Those improvements are real. Gemini 3.7 Flash climbed from 49.0% to 65.3% on DeepSWE v1.1 and reached 30.4% on Zapier’s AutomationBench, up from 17.0% for its predecessor. Independent testing from Artificial Analysis also placed it among the fastest reasoning models at roughly 340 output tokens per second.

The launch headline leaves out several conditions. The discounted price expires at the end of 2026, other models remain cheaper, and the consumer rollout through Gemini Spark excludes several large markets. Google’s model also loses to rivals on some agent and computer-use evaluations. Developers therefore need to separate a strong Flash upgrade from the broader claim that it is the best or cheapest model for every workload.

What Is Gemini 3.7 Flash

Gemini 3.7 Flash is Google’s latest high-speed model for coding, agents and knowledge work. It replaces Gemini 3.6 Flash as the company’s main workhorse model only three weeks after the previous version arrived.

Google describes the update as the result of developer feedback and algorithmic improvements. Gemini 3.7 Flash is designed to follow instructions more reliably and recover from roadblocks across multi-step tasks.

MemeBurn reported Gemini 3.7 Flash references appearing in Google’s Python SDK one day before the official launch. Google has now confirmed access through the Gemini API, Google AI Studio, Android Studio, Antigravity and Gemini Enterprise.

For individual users, Gemini 3.7 Flash also powers Gemini Spark for Google AI Pro and Ultra subscribers in supported countries. That consumer route has regional restrictions that do not necessarily apply to developer API access.

The Benchmark Gains Are Substantial

Google’s official Gemini 3.7 Flash announcement shows consistent improvement over Gemini 3.6 Flash across coding, web development, document analysis and automation.

The DeepSWE improvement matters for coding agents because the benchmark covers longer software engineering tasks. FrontierCode indicates stronger first-pass code quality, while WebDev Arena points to better web interfaces.

Artificial Analysis gave Gemini 3.7 Flash High an Intelligence Index score of 56, four points above Gemini 3.6 Flash. It also measured output at around 340 tokens per second, nearly three times the speed of GPT-5.6 Terra in its comparison. Production teams should still measure task success, retries and total token use rather than extrapolating from speed.

The Half-Price Offer Ends in December

Google has set Gemini 3.7 Flash at $0.75 per million input tokens and $3.75 per million output tokens, half the original price of Gemini 3.6 Flash.

Google’s introductory rate expires on December 31, 2026. Beginning January 1, 2027, input pricing increases to $1.50 and output pricing rises to $7.50.

The offer is clearly disclosed, but budgets should use the 2027 rate for applications expected to remain in production next year.

At the time of writing on August 14, Gemini 3.7 Flash is also not the lowest-priced major API model. OpenAI lists GPT-5.6 Luna at $0.20 for input and $1.20 for output. MemeBurn has covered how the GPT-5.6 Luna price cut changed the market for high-volume AI workloads.

DeepSeek lists V4 Flash at $0.14 for uncached input and $0.28 for output, making its current output rate more than 13 times lower. New DeepSeek V4 pricing takes effect on August 17, so the gap may soon narrow.

Price comparisons also need to account for capability. Luna and V4 Flash target high-volume efficiency, while Gemini 3.7 Flash is competing on stronger coding, multimodal and agent performance. The relevant figure is cost per successful task, not the cheapest token in isolation.

Strong Results Do Not Make It the Best at Everything

Gemini 3.7 Flash performs well across a broad benchmark set, but Google’s own comparison does not show a universal lead.

TechTimes reported that GPT-5.6 Terra scored 50.2% on OSWorld 2.0, ahead of Gemini 3.7 Flash at 38.1%. Claude Sonnet 5 also led on Agent’s Last Exam with 33.3%, compared with Gemini at 26.3%. Artificial Analysis placed Gemini at 56 on its Intelligence Index, one point behind GPT-5.6 Terra and Muse Spark 1.2.

OSWorld measures interaction with computer environments, while Agent’s Last Exam tests difficult multi-step reasoning. Gemini’s coding and speed advantages do not guarantee the same ranking in those tasks.

AutomationBench needs similar context. The benchmark is built by Zapier and tests end-to-end workflows across 47 tools in sales, marketing, operations, support, finance and human resources. Gemini 3.7 Flash currently leads its public leaderboard at 30.44%.

The tasks reflect patterns across Zapier’s platform, making the result useful for business automation. It remains one environment, and teams using different tools, permissions and data may see another ranking.

Gemini Spark Is Not Available Across Much of Europe

Google says Gemini 3.7 Flash will power Gemini Spark for Google AI Pro and Ultra subscribers. Spark can manage multi-step tasks, work with connected apps and continue certain jobs in the background.

The Gemini Apps support page states that Spark is unavailable in the European Economic Area, the United Kingdom, Switzerland and Nigeria. Users also need to be at least 18, use a personal Google account and keep Gemini Apps activity enabled.

This restriction applies to Spark rather than the model’s entire availability. Developers may have other routes through Google AI Studio, the Gemini API or enterprise products.

Google says Spark reaches more than 160 countries, but the excluded markets still cover a significant share of European users.

Who Should Use Gemini 3.7 Flash

Gemini 3.7 Flash suits coding agents, document processing and high-throughput web applications, especially where latency and first-pass code quality matter.

Enterprise trials should record task success, response time, token use, retries and human review, then recalculate the result using the January 2027 price.

Teams choosing primarily on API cost have cheaper options. GPT-5.6 Luna and DeepSeek V4 Flash currently undercut Gemini, although their capability profiles differ. MemeBurn’s broader GPT-5.6 model comparison explains where OpenAI’s Sol, Terra and Luna tiers fit.

Consumers in the EEA, Britain, Switzerland and Nigeria cannot use Gemini Spark at launch.

Gemini 3.7 Flash is therefore a strong workhorse release with unusually fast output and meaningful coding gains. Its value depends on whether those advantages survive a team’s production workload after the introductory discount disappears.

FAQs

How Much Does Gemini 3.7 Flash Cost

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens through December 31, 2026. The rates rise to $1.50 for input and $7.50 for output on January 1, 2027.

Is Gemini 3.7 Flash Better Than Claude Sonnet 5

It depends on the task. Gemini 3.7 Flash leads on Zapier’s AutomationBench and offers faster, cheaper inference. Claude Sonnet 5 scored higher on Agent’s Last Exam in the published comparison, indicating an advantage on that difficult multi-step agent test.

Is Gemini 3.7 Flash the Cheapest AI Model

No. As of August 14, 2026, GPT-5.6 Luna and DeepSeek V4 Flash have lower published input and output prices. DeepSeek has announced that its V4 API pricing will change on August 17.

Where Is Gemini 3.7 Flash Available

Developers can access the model through the Gemini API, Google AI Studio, Android Studio and Antigravity. It is also available in enterprise products. Consumer access through Gemini Spark excludes the EEA, the United Kingdom, Switzerland and Nigeria at launch.

The post Google Launches Gemini 3.7 Flash but Its Low Price Has an Expiry Date appeared first on Memeburn.

Best Free Antivirus by Platform: Quick Comparison 

The AV-TEST scores are based on the June 2026 Windows 11 testing round and reflect three areas that matter in everyday use: protection, performance, and usability. Each category is scored out of 6, giving a maximum of 18 points. The results gave us a useful way to compare detection strength alongside system impact and false positives. 

