecosystem: users of the Brave browser can already earn Basic Attention Tokens (BAT) via their Brave Rewards feature, creating a naturally crypto-aware user base. Brave also builds the multi-chain Brave Wallet directly into the browser, providing users a secure, easy way to manage digital assets and access Web3.

BAT tokenizes the attention economy, enabling users, advertisers, and creators to earn, engage, and transact in new ways. For these users, quick access to crypto data is essential to their daily digital experience. By eliminating the need to navigate away from search results to check BAT prices or other cryptocurrency data, Brave creates a seamless workflow that maximizes both convenience and engagement for its crypto-engaged audience. And, with the recently published BAT Roadmap 4.0, accessing crypto data via Search will be even more relevant across a variety of new use cases as they are released.

Brave’s integration of the CoinGecko API ensures that the market data behind its search results, conversion tools, market charts, wallet asset valuations, and relevant AI-powered answer experiences is sourced from a reliable, independent aggregator with broad token and market coverage. This allows Brave to display live prices, real-time asset valuations, and timely chart data directly within the user experience, supporting practical crypto search use cases without unnecessary complexity.

Get In Touch

Ready to supercharge your crypto project? Fill in the form below to connect with our API Sales team for a custom CoinGecko API plan tailored to enterprise needs.

This article was written in collaboration with the Brave team.

How Boros Turns Funding Rates Into Tradable Onchain Yield

2026-07-17T04:52:23Z

What Is Boros?

Boros is a recent product from Pendle that turns funding rates, the periodic payments perpetual futures traders pay or receive, into a tradable token called a Yield Unit (YU).

How it works: Long YU pays a fixed rate and receives the floating rate; Short YU pays floating and receives fixed.
What it's for: Speculating on funding rates, hedging an existing perp position, or capturing rate spreads across venues.
What it doesn't require: Any view on the underlying asset's price. Positions are on the rate itself, not the token.

This article is brought to you by Pendle.

If you've traded perpetual futures, you've paid or received funding: the periodic payment that flows between longs and shorts to keep a perp's price tethered to spot. It's a cost or a benefit that sits alongside every position, and up to now there's been no direct way to trade it, hedge it, or take a view on it separately from the position itself.

Boros, a recent product from Pendle, changes that. It takes the funding rate itself and turns it into something you can buy, sell, hedge, or lock in: a tradable asset in its own right, not just a side effect of holding a perp.

What a Funding Rate Actually Is

Perpetual futures don't expire like traditional futures contracts, so exchanges need a mechanism to keep the perp price tethered to the spot price. That mechanism is funding: when the perp trades above spot, longs pay shorts; when it trades below, shorts pay longs. The payment resets periodically (often every few hours), and the rate can swing sharply depending on market sentiment and positioning.

The problem is that funding is unpredictable and, until Boros, untradeable on its own. If you're running a perp position, you're stuck taking whatever the market's rate happens to be on any given day. And if you had an opinion on where funding was headed, there was no direct way to put it into a trade.

Boros’s Yield Unit (YU)

Boros solves this by wrapping a floating rate, starting with perp funding, into a tradable token called a Yield Unit (YU). Every YU market splits into two sides:

Long YU: you pay a fixed rate and receive the floating rate. You want floating rates to rise above the fixed rate you locked in.
Short YU: you pay the floating rate and receive a fixed rate. You want certainty, or you expect floating rates to fall.

Each market shows two numbers that matter: the Underlying APR (the current floating rate) and the Implied APR (the fixed rate the market has priced in). Trading YU is essentially taking a position on the gap between those two. As one example, at the time of writing an ETHUSDT market on Boros showed an Underlying APR of 1.97% against an Implied APR of 4.61%, a live illustration of how far the fixed and floating sides can diverge, though these figures move constantly and shouldn't be read as a standing opportunity.

What Can Users Do With Funding Rates on Boros?

Boros gives users three ways to act on a funding rate.

Take a rates view: You think funding is heading up or down and want to take a direct position on it, without touching the underlying token's price.

Hedge my funding rates: You already hold a perp position and want to lock in your funding cost instead of being exposed to it swinging against you.

Capture the spread: You want to exploit a funding rate difference between two venues (say, Boros pricing versus CME or Deribit) in a delta-neutral trade.

All three are variations on the same primitive, going long or short YU, applied to different goals. None require a view on where ETH, BTC, or any other underlying asset's price is going.