Is Windows Defender Actually Good Enough on Its Own? 

For most Windows users, yes. Microsoft Defender has reached the point where installing a third-party antivirus isn’t an automatic requirement for staying protected. It’s no surprise the antivirus was the top choice in 2025, with 23% of users relying on it as their primary protection.

We found the appeal during testing. Defender starts working with Windows, runs quietly in the background, and keeps key security controls inside Windows Security. It’s also a practical free antivirus program for users who want real-time protection. 

For a typical computer, that combination can provide full protection against many everyday threats while keeping system performance in mind. There’s no extra subscription to manage or a separate security app competing for attention.

Its protection also goes beyond basic malware scanning. Windows Defender comes with cloud-based detection, behavior monitoring, ransomware protections, and defenses against potentially unwanted applications. 

From our perspective, third-party antivirus still has an edge if you want extras such as virtual private networks (VPNs), a password manager, privacy monitoring, or broader scam protection. For everyday Windows use, though, we’d have no hesitation making Defender our default choice.

How Free Antivirus Software Actually Makes Money

Free antivirus solutions exist because the free version usually plays a role in a much bigger business. The malware protection may cost you nothing, but the company still has several ways to turn a free user into a paying customer when they need more advanced features.

• Premium upgrades: The free version handles core malware detection, while features such as advanced ransomware protection, VPN access, identity monitoring, or privacy controls sit behind a subscription. The software becomes a working demonstration of the paid product.
• Freemium product ecosystems: Companies can use antivirus as the starting point for selling other security products. VPNs, password managers, data backups, and device-optimization tools can all become part of the same subscription.
• Advertising and promotional offers: Free users may see upgrade messages, discounts, product recommendations, or prompts for related services. Avast was particularly noticeable here during our testing, with upgrade messaging appearing more frequently than we’d prefer.
• Data and privacy considerations: Security companies have faced scrutiny over how they collect, use, or share user data. That makes the privacy policy worth checking before installation, even when the software itself doesn’t charge you.

The important point is that free doesn’t automatically mean inferior. Defender and Bitdefender show that useful protection can be available without paying. When we evaluate a free antivirus, we look at how well it protects the device and how much commercial pressure comes with using it.

Best Free Antivirus for Windows 

Windows users already have a capable antivirus sitting inside the operating system, so installing another security suite isn’t automatically an upgrade. We tested the leading free options with that baseline in mind, paying attention to detection, system impact, useful extras, and how aggressively each product pushed its paid plans.

1. Avast Free Antivirus

• Best for: Users who want the broadest free feature set and don’t mind upgrade prompts
• Key strength: Strong independent detection results combined with a wide range of free security features
• Price: Free

Avast Antivirus is one of the strongest free options we tested when we looked at how much protection you actually get without paying. In June 2026, AV-TEST gave Avast Free Antivirus a perfect 18/18 score. AV-TEST is an independent antivirus testing lab that evaluates security products under controlled conditions, so its results give us a useful benchmark beyond what a vendor says about its own software. Avast got full marks for protection, performance, and usability in that round.

Our hands-on experience backed up the lab results. Avast antivirus feels like a complete security suite, with a polished interface and several useful protection layers available without a subscription. You can access all the features included in its free tier without having to assemble separate security products. Additionally, you don’t need much technical knowledge to find your way around it.

The catch is hard to miss. Avast regularly pushes its paid plans, and those prompts became one of the more noticeable annoyances during our testing. We also found the software less appealing on older hardware, where its broader feature set can have a greater performance impact.

Still, Avast makes the most sense when you want more than basic malware detection without immediately paying for a security suite. Our testing showed that its free tier offers enough depth for everyday protection, but the frequent upgrade prompts are a real part of the experience. If those interruptions don’t bother you, the feature-to-cost ratio is hard to ignore. 

2. Bitdefender Antivirus Free

• Best for: Users who want quiet, lightweight protection
• Key strength: Strong malware detection with minimal interruption
• Price: Free

The best antivirus experience can sometimes be the one you barely notice. That was our biggest takeaway after spending time with Bitdefender Antivirus Free. The software stayed quiet during everyday use, with far less emphasis on upgrades than we experienced with Avast. We could adjust the essentials, run a scan, and leave it working in the background.

Protection is still the main reason to consider it. Bitdefender has performed strongly in AV-Comparatives, an independent testing organization that evaluates antivirus products against real-world threats. Its free tier also protects against malware and malicious websites, giving it a solid foundation for everyday use. 

The product is also useful for malware blocking and protection from malicious and fraudulent websites. Its broader paid lineup includes products such as Bitdefender Total Security for users seeking more than the free tier.

We noticed another benefit on less powerful hardware. Bitdefender doesn’t try to pack the free version with every possible security tool, which helps keep the experience focused. If you’re using an older laptop, that restraint can matter.

From our research, Bitdefender makes a strong case when you value protection without the noise. It’s lightweight, easy to live with, and far less distracting than many free competitors we’ve tested. After all, antivirus software should protect your computer without constantly becoming another task to manage. 

3. AVG AntiVirus Free

• Best for: Users looking for Avast-level core protection in a familiar free package
• Key strength: Strong detection based on the same underlying engine as Avast
• Price: Free

AVG and Avast have more in common than their branding suggests. Avast acquired AVG in 2016, and the two products share the same underlying antivirus engine. That means you shouldn’t expect a dramatic difference in raw malware-detection capability simply because the applications look different.

Where we noticed more of a distinction was in the user experience. AVG puts a considerable amount of emphasis on getting users into its wider paid ecosystem. The upgrade prompts can feel more persistent than you’d expect from a product you’re using because it’s free.

The protection itself remains credible. AVG provides real-time malware protection, web protection, and other core security functions without requiring a paid subscription for the basics. That gives you a solid layer of everyday protection against common threats, while the paid plans mainly add broader security and privacy features. 

So why choose it over Avast?

There isn’t a compelling detection-based reason for most users, to be honest. If you already prefer AVG’s interface or have used its tools before, there’s nothing wrong with staying there. But if you’re starting from scratch, we’d compare the amount of interruption you’re willing to tolerate before making the choice.

4. Avira Free Security

• Best for: Users who want an established alternative to Avast and AVG
• Key strength: Reliable protection with a broader security toolkit
• Price: Free

Not every worthwhile antivirus needs to dominate the charts to earn a place on your PC. Avira Free Security stood out to us as a credible middle-ground option during testing. It doesn’t have Defender’s built-in Windows advantage or Avast’s sheer presence, but it brings a long security track record and respectable independent testing results.

The protection goes beyond a basic malware scanner. Avira covers everyday threats while adding security and privacy-focused tools around the core antivirus experience. We found the overall package useful for someone who wants a little more functionality without immediately stepping into a paid security suite.

Independent testing labs support that assessment, although the numbers need context. One hands-on evaluation recorded about 72% full-scan detection and roughly 85% real-time detection. Results can vary as testing methods, malware samples, and software versions change, so we wouldn’t use one round to rank Avira above every competitor.

What mattered more in our evaluation was the consistency across different testing rounds. Avira has enough independent evidence behind it to make the free version worth considering, particularly if you’re looking beyond Avast and AVG.