Why This Matters for Pendle

Pendle's original product, Pendle V2, is built around a simple idea: split a yield-bearing asset into two parts, a principal token, which represents the underlying asset itself, and a yield token, which represents the income it generates. Once separated, each half can be traded independently. Someone who wants upside on future yield can buy the yield token; someone who wants certainty can lock in a fixed return by holding the principal token to maturity. Either way, yield that used to be locked inside a single position becomes something you can price, trade, and hedge on its own.

Boros takes that same underlying idea (separate a rate from the position that produces it, then let each side trade freely) and applies it to a much bigger, faster-moving category: floating rates tied to leverage, starting with perpetual funding. Where Pendle V2 deals with yield that accrues relatively slowly and predictably (staking rewards, lending yield, LP returns), Boros deals with a rate that can flip sign within hours and is tied directly to how leveraged traders are positioned across the market.

That distinction is why Pendle is positioning Boros as a second core product rather than a feature bolted onto V2. Together, the two products span very different points on the risk and volatility spectrum: V2 for stable, income-generating yield, Boros for the sharper, more volatile rates that come from derivatives markets. The shared thread is Pendle's broader thesis: that almost any rate, however it's generated, is more useful to markets once it can be split out and traded on its own rather than bundled into a position you have to hold in full.

Beyond Crypto: Commodities and Equities Are Already in Scope

The breadth here is worth underlining. Boros isn't limited to crypto funding rates. Its market list already includes commodity-linked rates like Brent Oil, alongside the usual BTC and ETH markets.

As of writing, that Brent Oil market carried over $540,000 in notional open interest, a modest but real sign that traders are already using Boros for rate exposure outside of crypto-native assets. The long-term thesis is that any floating rate, onchain or off, could eventually be priced and traded through the same mechanism.

Trading Markets and the Boros Data Board

Boros isn't a single interface. Alongside the Markets page where trades actually happen, Boros also publishes a public Data Board for spotting where an arbitrage opportunity might be worth a closer look.

Markets: Active Rate Trading

This is where everything described above happens. On the Markets page, you pick a specific market (say, ETHUSDT or BTCUSDC), a maturity date, and a side (long or short YU), then set a size. Each market shows live Underlying APR and Implied APR, order book depth on both the long and short side, and a rate sensitivity figure showing how much your position moves for every 1% shift in implied rates. This is the surface built for the three jobs above: taking a rates view, hedging an existing perp, or capturing a cross-venue spread.

The Boros Data Board: Spotting Fixed Yield Arbitrage

The Data Board is a separate dashboard with its own tabs: Arbitrage, Funding Rates, Markets, Activity, and a Calculator. Its Global Settings let you set a lookback window (30 days out to all-time) and a moving-average smoothing period, so every table and chart underneath reflects the same time frame.

The top view features two tables sitting side by side. One shows the Boros Fixed Spread currently available on a given market, alongside its Historical Median Spread over the selected lookback and how deep that spread holds up to (±0.5% depth). The other leads with the Median Historical Spread and comparing it against the Current Funding Spread, so you can see at a glance whether today's number sits above, below, or in line with where that pair has typically traded. As an example, at the time of writing a HYPE market on Hyperliquid versus Bybit showed a Boros Fixed Spread of 6.99% against a Historical Median Spread of 7.43%, meaning the currently available fixed rate was pricing slightly below where that spread has typically sat over the past 180 days.

Beyond the tables, the Data Board also charts Per-Exchange Funding as a box-and-whisker plot (the middle 50% of the 30-day average funding rate per exchange, with whiskers showing the 5th-to-95th percentile range) and an Arbitrage Overview chart plotting each pair's median spread and P5-P95 range, with a line for the median and another for the mean. Together, these give a sense of how wide a given exchange's funding typically swings and where a specific pair's spread sits relative to its own history, before that read gets taken into a 4-Leg Arbitrage position on the Markets page.

Getting Started

Boros's Quick Start screen turns the three moves above into three guided flows, each with its own screen, terminology, and example, rather than dropping you straight into an order book.

Funding Rate Speculation

This is the direct rates-view flow. You pick an asset (BTC, ETH, and others), an exchange whose funding rate you're speculating on (Bybit, KuCoin, and others), and a time period, then enter your own prediction for the average funding rate over that window. Boros then searches for YU markets that match, going long if you expect the rate to land above the current Implied APR, short if you expect it to land below. As an example, entering BTC on KuCoin over a 23-day window shows a live average funding rate prediction of 11.94%, alongside toggles to compare that against the current rate or its 7-day and 30-day moving averages.

Funding Rate Hedge

This flow is built for people who already hold a perp position. You specify which perp and which exchange you're hedging, and Boros searches for a matching fixed-rate hedge. Under the hood, this connects two sides: a "perp trader" paying floating funding on their live position, matched against a "carry trader" who receives that floating rate and, in exchange, fixes their own funding yield through Boros. Your underlying perp position stays exactly where it is; only the funding exposure moves.

4-Leg Arbitrage

This is the more advanced, delta-neutral version of "capturing the spread." Boros presents a table of ready-made strategies: for each one, you'd go long YU on one exchange's market and short YU on another exchange's equivalent market, while Boros locks in fixed rates on both legs. The gap between what you pay on the long leg and receive on the short leg is your estimated fixed return. At the time of writing, live strategies on the board ranging up to over 21% estimated fixed APR, depending on the asset pair and maturity, a reminder that these spreads move constantly and shouldn't be read as a standing return.

For anyone building out a 4-Leg Arbitrage position, the Data Board (covered above) is a useful first stop, since it shows whether the spread you're looking at is actually wide relative to its own history before you commit capital to it.

A Few Things Worth Remembering

Boros makes funding rates tradable, but trading them still carries real risk. A few things worth keeping in mind before using it:

Funding rates are not stable. They can swing sharply in either direction depending on market positioning, and a rate that looks attractive today can move against you before your position matures.

Nothing here is a guaranteed return. Implied APR is the market's current pricing, not a promised outcome, the same way a bond's yield-to-maturity isn't a guarantee if you sell early or the issuer's rate assumptions change.

Leverage cuts both ways, on both legs. Long and short YU positions can be opened with leverage, and each leg carries its own liquidation risk independent of what the underlying asset's price does. A position can be liquidated purely on rate movement, with no change in ETH or BTC's spot price at all.

The figures in this piece are a snapshot, not a forecast. Underlying APR, Implied APR, and open interest figures cited above reflect Boros data at the time of writing and will have moved by the time you're reading this. Treat them as an illustration of how the mechanics work, not as current market conditions.

This article is an explanation of a new mechanism for a market, and is not financial advice, and not a recommendation to take a position.

Figures cited (Implied APR, Underlying APR, notional open interest) reflect Boros data at the time of writing and are illustrative only, not current market conditions or guarantees.

What Are Crypto Narratives? Top 10 Narratives for 2026 (UPDATED)

2026-07-15T09:00:00Z

What Are Crypto Narratives?

Crypto narratives are the dominant themes, trends, or beliefs that shape how investors perceive and value digital assets during a given market cycle. Narratives influence capital rotation, drive adoption of emerging technologies, and determine which sectors attract the most attention and liquidity.

How they work: Narratives simplify complex technological shifts into investable themes — like "DeFi Summer" in 2020, the NFT boom in 2021, or the AI crypto trend in 2024, or Prediction Markets in 2025-2026.
Why they matter: Identifying narratives early can help investors anticipate where liquidity will flow next. Narratives often drive price action before fundamentals catch up.
Top narratives for 2026: Stablecoins & Stablechains, Real-World Assets (RWA), AI x Crypto, AI x DePIN, Quantum, Prediction Markets, Perp DEXs, Privacy/ZK, ETFs/DATcos, and Collectible Cards.

What Is a Narrative in Crypto?

Market participants use narratives to simplify complex technological shifts into digestible investment themes. Whether it's the belief in Bitcoin as "Digital Gold" or the tokenization of real-world assets, narratives help investors predict where the next wave of liquidity will flow.

The market has increasingly favored protocols with real revenue, institutional integration, and infrastructure value over pure speculation; a rotation that continued even as Bitcoin itself corrected from its October 2025 peak near $126,000 into the low-$60,000s by July, suggesting the "flight to quality" theme held up through a genuine downturn rather than just a bull-market mood.

One important framing note: the narratives below describe medium-term thematic rotation, where capital and attention are flowing over months and quarters, rather than short-term price signals. Week-to-week price action in crypto is still frequently driven by idiosyncratic, narrative-independent events (a single protocol's news, a token unlock, a celebrity-linked launch), so a hot narrative doesn't guarantee any individual asset within it will move in lockstep.

1. Stablecoins and Stablechains

Stablecoins have evolved from a trading tool into core financial infrastructure, and 2026 has been a significant year for both their growth and their regulation. The total stablecoin market cap peaked at approximately $311 billion in April 2026, up more than 50% from roughly $205 billion at the start of 2025, before pulling back to around $290 billion by July — the sector's first real contraction since its 2025 growth wave, and a useful signal that the initial expansion phase may be maturing rather than accelerating indefinitely. Tether's USDT holds around 61% market share, while Circle's USDC has climbed to roughly 26%, continuing a multi-quarter shift toward regulation-compliant issuers.