Unfortunately, it’s not the lightest option, and you’ll encounter some prompts for paid features. Still, the underlying protection gives Avira a legitimate place among the top free antivirus options.

5. Sophos Free Home

• Best for: Users looking for a current alternative outside the usual free-antivirus shortlist
• Key strength: A fresh option worth considering in 2026
• Price: Free tier available

Some antivirus names show up in almost every comparison. Sophos Free Home caught our attention because it doesn’t get nearly as much consumer coverage, despite coming from a company with deep cybersecurity experience. It has also appeared in newer 2026 comparisons, including testing roundups published as recently as June, making it a more current option worth examining.

Sophos brings an enterprise-security background to the conversation. The company has spent years working on threat prevention, web protection, and security management for organizations, so its security credentials aren’t built solely around a consumer antivirus product.

Our assessment is more cautious. We wouldn’t place Sophos above products with a deeper body of current independent consumer testing simply because it’s a newer inclusion. Antivirus software needs evidence behind it, and a fresh appearance on a comparison list isn’t enough to establish long-term performance.

That doesn’t make Sophos irrelevant. Quite the opposite. It’s worth keeping on your shortlist if you’re looking for an actively maintained alternative beyond the usual Avast, AVG, and Avira choices. 

During testing, we noticed that Sophos feels more focused on direct protection than the feature-heavy experience offered by some competitors. The interface was easy to navigate, the core security controls were clear, and we didn’t find ourselves working through a maze of unnecessary settings. That made it a practical option, although its smaller consumer footprint means there’s less hands-on history to draw from than with the better-established names.

6. Microsoft Defender

• Best for: Windows users who want protection without installing another antivirus
• Key strength: Built into Windows with no separate subscription
• Price: Free with Windows

Microsoft Defender is the product we’d expect most people to overlook while searching for the best free antivirus software. There’s no flashy standalone application to download, and Microsoft doesn’t need to convince you to install it. It’s already there.

We tested it from that perspective and found the biggest benefit was how little maintenance it needed. Windows Security handles the core protection experience, while updates and security intelligence arrive through Microsoft’s normal Windows infrastructure.

Defender also benefits from Microsoft’s enormous cloud-security infrastructure. Suspicious files and behaviors can be assessed through Microsoft’s broader security systems, giving the antivirus more context than a purely local scanner would have.

It isn’t perfect for every situation. Users who want bundled privacy tools may find third-party products more attractive. A third-party suite may also bundle a simple password manager, software updater, parental controls, or other privacy-focused features that aren’t central to Defender.

But there’s a strong argument for leaving Defender alone. Every additional security application introduces another interface, another update mechanism, and potentially another source of notifications.

If you’re looking for free antivirus for Windows and don’t have a specific reason to add another product, we’d start with Defender before downloading anything else.

7. Surshark Antivirus

• Best for: Users who already use Surfshark’s privacy tools and want security features in the same ecosystem
• Key strength: Combines antivirus with broader privacy and security tools
• Price: Availability depends on the Surfshark plan

Surfshark makes more sense once you look beyond antivirus alone. It is closer to a broader internet security package, where the antivirus tools sit alongside other services. During our testing, we found that its appeal comes from bringing several security functions into one ecosystem, with antivirus sitting alongside privacy-focused tools such as its VPN. That setup is convenient if you already use Surfshark and want fewer separate security products to manage.

The antivirus side handles malware scanning and suspicious files, while the VPN addresses a different part of the security picture. Still, we wouldn’t treat those functions as interchangeable. A VPN can protect your connection and improve online privacy, but it won’t replace an antivirus engine that detects malicious software on your device.

That distinction also shaped our recommendation. If you’re starting from scratch and simply want free antivirus for PC, Surfshark wouldn’t be our first choice. Defender, Bitdefender, or Avast gives you a clearer antivirus-focused solution.

Surfshark becomes more interesting when you already value its wider privacy ecosystem. Our testing showed that consolidation is the real attraction here. You can keep more of your security tools under one provider, although that convenience only makes sense if you actually need the additional privacy features.

Best for On-Demand Scanning

8. Malwarebytes

• Best for: Users who want a second layer of protection alongside Defender or another primary antivirus
• Key strength: Strong on-demand scanning for malware, potentially unwanted programs, and suspicious software
• Price: Free for on-demand scanning; premium plans add real-time protection

Now, this might sound surprising, but from our research, Malwarebytes makes more sense as a second opinion than as your main antivirus. We tested the free version by running manual scans after installing unfamiliar software and checking systems where we wanted another layer of scrutiny. The biggest advantage was its role as a separate scanner. It didn’t need to take over the protection already provided by Defender.

Malwarebytes has built a strong reputation around detecting potentially unwanted programs and suspicious software. One detailed hands-on comparison found that pairing Malwarebytes Free with Windows Defender could cover roughly 99% of home users. Defender provides continuous protection, while Malwarebytes gives you a separate on-demand scanner when you want to investigate something.

What we liked most was the flexibility. Malwarebytes Free can sit quietly until you need it. If a download looks suspicious, a browser starts behaving strangely, or you simply want an independent check, you have another scanner ready to go. 

Even so, we wouldn’t recommend running two full-time antivirus products simultaneously. That’s unnecessary and can create resource conflicts. A primary antivirus paired with an on-demand scanner gives you the extra checking power without making both programs fight for the same system resources. 

Do You Need Antivirus on Mac? 

No, Mac users don’t need to install antivirus software. Based on our research, we found that macOS already provides a strong baseline of protection, with built-in malware defenses, app verification, system integrity safeguards, and regular security updates from Apple.

That makes us cautious about recommending third-party antivirus to every Mac owner. For typical use, Apple’s built-in protections cover a lot of ground. If you keep macOS updated, download apps from reputable sources, and avoid suspicious attachments and links, adding another security program isn’t automatically necessary.

Still, there are cases where an extra layer can make sense. Businesses may need endpoint protection as part of their security policies. Someone who regularly moves files between Mac and Windows computers may also appreciate additional scanning. We’d consider it for users who handle sensitive data or frequently download software from less controlled sources.

We tested Avast Free, Avira Free, and Malwarebytes as Mac-compatible options, and all three can provide additional protection. Malwarebytes is particularly useful if you want an on-demand second opinion without changing your existing setup.

Our recommendation is to start with Apple’s built-in security and add software because you have a specific risk to address. Don’t install antivirus in a Mac simply because you assume macOS has no protection without it. 

Do You Need Antivirus on iPhone and Android? 

The answer depends on how the mobile operating system handles apps and security. We looked at both platforms separately during our evaluation because the same antivirus advice doesn’t apply to iPhone and Android users. 

iPhone

You don’t need traditional antivirus on an iPhone.

Apple’s app sandboxing prevents applications from freely inspecting other apps and system files. This makes conventional antivirus scanning difficult in the first place. Apple also doesn’t allow traditional antivirus apps to operate on iOS in the same way they do on Windows.

You’ll find plenty of apps in the App Store marketed around “security,” but many provide services such as VPNs, breach monitoring, password management, or phishing protection. They aren’t traditional antivirus scanners running across your iPhone.

The bigger security concerns for iPhone users tend to involve phishing attacks, stolen credentials, malicious links, fraudulent websites, compromised accounts, and outdated software. Keep iOS updated, use strong authentication, and be cautious about links and login requests while you browse online. Those habits address risks that an antivirus app wouldn’t necessarily solve anyway.

Android

Android gives you more flexibility, which also creates more opportunities for mistakes. Google Play Protect provides baseline malware scanning automatically. That’s enough for many users who install applications through Google Play and keep Android updated.

The risk changes when you start sideloading applications. Installing APK files from unknown websites bypasses some of the protections people assume they’re getting from the Play Store, and malicious or modified apps can create a much bigger problem.

That’s where an additional product, such as Bitdefender or Malwarebytes, can help with suspicious files and other malware.

We wouldn’t recommend every Android user install a third-party antivirus. If you stick to reputable app stores and keep Play Protect enabled, start there. If you regularly sideload apps, an additional security layer becomes much easier to justify.

The Kaspersky Question: Why It’s Banned in Some Countries 

Kaspersky’s detection capabilities are difficult to dismiss. The company reported detecting an average of 500,000 malicious files per day in 2025, and independent testing has also consistently rated its malware protection highly. 

So why would a product with that kind of technical track record be restricted in some countries? It’s about trust and national security concerns. 

The U.S. government banned Kaspersky from providing antivirus software and cybersecurity services to U.S. customers in 2024. The concerns were about the company’s ties to the Russian government and the potential risks associated with its software and data access. The UK had also issued restrictions in 2017 affecting government use of Kaspersky products. 

Those restrictions matter when you’re deciding what to install. If you’re in a country where Kaspersky is banned or restricted, we’d choose another antivirus regardless of its detection performance. Technical performance doesn’t override legal or security considerations. Besides, there’s no reason to build your security setup around software you may not be permitted to use. 

For users elsewhere, availability and restrictions can change. Check the current position in your country before installing Kaspersky, particularly if you’re using it on a business or government-managed device. Its malware protection may be excellent, but antivirus software also needs a level of trust in the company operating it. 

How to Choose the Right Free Antivirus

After testing these products across different devices and use cases, we found that the best free antivirus program depends less on how many features appear on the product page and more on what you actually need it to do. Some users need nothing beyond quiet, built-in protection. Others benefit from stronger detection, fewer interruptions, or a second scanner for suspicious files.

If you want zero-effort protection

Stick with Microsoft Defender. It’s already built into Windows, runs in the background, and doesn’t need another installation or subscription. We found it particularly easy to recommend for people who keep Windows updated and want reliable protection without managing another security product.

If you want the most free features

Choose Avast Free Antivirus. Its perfect 18/18 AV-TEST score from June 2026 and broad collection of free security features make it one of the strongest packages we tested. The catch is the upgrade messaging. If you can tolerate the prompts, Avast gives you a lot without paying.

If you hate interruptions

Go with Bitdefender Antivirus Free. It keeps the interface restrained and doesn’t constantly push you toward premium features. We preferred it when we wanted antivirus protection running quietly in the background without turning security into another thing to manage.

If you want a second scanner

Pair Malwarebytes Free with Microsoft Defender. We found Malwarebytes particularly useful for manual scans when something looked suspicious. Defender can handle real-time protection while Malwarebytes provides an independent second check when you need one.

If you’re using a Mac

Start with macOS’s built-in protection. Most Mac users don’t need dedicated antivirus for ordinary use. If you want another layer, Avast Free, Avira, or Malwarebytes are legitimate options we tested on Mac.

If you use an iPhone

Skip traditional antivirus apps. Apple’s sandboxing limits what these apps can actually do, so most “security” apps on the App Store focus on VPNs, breach monitoring, or other privacy features rather than conventional malware scanning.

If you’re using Android

Keep Google Play Protect enabled. It provides baseline app scanning automatically. If you regularly sideload apps outside Google Play, we’d consider adding Bitdefender or Malwarebytes for extra protection.

If you’re considering Kaspersky

Check your country’s restrictions first. In jurisdictions where Kaspersky is banned or restricted, we’d choose another product regardless of its strong detection record. Outside those jurisdictions, Kaspersky remains worth considering if top-tier malware detection is your priority, provided its current availability and regulatory status work for you.

Final Verdict 

After putting the major free antivirus options through everyday workflows, Microsoft Defender is the recommendation we’d make for most Windows users. It needs virtually no setup and provides a strong baseline without asking you to tolerate another company’s upgrade funnel.

Avast earns the nod for users who want the broadest free feature set, backed by its perfect 18/18 AV-TEST result in June 2026. Bitdefender is the cleaner choice if you care more about quiet operation, while AVG and Avira remain capable alternatives with different trade-offs.

Malwarebytes serves a different purpose. We like it most as a free second-opinion scanner alongside Defender, not as a replacement for continuous protection.

Mac users have less reason to install third-party antivirus, and iPhone owners generally don’t need traditional antivirus at all. Android users have a different decision to make. Google Play Protect provides a baseline layer of protection, but the risk increases when you install apps from outside the Play Store. 

Ultimately, the best free antivirus software is the one that matches your platform and risk without creating another problem to manage. Free protection has become good enough that you don’t need to pay simply to get competent malware defense. The real question is what additional protection, convenience, or privacy features you actually need.

FAQs

Is there 100% free antivirus?

Yes. Microsoft Defender, Avast Free Antivirus, Bitdefender Antivirus Free, AVG AntiVirus Free, and other products offer free protection without requiring a paid subscription. Free tiers may limit advanced features or promote upgrades, so check exactly what’s included before installing.

Is free AVG better than Windows Defender?

Not necessarily. AVG uses the same underlying antivirus engine as Avast, while Microsoft Defender is built directly into Windows and provides real-time protection without another installation. AVG adds some extra security features, but its frequent upgrade prompts can make Defender the simpler choice for most Windows users.

Is there any really free antivirus?

Yes. Microsoft Defender is genuinely free with Windows and provides real-time antivirus protection without requiring a separate subscription. Avast, AVG, Bitdefender, and Avira also offer free tiers, although some advanced features and protections are reserved for paid plans.

What’s the best totally free antivirus?

Microsoft Defender is the best totally free option for most Windows users. It provides real-time protection without a separate subscription or installation. Avast and Bitdefender are stronger alternatives if you specifically want additional features or a different user experience.

The post 8 Best Free Antivirus Software in 2026: Windows, Mac & Mobile  appeared first on Memeburn.

Beta builds start rolling out in China on August 14, with three batches of eligible devices scheduled through mid-September.

Here is everything you need to know about HyperOS 4: the full feature breakdown, eligible devices, and the timeline for global users.

HyperOS 4 Embraces the Liquid Glass Design Trend

The most visible change in HyperOS 4 is its glass-inspired user interface. Xiaomi has joined the Liquid Glass design movement that has swept across Android since Apple introduced the aesthetic in iOS 26.

The system renders realistic refraction throughout the interface. UI cards, Control Center toggles, and notification panels feature translucent, frosted-glass layering with dynamic reflections that respond to wallpaper colors. Xiaomi claims the system calculates depth, specular highlights, and refraction angles in real time using GPU-accelerated rendering.

Nearly every major Android manufacturer, from OPPO to Samsung, has adopted some version of this glass language over the past year. HyperOS 4 goes further than most by applying the effect system-wide rather than limiting it to select elements.

Lock Screen, Widgets, and Customization

HyperOS 4 overhauls how users organize their home and lock screens.