Regulation has become the defining story of the sector in 2026, not just an afterthought. The GENIUS Act, signed into law in July 2025, faces its first real test this month: federal agencies have a July 18, 2026 statutory deadline to finalize implementing rules on stablecoin capital, reserves, and liquidity requirements. In the EU, MiCA's transition period expired on July 1, 2026 with no extensions — triggering the largest stablecoin delisting wave in European history, as Coinbase, Kraken, Crypto.com, and Binance's EU entity all restricted or delisted non-compliant tokens like USDT for EU users, while MiCA-compliant issuers like Circle picked up the resulting demand. Circle itself deepened its regulatory position further, receiving an OCC trust bank charter on July 10, 2026, allowing it to manage USDC reserves directly rather than through third-party custodians.

Alongside stablecoins themselves, we're seeing the rise of Stablechains — blockchains specifically optimized for stablecoin transactions and gas-less transfers. In 2025, several stablecoin-focused chains were launched:

Stable: A dedicated "stablechain" that launched in early December 2025.
Plasma: A Layer 1 that quickly established itself, ranking as the 8th largest blockchain by stablecoin supply within three months of its 2025 launch.

As we head into 2026, several high-profile projects are currently in development or testnet phases:

Circle's Arc: Circle’s proprietary network designed specifically for institutional stablecoin applications, currently in testnet.
Stripe & Paradigm’s Tempo: A collaboration focused on creating a high-performance payment rail, also currently in the testnet stage.

Traditional finance is joining the race too:

European Bank Consortium Chain: A group of nine major European financial institutions (including ING and UniCredit) plans to launch a MiCA-compliant Euro stablecoin chain in the second half of 2026.
Japanese Bank Platform (Progmat): Mitsubishi UFJ, Sumitomo Mitsui, and Mizuho received approval in late 2025 to jointly issue a Yen stablecoin using the Progmat blockchain platform for inter-bank clearing.

The industry is moving from "stablecoins as a tool" to "stablecoins as the infrastructure". By 2026, these dedicated chains are expected to transition from pilots to core institutional systems, offering 24/7 real-time settlement that rivals traditional systems like SEPA or SWIFT with the transparency of blockchain.

2. Real-World Assets (RWA)

Real-World Assets (RWA) remain the clearest bridge between traditional finance and crypto — and 2026 has been the year institutional infrastructure caught up to the thesis. On-chain tokenized RWAs (excluding stablecoins) grew from around $5.4 billion in January 2025 to roughly $34 billion by July 2026, a trajectory that held up even as the broader crypto market corrected sharply from Bitcoin's October 2025 peak — a notable sign that RWA growth isn't simply tracking the wider market cycle.

Tokenized treasuries remain the largest non-stablecoin category at around $11.5 billion, led by Circle's USYC and BlackRock's BUIDL, both of which have crossed $2.8 billion individually — alongside genuinely fast-growing challengers like Ondo's USDY and Centrifuge's JTRSY, both of which have more than doubled since January. Tokenized stocks have scaled from a standing start in mid-2025 to roughly $1.3 billion, with Circle, Micron Technology, and SpaceX (following its landmark June 2026 IPO) now the largest individual names — issued across a rapidly diversifying platform landscape that now includes Ondo Global Markets, Backed Finance/xStocks (under Kraken), and Binance's newly launched bStocks program.

The single biggest institutional development this year: the Depository Trust & Clearing Corporation (DTCC) — whose depository subsidiary custodies over $114 trillion in securities — received SEC authorization in December 2025 to launch a tokenization service covering Russell 1000 equities, major ETFs, and US Treasuries, and has since convened a 50+ firm Industry Working Group including BlackRock, Goldman Sachs, JPMorgan, and Citi to design it. Limited production trades began in July 2026, with a full launch targeted for October — arguably the strongest institutional validation the tokenization thesis has received to date.

Regulatory tailwinds have kept building too: the SEC's formal Tokenization Statement (January 2026), Nasdaq's approval to integrate tokenized stocks and ETFs natively (March 2026), and the ECB agreeing to treat certain DLT-issued assets as eligible Eurosystem collateral (from March 2026) all point the same direction — RWA infrastructure moving from experimental to institutionally load-bearing.

For the full breakdown — including private credit, commodity-backed tokens, RWA perpetuals, multi-chain distribution, and protocol-token risk — see our dedicated RWA guide.

3. AI x Crypto

The intersection of AI and crypto has matured past the "AI agent with a wallet" novelty phase of 2024–2025. As a medium-term theme, the story now centers on three overlapping threads: agentic payments, verifiable AI infrastructure, and compute/inference marketplaces — the last of which increasingly overlaps with the DePIN narrative below.

Agentic payments — AI agents autonomously paying for compute, data, APIs, and goods using stablecoins — moved from concept to measurable infrastructure in 2026. Keyrock reported AI agents settled over $73 million across 176 million transactions in the past year, with 98.6% of that volume settling in USDC; the median payment size was between $0.01 and $0.10, well below the ~$0.30 floor where card-network fees make traditional rails uneconomical. Multiple competing protocol standards are now live rather than theoretical: Coinbase's x402 (reviving the old HTTP 402 status code for pay-per-call APIs) had processed roughly 165 million transactions across 480,000+ agents by April 2026; Google's AP2 attracted 60+ partner organizations including PayPal, Mastercard, and Amex; and Stripe launched a competing Machine Payments Protocol (MPP) via its Tempo blockchain, partnered with stablecoin fintech RedotPay.

Forecasts vary widely on scale — Juniper Research's more conservative estimate puts 2026 agentic spend at $8 billion, climbing toward $1.5 trillion by 2030, while Gartner has floated AI agents intermediating up to $15 trillion in purchases by 2028 — but the directional bet from Coinbase, Stripe, Google, Visa, and Mastercard all building competing rails simultaneously is a strong signal this is being treated as infrastructure, not a demo. Worth naming the concentration risk directly: with 98.6% of agent payment volume running through a single stablecoin issuer, the category currently carries meaningful single-point-of-failure exposure.

Verifiable AI infrastructure is the second thread: on-chain systems for proving how a model was trained, what data it used, or that its output wasn't tampered with — positioned as a trust layer for AI outputs generally, not just crypto-native use cases.

Compute and inference marketplaces round out the third thread — decentralized networks that let anyone contribute GPU capacity or run inference jobs, an area that overlaps directly with, and is often indistinguishable from, the AI x DePIN narrative that follows.

Rather than a single hot sector, AI x Crypto is best understood as connective tissue running through several of 2026's other narratives — DePIN, prediction markets, and even RWA tooling increasingly reference an "AI layer" in their roadmaps. That cross-cutting nature is part of why AI-linked tokens have kept showing up among the stronger medium-term performers even through a broader market correction.

4. AI x DePIN

Decentralized Physical Infrastructure Networks (DePIN) coordinate real-world resources — compute, storage, wireless bandwidth, energy — through token incentives instead of centralized ownership. In 2026, the AI-focused corner of DePIN crossed a real inflection point: leading networks moved from token-subsidized growth to genuine enterprise revenue.

Render Network runs 5,600+ active GPU nodes and has rendered over 67 million cumulative frames — client work has included a Coca-Cola activation on the Las Vegas Sphere and NASA content for the ISS, alongside its pivot into general AI inference via its Dispersed.com subnet.
Akash Network hit $5 million in Q1 2026 "compute spend" — its own reported figure, tied to a March 2026 tokenomics upgrade (Burn-Mint Equilibrium) that links AKT token burns directly to network usage — with GPU utilization above 80% and usage up 428% year-over-year.
Aethir reports the largest revenue figure in the sector by a wide margin — $127.8 million for full-year 2025, according to its own disclosures, with a described annualized run rate of $166 million by Q3. Note that Nasdaq-listed Predictive Oncology invested $344 million into a digital asset treasury built around Aethir's ATH token, which in turn deploys that capital to purchase Aethir's own compute, meaning some portion of Aethir's "enterprise revenue" may be self-referential rather than fully external demand.
Bittensor, structurally different from the rest, doesn't rent hardware at all — it incentivizes the production of AI outputs directly across 128 competing subnets, and sits at the top of the AI-token category by market cap (~$3.4 billion).

DePIN-for-AI has real, growing enterprise usage in aggregate, with sector-wide annualized compute revenue estimated at roughly $180-220 million. That said, it's important to consider the gap between a project's "compute spend" and its actual "protocol revenue," which is one of the most important numbers to consider before taking any figure at face value.