Lock screen customization now lets users freely arrange the clock, notification layout, and widget placement, a step up from HyperOS 3’s fixed positioning.

Widget stacking allows up to 10 widgets in a single home screen slot. Users swipe through stacked cards with physics-based 2.5D transitions. Smart auto-rotate surfaces different widgets based on your daily routine: morning weather, work calendars, and evening media controls cycle automatically.

Folder resizing gives users more control over how app groups appear on the home screen.

Floating apps now rotate to match portrait or landscape orientation automatically, without the jarring transition that older HyperOS versions sometimes produced.

Faster Apps, Better Camera, Fewer Dropped Frames

HyperOS 4 introduces what Xiaomi calls HyperCore, a set of optimizations focused on load calculation and memory preloading.

App loading speed sees a measurable improvement. Based on Xiaomi’s internal testing, after nine hours of continuous phone usage, HyperOS 4 loads apps approximately 18% faster than HyperOS 3. The system uses AI to anticipate upcoming resource demands and stages them in RAM before the user taps.

Camera processing has been tightened as well. HDR photo processing drops from 310ms to 240ms, a roughly 23% improvement. Cold-launching the camera is now 200ms faster than before, which means less waiting when pulling the phone out of your pocket for a quick shot.

Video playback has been optimized to virtually eliminate dropped frames.

These gains build on Android 17, which introduced app memory limits and performance features at the platform level.

Super AI Assistant 2.0: Xiaomi’s Answer to Google Gemini

The AI centerpiece of HyperOS 4 is Super AI Assistant 2.0, powered by Xiaomi’s open-weight MiMo language model.

The assistant handles voice transcription, note organization, photo album search, travel planning, and smart home control. Xiaomi has also connected it to its automotive ecosystem, so the assistant works across phones, tablets, IoT devices, and Xiaomi smart cars.

The interaction model has been redesigned around Xiaomi Super Island, the interactive area around the punch-hole camera cutout. When you issue a request, Super Island shows a processing indicator rather than immediately taking over the full screen. The complete interface only appears once the AI has a response ready. Most phone AI assistants hijack the entire display instantly. Xiaomi’s approach keeps you in context until there is something worth showing.

Inspiration Ball: Xiaomi’s Circle to Search Alternative

One of the more distinctive HyperOS 4 features is Inspiration Ball, a floating pointer that gives the AI contextual awareness of on-screen content.

Users can drag the ball onto a street address on screen and issue a voice command to open navigation instantly. They can also point it at a product image and request a shopping search. The feature replicates much of what Google’s Circle to Search does, but runs entirely through Xiaomi’s own AI stack.

Because Inspiration Ball overlaps functionally with Circle to Search, it may not appear in the global HyperOS 4 release. Google’s feature is already baked into Android 17 on devices with Google Mobile Services, and Xiaomi may avoid the redundancy outside China.

For more on the Xiaomi 18 series and HyperOS 4, see our Xiaomi 18 Pro leaked specs and Xiaomi 18 vs Xiaomi 17 comparison.

HyperOS 4 Beta: Full Device List and Timeline

Beta testing begins August 14, 2026 in China, divided into three batches.

Batch 1 (August 14, 2026)

• Xiaomi 17 Ultra (including Leica Edition)
• Xiaomi 17 Pro Max
• Xiaomi 17 Pro
• Xiaomi 17
• Redmi K90 Pro Max (including Champion Edition)
• Redmi K90
• Xiaomi Pad 8 Pro
• Xiaomi Pad 8

Batch 2 (August 27, 2026)

• Xiaomi 17 Max
• Xiaomi 17T Pro
• Xiaomi 17T
• Xiaomi 15 Ultra (including Satellite Edition)
• Xiaomi 15S Pro
• Xiaomi 15 Pro
• Xiaomi 15
• Redmi K90 Max
• Redmi K90 Ultra
• Redmi K Pad 2

Batch 3 (September 17, 2026)

• Redmi K100 Pro Max
• Redmi K100 Pro
• Redmi K80 Pro
• Redmi K80 Pro Extreme Edition
• Redmi K80
• Xiaomi Mix Flip 2
• Xiaomi Pad 7 Ultra
• Xiaomi Pad 7S Pro 12.5

The first batch will receive software in the afternoon on August 14, while Batches 2 and 3 will follow a more gradual rollout.

When Will HyperOS 4 Go Global?

Xiaomi has not confirmed a global release date yet. However, the pattern is predictable. HyperOS 3 launched its China beta in August 2025 and reached global markets in September. A similar timeline would put the global HyperOS 4 beta in September 2026, with a stable release arriving in October or November.

Global users with the Xiaomi 17T Pro and Xiaomi 17T should be among the first to receive the update outside China, as both appear in Batch 2. The recently launched Redmi 17 5G ships with HyperOS 3 on Android 16, and whether it receives HyperOS 4 will depend on Xiaomi’s update policy for mid-range devices.

Xiaomi’s upcoming foldable and the Xiaomi 18 series are expected to ship with HyperOS 4 out of the box later this year.

How HyperOS 4 Compares to One UI 9

HyperOS 4 enters a crowded update season. Samsung’s One UI 9 is already in beta on the Galaxy S26, also built on Android 17, and debuted at Galaxy Unpacked 2026.

Where Samsung focused on practical refinements and security, Xiaomi is betting bigger on visual identity and AI. The glass UI is more dramatic than anything Samsung has shipped, and Super AI Assistant 2.0’s smart home and automotive control goes further than what rivals currently offer.

FAQs

When is the HyperOS 4 release date? 

Xiaomi announced HyperOS 4 on August 13, 2026, with beta testing starting August 14 in China. A stable public release is expected roughly six weeks later.

What Android version is HyperOS 4 based on? 

HyperOS 4 runs on Android 17, which Google released to Pixel devices on June 16, 2026.

Will HyperOS 4 be available globally?

No global timeline has been confirmed yet. Based on previous years, expect the global beta in September 2026 and stable firmware by October or November.

Is my Xiaomi phone eligible for HyperOS 4? 

Confirmed beta devices include the Xiaomi 17 series, Xiaomi 15 series, Redmi K90 and K80 lines, several Pad models, and the Mix Flip 2. More devices will be added as the rollout progresses.

What is Inspiration Ball in HyperOS 4?

A floating pointer that lets users drag over on-screen content and issue contextual voice commands, such as navigating to an address or searching for a product in an image. It works similarly to Google’s Circle to Search.

How does HyperOS 4 improve performance? 

Xiaomi reports 18% faster app loading after nine hours of use, 23% faster HDR processing, quicker camera startup, and virtually zero dropped frames during video playback.

The post HyperOS 4 Is Official: New Glass UI, AI Features, Beta Devices and Release Date appeared first on Memeburn.

The unusually fast update was confirmed by Google on 13 August. Gemini 3.6 Flash had only reached general availability on 21 July.

The timing isn’t completely unexpected. Gemini 3.7 Flash had already appeared in Google’s Python SDK before the official announcement, suggesting Google was moving quickly towards another Flash release.

Now we know what changed.

Gemini 3.7 Flash is built to make AI agents more reliable

Google says 3.7 Flash improves software engineering, knowledge work and web development, but the most important changes are around how the model completes complicated tasks.

It can follow instructions more closely, respond to roadblocks, ask for clarification when necessary and spend more reasoning effort on multi-step plans and tool calls.

That matters when an AI model moves beyond answering questions.

An agent might need to inspect a codebase, identify a problem, modify several files, run tools, verify the result and recover if one of those steps fails. A small error early in that chain can derail everything that follows.

Google’s pitch is that 3.7 Flash fails less often and needs fewer manual retries.

That’s also the direction Google has been taking with Gemini Spark, its always-on personal AI agent.

Spark is switching to Gemini 3.7 Flash and can use the model to work across tasks such as consolidating files, drafting emails and updating status documents.

Coding performance gets another jump

Coding is one of the clearest areas where Google wants 3.7 Flash to stand out.

Google says the model produces more accurate code on its first attempt and performs better at debugging, resolving software issues and generating production-ready code.

Independent benchmark data also points to a meaningful improvement.

The DeepSWE v1.1 leaderboard currently scores Gemini 3.7 Flash at about 65% under its high-effort configuration, compared with roughly 47% for Gemini 3.6 Flash. DeepSWE tests agents on long software-engineering tasks written from scratch across dozens of real code repositories.

That makes the three-week turnaround more interesting.

Gemini 3.6 Flash was already positioned as a more efficient coding and agent model. Google isn’t waiting for another major Gemini generation to improve that layer.

It’s iterating the workhorse model instead.

Google is also making Flash much cheaper

Performance isn’t the only headline.

Gemini 3.7 Flash launches with introductory API pricing of $0.75 per million input tokens and $3.75 per million output tokens through 31 December 2026.

That’s half the original Gemini 3.6 Flash rate.

There’s an important detail, though: Google is applying the same promotional pricing to Gemini 3.6 Flash. From 1 January 2027, Google currently plans to charge $1.50 per million input tokens and $7.50 per million output tokens for the models.

So the real competition isn’t simply about benchmark scores anymore.

Models that perform slightly better but require repeated calls, longer outputs or expensive reasoning can become costly when deployed across millions of requests. Google is trying to improve the performance side while also pushing down the cost of running agents at scale.

Developers get more control over how much Gemini thinks

Gemini 3.7 Flash keeps a one-million-token context window and supports up to 64,000 output tokens.

Developers can also choose between low, medium and high thinking levels. Medium is the default.

Low thinking prioritises speed for tasks such as chat, incident response and quick data analysis. High thinking allows the model to spend more effort on difficult coding, maths, reasoning and tool-heavy agent workflows.

That flexibility could be more important than a single benchmark result.

A company doesn’t necessarily want maximum reasoning on every customer request. It may want cheap, fast responses for routine work and deeper reasoning only when a difficult task appears.

Google’s rapid release cycle is becoming the real story

Gemini 3.5 Flash became generally available in May. Gemini 3.6 Flash followed in July. Gemini 3.7 Flash arrived three weeks later.

Meanwhile, Google has already confirmed that work on Gemini 4 has started.

We think the interesting part is the strategy this reveals. Google doesn’t appear to be treating every model number as a massive generational launch anymore.

Flash is beginning to look more like continuously updated infrastructure.

For South African and African developers, that could make capable AI agents cheaper to experiment with, particularly for businesses building customer support, document processing, software development or internal automation tools.

The trade-off is that developers may also have to get comfortable with a much faster model lifecycle.

If Google can replace a production model after only three weeks, how quickly will businesses be expected to test, migrate and optimise for the next one?

FAQs

What is Gemini 3.7 Flash?

Gemini 3.7 Flash is Google’s latest Flash-series AI model for coding and agentic workflows. It is designed for fast, cost-efficient tasks that can involve reasoning, tool use, software development and multi-step execution.

When was Gemini 3.7 Flash released?

Google released Gemini 3.7 Flash on 13 August 2026. Gemini 3.6 Flash became generally available on 21 July, meaning the new model followed only 23 days later.

How much does Gemini 3.7 Flash cost?

Until 31 December 2026, Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens under Google’s introductory pricing. Google says standard pricing of $1.50 for input and $7.50 for output will take effect from 1 January 2027.

The post Google launches Gemini 3.7 Flash just three weeks after Gemini 3.6 appeared first on Memeburn.

That makes the Grok 4.6 vs Claude Opus 5 comparison unusually close on capability but dramatically different on cost. Claude Opus 5 still holds a narrow intelligence lead and offers twice the context window. Grok responds with lower API pricing and competitive results across several agentic evaluations.

The practical winner depends on whether a team needs the highest reliability on difficult tasks or wants frontier-level performance at a price that can scale.

Grok 4.6 vs Claude Opus 5 comparison

The pricing gap is the most immediate difference. A workload using one million input tokens and one million output tokens would carry a headline token cost of $8 on Grok 4.6 and $30 on Claude Opus 5. That makes Grok about 73 percent cheaper in this simplified example before caching, batch discounts, reasoning settings and retries are considered.

Headline rates do not reveal the full production cost. A cheaper model may require more attempts or additional human review, while a more expensive model can sometimes finish a task with fewer tokens. Teams should therefore measure the cost of a successful task rather than comparing token prices alone.

Claude Opus 5 keeps the intelligence lead

Artificial Analysis gives Claude Opus 5 a score of 63 on its Intelligence Index, compared with 61 for Grok 4.6. The gap is small, but it supports Anthropic’s position that Opus 5 is the safer choice when capability matters more than the API bill.

Anthropic says Claude Opus 5 is designed for difficult software engineering, knowledge work and multi-step agent tasks. The model is also stronger at checking its own work and continuing through ambiguous problems. Those qualities matter in code review, financial analysis and enterprise workflows where a plausible but incorrect answer can create expensive downstream errors.

Its one-million-token context window is another material advantage. Grok 4.6 has a 500,000-token window, according to Artificial Analysis. Both limits are large, but Opus can hold substantially more code, documents and tool history in one request.

Memeburn’s earlier look at Claude Opus 5 and its lower pricing relative to Fable 5 explains why Anthropic positioned Opus as the premium everyday model rather than its most restricted research system. It offers much of the company’s top-end capability at a rate intended for regular professional use.

Grok 4.6 makes frontier agents cheaper

SpaceXAI trained Grok 4.6 across software engineering, knowledge work, web development, computer-aided design and other agent environments. The company says the model can sustain longer projects, test its own work and improve visual or interactive applications over several iterations.

Independent results support the cost argument. Artificial Analysis measured Grok 4.6 at $0.84 per task in its evaluation framework and placed it on the cost-performance frontier. It also completed long-horizon knowledge work in roughly 53 turns on average, compared with about 103 turns for Claude Opus 5 at maximum effort in the same analysis.

That result does not mean Grok is universally better. It shows that model quality must be evaluated together with the path taken to reach an answer. Fewer turns and lower per-token rates can make a large difference when an agent repeatedly searches, writes code, runs tools and revises its output.

The pricing strategy continues the approach covered in Memeburn’s Grok 4.5 launch analysis. SpaceXAI is trying to narrow the capability gap without raising the base price, which puts pressure on premium models whose output tokens cost several times more.

Which model is better for coding

Claude Opus 5 is the stronger choice for difficult debugging, root-cause analysis and code review where consistency is more important than price. Anthropic reports that the model leads Frontier-Bench and performs close to Fable 5 on CursorBench at maximum effort.