5. Quantum

Quantum computing's threat to crypto shifted from a distant, decades-away concern to a compressed, actively-debated timeline in 2026. The catalyst was Google's Quantum AI team publishing a March 31, 2026 whitepaper finding that breaking Bitcoin and Ethereum's elliptic curve cryptography may require fewer than 500,000 physical qubits and roughly 1,200-1,450 logical qubits, a roughly 20-fold reduction from earlier estimates that ran into the millions. That's a genuine re-rating of the threat, not just alarmist framing — but the practical gap remains enormous: today's most advanced quantum processors run a few thousand noisy physical qubits, putting a real attack machine at minimum a decade away by most cryptography researchers' estimates.

The exposure is concentrated, not network-wide, and centers on wallets with already-exposed public keys — a byproduct partly of 2021's Taproot upgrade, which makes public keys visible by default. Bitcoin's own architecture already blunts much of the risk: most modern addresses only reveal a hashed version of the public key, not the key itself, narrowing any attack window to the brief period a transaction sits unconfirmed. Notably, Google's own disclosure was deliberately structured to avoid overstating the threat — the paper explicitly cautions that unsubstantiated resource estimates for quantum attacks can themselves function as an attack on public confidence in the system, and Google verified its findings via a zero-knowledge proof specifically so outside researchers could confirm the claims without publishing an exploitable roadmap.

The industry response moved fast relative to the threat's distance: NIST finalized post-quantum cryptographic standards back in 2024, Google set a 2029 internal deadline to migrate its own systems, and Bitcoin's BIP-360 proposal offers a voluntary path to quantum-resistant wallet formats via soft fork. The harder problem is coordination, not cryptography — migrating a fully decentralized network could take five to ten years even after a technical solution is agreed on, and dormant wallets with already-exposed keys can't be upgraded at all, leaving an unresolved governance question about whether to eventually freeze coins nobody can move to protect them.

Quantum readiness is a long-term infrastructure question, not a near-term price catalyst. The threat estimate got measurably closer in 2026, and the industry has responded accordingly — but the actual hardware gap remains large, and no attack is close to possible today. It's on this list because it's now a genuine engineering priority shaping how core protocols are built, not because it's likely to move markets on any near-term timeline.

6. Prediction Markets

Prediction markets moved from a 2024-election novelty to genuine financial infrastructure in 2026. Kalshi raised $1 billion at a $22 billion valuation in March, then began talks for a $40 billion valuation by June — nearly double in three months, with annualized revenue reportedly over $2 billion. Polymarket's own valuation sits notably lower, around $15 billion as of an April funding round backed by NYSE-parent ICE (whose total committed capital in the platform has now passed $1.6 billion) — a gap partly explained by timing: Polymarket only began charging trading fees in February 2026, meaning its valuation is priced far more on future potential than current revenue. Together, the two platforms control roughly 79% of the prediction markets industry, which Bernstein estimates could reach $1 trillion in annual volume by 2030.

The two are increasingly specializing rather than directly competing. Kalshi holds the stronger US regulatory position as a CFTC-regulated exchange; Polymarket, more crypto-native and globally popular, rebuilt its own US footing by acquiring CFTC-licensed exchange QCEX for $112 million in 2025, relaunching as "Polymarket US" that December. Despite Kalshi's regulatory edge, Polymarket still dominated the highest-profile 2026 event by volume: roughly $3 billion traded on its World Cup winner market, versus $500 million on Kalshi.

Rivalry aside, both CEOs backed 5c(c) Capital, a new $35 million fund for prediction-market infrastructure (data, liquidity, compliance) rather than the exchanges themselves. Regulatory conflict has intensified alongside the growth: Arizona filed criminal charges against Kalshi, Nevada banned it outright, and Illinois's new tax on sports contracts is being fought by both Kalshi and the CFTC in court — a state-vs-federal jurisdiction fight likely headed to the Supreme Court.

Kalshi is also using its regulatory position to expand beyond prediction markets: its CFTC-approved BTCPERP, the first Bitcoin perpetual futures product on a US-regulated exchange, did $5.5 billion in volume within two weeks of its June 2026 launch, and the company is now seeking approval to extend the same model to metals, forex, and energy. It's a useful example of how a licensed exchange can leverage its regulatory footing into adjacent product categories.

7. Perp DEXs

Perpetual DEXs kept growing as a category through 2026 — the sector captured roughly 26% of all crypto perpetual trading by late 2025, up from just 2.7% in 2023, with over $1.2 trillion in monthly volume by some estimates — but the competitive picture between individual platforms has been genuinely volatile, not stable.

Aster's rise in late 2025 was dramatic: backed by Binance co-founder Changpeng Zhao and running on BNB Chain, it briefly overtook Hyperliquid entirely, at one point capturing an estimated 45-50%+ of market share (depending on the metric) while Hyperliquid's share reportedly fell into the single digits. That dominance didn't hold. By early 2026, Hyperliquid had reasserted itself as the clear leader — estimates through mid-2026 put its share back in the 37-70% range depending on whether volume or open interest is measured — while Aster settled back down to roughly 9-20%. The broader lesson: Aster's growth was heavily incentive-and-airdrop-driven, while Hyperliquid's is backed by deeper open interest and TVL, which several analysts flag as the more durable signal of the two.

The field has also genuinely widened beyond a two-horse race. Lighter processed a reported $232 billion in 30-day volume ahead of its December 2025 token launch; StarkWare's technology now underpins a meaningful combined share of volume across Paradex, Extended, and edgeX. Hyperliquid, meanwhile, has kept building out its own ecosystem — HyperEVM, the HIP-3 framework for permissionless market creation, and its native USDH stablecoin — which is also the infrastructure behind Ventuals, a notable 2026 offshoot letting traders take leveraged positions on pre-IPO private company valuations (OpenAI, SpaceX, Anthropic) without needing actual equity access. That product is also a useful cautionary tale for the category: Ventuals' SpaceX contract reportedly crashed sharply on faulty oracle data in 2026, a reminder that "valuation" perps on illiquid private assets carry more oracle risk than a standard BTC or ETH contract.

8. Privacy and Zero-Knowledge (ZK)

Privacy coins had one of 2026's most striking rallies — up roughly 288% as a category in 2025 and still outperforming into 2026 — but the three leading projects are taking genuinely different paths with the institutional attention that's followed.

Zcash is courting institutions directly. ZEC pushed past $600 in May, with Multicoin Capital and Arthur Hayes both disclosing positions, after Grayscale filed to convert its Zcash Trust into a spot ETF and the SEC closed its review in January without enforcement action. Its optional-privacy design keeps it listed on Coinbase and Robinhood, unlike Monero; shielded-pool adoption has climbed to ~30% of supply, up from 8% in 2024.

Monero is doing the opposite — leaning further into mandatory privacy rather than courting compliance. Its FCMP++ upgrade entered beta in May, replacing ring signatures with proofs referencing 150M+ historical outputs (mainnet expected mid-2026), even as its all-or-nothing model keeps driving exchange delistings (73 and counting), since it's structurally incompatible with FATF Travel Rule compliance.

A third path: Midnight, a Cardano-affiliated chain backed by ~$200M from Charles Hoskinson, launched mainnet in March with an institutional partner list from day one (Google Cloud, MoneyGram, Worldpay, a Bank of England-regulated bank). It explicitly isn't chasing Monero/Zcash's privacy-maximalist users — Hoskinson has said it's built for institutions that want selective disclosure, not an all-or-nothing switch.

The regulatory backdrop keeps tightening even as prices rally: the EU's AMLR is phasing in privacy-coin restrictions by 2027, and the FATF Travel Rule remains the structural chokepoint pushing exchanges to delist anything without a compliance pathway — meaning long-term relevance may hinge less on price and more on whether a project can offer regulators an "on" switch, the way Zcash and Midnight can and Monero can't.

9. ETFs and DATcos

The DATco (Digital Asset Treasury Company) story looks very different in July 2026 than it did even a few months ago. DATcos exploded from just 4 companies in 2020 to 142 by late 2025, holding $137.3 billion in crypto — Strategy alone accounts for roughly half that, at $70.7 billion — but the model has hit real turbulence since the broader market corrected from its October 2025 highs. Most DATcos have now halted new purchases or begun selling, and even Strategy, the company that built its entire identity on "never selling," authorized a sale of up to $1.25 billion of its Bitcoin treasury in 2026, with the first tranche — 3,588 BTC, worth roughly $216 million — executed in early July. The driver was structural: dividend obligations on Strategy's STRC preferred stock nearly tripled between January and April, pushing its cash-reserve runway below the company's own one-year minimum policy and forcing a real bitcoin drawdown to rebuild it. With over $1 billion still available under the authorization and STRC still trading below its intended peg, further sales are considered likely — a genuine crack in the "never sell" playbook that goes well beyond symbolism.

The regulatory backdrop is genuinely live right now. The CLARITY Act — the market-structure bill meant to formally define federal jurisdiction over digital assets — passed the House in July 2025 and cleared the Senate Banking Committee 15-9 in May 2026, but has since stalled: no vote has been scheduled, with three unresolved disputes (ethics rules tied to the Trump administration's own crypto holdings, law-enforcement objections to a developer-shield provision, and a fight over stablecoin yield) still blocking the bipartisan support needed to pass.