Grok 4.6 is more attractive for high-volume development work, iterative application building and agents that generate large amounts of code. SpaceXAI reports a 69.9 percent score on CursorBench 3.2, showing that the lower price does not come with an obvious collapse in coding ability.

Developers should still test both models inside the same harness. Benchmark rankings can change with prompting, tool access, reasoning effort and repository structure. Memeburn’s ranking of the best AI models in 2026 also shows why one overall leaderboard rarely identifies the best model for every job.

Which model is better for business AI agents

Grok 4.6 has the stronger economic case for customer support, research assistance, repeated workflow automation and other tasks where token usage can grow rapidly. Its low output price gives businesses more room to let agents iterate without turning every extra response into a major cost increase.

Claude Opus 5 is better suited to higher-value workflows where errors are costly and the model must maintain instructions across very large files or long sessions. Legal review, complex financial work and critical software changes fit this profile, although human verification remains necessary.

The wider shift toward routing different jobs to different models is already changing enterprise spending. As Memeburn previously reported, cheaper AI models are reshaping business budgets because companies increasingly reserve premium systems for the tasks that justify them.

Grok 4.6 or Claude Opus 5

Claude Opus 5 wins on peak capability, context length and careful execution. It is the better default when a failed task costs more than the additional token spend.

Grok 4.6 wins on price-performance. It reaches the same frontier tier while charging 60 percent less for input and 76 percent less for output than Opus 5. That advantage becomes difficult to ignore at production scale.

For many teams, the most efficient setup will use both. Grok can handle broad, repeatable and output-heavy work, while Opus receives the smaller set of tasks that require deeper verification or a larger context window.

FAQs

Is Grok 4.6 better than Claude Opus 5

Grok 4.6 offers better value and competitive agent performance, but Claude Opus 5 retains a narrow intelligence lead and a larger context window. The better choice depends on the workload and the cost of errors.

Is Grok 4.6 cheaper than Claude Opus 5

Yes. Grok 4.6 costs $2 per million input tokens and $6 per million output tokens. Claude Opus 5 costs $5 and $25 respectively.

Which model is better for coding

Claude Opus 5 is better suited to difficult debugging, code review and complex repository work. Grok 4.6 is more cost-effective for high-volume coding, rapid application development and iterative agent workflows.

Which model has the larger context window

Claude Opus 5 supports one million tokens, while Grok 4.6 supports 500,000 tokens according to Artificial Analysis.

Can Grok 4.6 replace Claude Opus 5

It can replace Opus 5 in many cost-sensitive coding and automation tasks. Teams working with very large contexts or high-stakes outputs should evaluate reliability before switching completely.

The post Grok 4.6 vs Claude Opus 5: Is Cheaper AI Finally Better? appeared first on Memeburn.

The company unveiled Ultrafast mode for GPT-5.6 Sol on 13 August 2026, a new OpenAI API service tier powered by Cerebras. OpenAI says it can run GPT-5.6 Sol up to 14 times faster than Standard processing, while generating as many as 750 output tokens per second.

That number comes with an important qualifier: up to. OpenAI isn’t promising every request will suddenly run 14 times faster, and Ultrafast remains a limited preview for selected customers while capacity expands.

Still, the interesting part isn’t simply watching words appear faster. It’s what happens when a frontier model becomes quick enough to sit inside workflows where delays can change the outcome.

Ultrafast attacks the speed-versus-intelligence trade-off

Fast AI has traditionally involved a compromise. Developers could choose a smaller model for lower latency or wait longer when a task needed stronger reasoning.

OpenAI wants Ultrafast to narrow that gap. The company says the new tier runs GPT-5.6 Sol faster rather than requiring developers to switch to a smaller or more specialised model.

That matters because Sol sits at the top of the GPT-5.6 family alongside Terra and Luna. Sol targets complex reasoning and agentic work, while the other models give developers different balances of cost, capability and speed.

OpenAI has also been attacking the cost side of that equation. It recently cut GPT-5.6 Luna pricing by 80% and Terra by 20%, while keeping Sol’s Standard API price unchanged.

At the same time, OpenAI introduced Fast mode for GPT-5.6 Sol, which delivers up to 2.5X the speed of Standard processing at twice the Standard price.

Ultrafast now pushes that latency race much further.

Real-time AI agents could be the bigger story

OpenAI highlights incident response, financial research, fraud analysis, customer support, commerce and other interactive applications as areas where extra speed could matter.

Consider an outage.

Engineers may need to inspect application logs, recent code changes and internal reports while a system is still failing. OpenAI says its own developers have been testing Ultrafast for this type of incident-response workflow, helping them analyse changing evidence and prepare potential fixes in real time.

Research offers another example. When an AI model can complete each reasoning step more quickly, teams can potentially run more experiments and iterate several times during the same working session instead of waiting between lengthy model responses.

This is where speed becomes more than a nicer user interface.

An AI agent that pauses for minutes between meaningful steps feels like background automation. One that responds almost immediately can become part of a live loop between a developer, customer, analyst and software system.

The industry is already pushing hard in this direction. Memeburn recently looked at Xiaomi’s MiMo reaching around 1,000 tokens per second, showing how inference speed itself is becoming another battleground between AI companies.

Cerebras is becoming part of OpenAI’s inference strategy

The hardware story matters too.

According to OpenAI, Ultrafast represents the next stage of its partnership with Cerebras, whose hardware specialises in ultra-low-latency AI inference.

Inference is what happens after an AI model has been trained. Every time you send a prompt, infrastructure has to run that model and generate the answer. Faster inference means less waiting between sending a request and receiving useful output.

OpenAI says Cerebras is helping GPT-5.6 Sol reach up to 750 output tokens per second under Ultrafast.

That signals another shift in the AI race. Companies aren’t competing only over who trains the smartest model anymore.

They are increasingly competing over who can deliver that intelligence fastest, cheapest and most reliably when millions of people and software agents actually use it.

Speed still has to prove its business value

For South African companies, lower latency could be useful in customer support, fintech, ecommerce, cybersecurity and developer tools.

But speed alone doesn’t settle the business case.

Local teams still have to think about the total cost of running AI workflows, particularly because API bills are typically priced in US dollars. Faster processing only creates value when it improves the economics of the task being completed.

That’s why cost per useful result may matter more than tokens per second.

Ultrafast also isn’t broadly available yet. OpenAI says GPT-5.6 Sol Ultrafast remains a limited preview for selected customers, with wider access planned as capacity grows. Businesses interested in the tier can register for Ultrafast access updates.

So what we’re watching now isn’t whether 750 tokens per second looks impressive in a demo.

It’s whether developers start building products that simply weren’t practical when frontier intelligence came with a noticeable wait.

If your AI agent could think almost as fast as you can interact with it, what would you build differently?

FAQs

What is OpenAI Ultrafast mode?

Ultrafast is a new OpenAI API service tier that runs GPT-5.6 Sol at much higher inference speeds. OpenAI says it can reach up to 750 output tokens per second and operate up to 14X faster than Standard processing. It is currently available through a limited preview.

Is GPT-5.6 Sol Ultrafast a different AI model?

No. Ultrafast is a faster processing tier for GPT-5.6 Sol, rather than a separate lower-capability model. OpenAI’s goal is to reduce latency without requiring developers to move demanding workloads to a smaller model.

Can anyone use GPT-5.6 Sol Ultrafast now?