Amid all this, product innovation hasn't stopped: Solana staking ETFs have launched and are already seeing fee competition play out in public — Grayscale's Solana Staking ETF cut its sponsor fee from 0.35% to 0.19% and its staking fee from 23% to 7% in June 2026, a sign issuers are competing hard for share in a still-nascent product category even as the DATco trade struggles.

10. Collectible Cards

Tokenized collectibles, specifically physical trading cards vaulted and represented on-chain as redeemable tokens — became one of 2026's more surprising growth stories. The model inverts the usual NFT playbook: instead of manufacturing speculative value from nothing, these platforms digitize assets that already carry real collector value, then add blockchain-native liquidity and gamified "gacha" pack-opening mechanics on top. The sector hit a record $7.4 million in weekly revenue in May 2026, up 337% year-over-year, partly fueled by Pokémon's 30th anniversary driving renewed mainstream interest ahead of a global "30th Celebration" card set launching in September 2026.

Collector Crypt, the Solana-native leader, has overtaken longtime frontrunner Courtyard in weekly revenue as of June 2026, with cumulative trading volume around $1.3 billion and cumulative protocol revenue surpassing $64 million. More than 30% of users have redeemed an actual physical card from the vault — a meaningful sign the model isn't purely speculative churn. The platform has also expanded into "Collectibles-Fi," partnering with Loopscale to let users borrow USDC against vaulted cards, and integrated with the Solflare wallet (4 million monthly users) to bring pack-opening directly in-wallet.

In terms of regulatory risks, the SEC maintains that tokenized securities are still securities, and most tokenized collectible offerings likely qualify for registration requirements under that framework — a real legal exposure distinct from, though sometimes confused with, gambling-style loot-box scrutiny. IP risk is another potential challenge: The Pokémon Company tightly controls its trademarks and generally prohibits commercial use without licensing, an overhang for any platform built on its cards. And the entire model still depends on trusting a centralized vault custodian — if that custody fails, the on-chain token has nothing behind it.

11. Speculative & Consumer Narratives

While these categories remain a meaningful slice of the market, the story here is retention and infrastructure, not growth at the pace of the narratives above them.

Crypto Cards

Spending on-chain assets directly via Visa/Mastercard rails with crypto cards remains one of the more durable consumer on-ramps in crypto, converting trading and holding activity into everyday spending power without requiring users to understand the underlying infrastructure. Of the three categories in this section, this is the one with the clearest staying power — it doesn't depend on a speculative cycle to keep working.

Memes

The sector has cooled in 2026 — CoinGecko's own sub-sector tracking shows major categories like Dog-Themed and 4chan-Themed tokens are down roughly 30% or more from their mid-April levels through July, with smaller niches (Solana Meme, AI Meme, Chinese Meme) holding flat near the bottom of the range. That said, in spite of the overall decline in the sector, Canary Capital has filed for a spot PEPE ETF, and multiple spot DOGE ETF applications are pending at the SEC — institutional product-wrapping reaching even the most speculative corner of the market.

ICOs

Milestone-based escrow and more accountable, community-first launchpads continue to exist as a steadier alternative to the 2017-era free-for-all, though it's a minor and slow-moving corner of the market rather than an active 2026 story.

Conclusion

The throughline across 2026's narratives is a rotation toward real revenue, institutional integration, and infrastructure. Stablecoins, RWA, and AI-linked compute all kept growing through a genuine market correction rather than merely riding a bull-market mood — a real test that most of 2025's hype-driven categories haven't faced. Even where speculation persists, it increasingly comes with something real underneath it: Collector Crypt's card platform is genuinely profitable, not just high-volume; Kalshi and Polymarket are raising capital at levels that rival established fintechs; DTCC's tokenization pilot and Google's own quantum vulnerability disclosure are the kind of institutional and scientific validation speculative narratives rarely get.

The categories that didn't make that transition tell the opposite story. Meme tokens cooled sharply as capital rotated elsewhere, and DATcos were hit hardest of all — a reminder that 'crypto adjacent' isn't the same as 'crypto resilient' once a business model depends on trading volume rather than underlying usage.

The clearest lesson for 2026, then, isn't which narrative is hottest — it's which ones can prove they don't need the hype to keep working.

Disclaimer: This article is for educational purposes only and does not constitute financial advice. Always conduct your own research (DYOR) before investing in any digital assets.