Not yet. OpenAI says Ultrafast is available to a select group of customers during the preview period. The company plans to expand access as additional capacity becomes available.

The post OpenAI previews GPT-5.6 Sol Ultrafast mode at up to 14X speed appeared first on Memeburn.

Best AI Note-Taking Apps in 2026: Quick Comparison

Here is a side-by-side comparison of the best AI note-taking apps to help you decide which offers more solutions for your use case.

Two Types of AI Note-Taking Apps

There are two types of AI note tools: personal note assistants and team-grade apps. Tools like Reflect, Otter.ai, or Notion, with plugins, help a person write and organize their own notes. The AI drafts summaries and sends reminders, but you still file the notes yourself since everything stays in your private workplace.

The second type is a team-grade app. Tools like Tana, Otter.ai, or Fireflies in their CRM-sync modes do more. They turn a note into a real task and send it into tools your team already uses, like project trackers, shared docs, and Salesforce integrations. This builds shared knowledge that the whole team can search, rather than a private pile of notes.

Best AI Meeting Notetakers

AI meeting notetakers turn calls into structured notes, action items, and follow-ups without manual work. Tools like Jamie, Fathom, Otter.ai, Fireflies, Granola, Reflect, Notion, Tana, NotebookLM, and Plaid NotePro capture audio from Google Meet, Microsoft Teams, Zoom, and in-person conversations, then use AI to produce summaries, track topics, AI meeting notes and create smart chapters.

Some run as visible bots in the call; others record locally, build notes from your live typing, turn conversations into tracked tasks, ground answers in your uploaded documents, or use a dedicated consumer-technology hardware recorder.

While all these tools can save you and your team from manually reviewing conversations, the right choice depends on your need for accuracy, privacy, CRM integrations, team workspaces, research workflows, or standalone recording.

1 Jamie

• Best For: Anyone who wants the single most accurate, private AI note-taker without a bot joining the call.
• Key Strength: The best-tested accuracy of any tool in this category, delivered without a bot joining your call as a visible participant.
• Price: Free: €0 (10 meetings/month, 30 minutes each). Plus: €21/month billed annually (€25 monthly). Pro: €39/month billed annually (€47 monthly). Team: €33/month per seat, billed annually.

Jamie is the best AI note-taking app for accuracy. In our head-to-head test, we ran the same 11-minute Alphabet Q1 2026 earnings call through five tools at once and scored each transcript against the official record. Jamie’s transcript had the fewest errors on names, numbers, and technical terms by a wide margin. It also works without a bot joining your meeting, so internal meetings and customer-facing teams stay private.

The app captures audio from your device or browser, then produces a structured summary with clear sections, topic tracking, and action items. Sales teams and global teams get reliable raw material for deal coaching, CRM updates, and follow-ups without heavy cleanup.

Jamie advanced supports Google Meet, Microsoft Teams, and Zoom through secure local or browser-based recording. Transcripts are processed on protected servers, which supports GDPR-compliant workflows and enterprise pricing reviews.

2. Fathom

• Best For: Budget-conscious users who don’t want to hit a free tier ceiling.
• Key Strength: Unlimited recordings and transcriptions on the free plan, with no meeting cap or time limit.
• Price: Completely free core plan. Premium is $16/month per user for individuals. For teams, pricing starts at $15/user/month, increasing to $25/user/month for Business and $35/user/month for Enterprise.

Fathom offers a generous free plan with unlimited meeting transcripts, making it a strong free tool for users who have frequent meetings. It joins calls as a visible bot on Google Meet, Microsoft Teams, and Zoom, then automatically captures audio and produces structured notes. The free version includes real-time transcription, AI summaries, action items, and topic tracking with no minute limits.

The app creates short clips and smart chapters from your meeting recordings, so you can jump to key moments without scrubbing through hours of video. Global teams rely on it for cross-time-zone syncs because it handles multiple meetings per day without extra cost.

Its paid plans add conversation analytics, CRM integrations like Salesforce, and deeper CRM automation for enterprise pricing and GDPR compliant workflows.

3. Otter.ai

• Best For: Teams that need meeting notes to flow directly into existing business tools
• Key Strength: Deep CRM automation across sales, education, and media use cases, plus a bot-free desktop option for anyone who wants a bot free capture.
• Price: Basic: Free. Pro: $8.33/user/month billed annually ($16.99 monthly). Business: $19.99/user/month billed annually ($24 monthly). Enterprise: Custom pricing. 

Otter.ai creates structured meeting notes and can send action items, follow-ups, and key quotes to connected workplace platforms like Slack, Notion, HubSpot, and Salesforce. Its CRM capabilities make it particularly useful for sales teams that want conversation details reflected in customer records and deal workflows.

The platform integrates with Google Meet, Microsoft Teams, and Zoom, while its mobile app supports recording outside virtual meetings and capturing in-person conversations such as lectures, interviews, and voice memos, making it useful beyond standard business meetings.

Additional features include smart chapters, short clips, topic tracking, and conversation analytics. Enterprise plans add administrative controls, security features, and GDPR compliance for organizations handling sensitive information. For teams without a technical setup person, Otter requires little extra setup compared to tools that need custom API work.

4. Fireflies

• Best For: Users on varied meeting platforms who need one tool that reliably joins almost any call.
• Key Strength: Support for Zoom, Google Meet, Microsoft Teams, and 10+ additional platforms.
• Price: Free includes unlimited transcription. Pro costs $10/month per seat, billed annually; Business $19/month per seat; and Enterprise $39/month per seat, all billed annually.

Fireflies is a strong general-purpose meeting capture tool for teams working across different conferencing platforms. Its Fireflies bot can join Zoom, Google Meet, Microsoft Teams, and numerous other services, making cross-platform compatibility its main advantage.

All plans include unlimited transcription across 100+ languages. Storage varies by tier: Free is limited to 400 minutes for the entire team, Pro provides 8,000 minutes per seat, and Business and Enterprise offer unlimited storage.

Its AI features use monthly credits separately from transcription. Free and Pro provide 20 credits, Business provides 30, and Enterprise provides 50 for tools such as AskFred, advanced summaries, and action item extraction. Additional credits can be purchased after the included allowance is used.

Beyond live meetings, Fireflies supports other recording methods. Its Chrome extension can capture meetings without displaying the bot as a participant, while desktop and mobile apps allow users to upload audio and video files directly.

5. Granola

• Best For: Anyone who wants meeting notes without a bot appearing as a participant.
• Key Strength: Turns live scribbles and background audio into structured notes without sending a bot into the meeting.
• Price: Free includes unlimited meeting notes with access to the most recent 30 days. Business costs $14/user/month with unlimited history and integrations. Enterprise starts at $35 per user per month.

Granola is the most distinctive tool in this category. Rather than joining the call as a visible bot, it builds polished notes from the rough scribbles you type live, avoiding the awkward “bot in a client call” problem entirely.

This approach works across Google Meet, Zoom, Microsoft Teams, and Slack Huddles without adding a visible participant to the call. It is particularly useful for client conversations where an automated meeting attendee could feel intrusive.

Granola is available on macOS, Windows, iOS, and Android. Its mobile apps also support in-person conversations, including coffee meetings and walking discussions.

For teams using AI workflows, the MCP connector makes meeting information accessible from connected AI applications. Paid plans also support integrations with Notion, HubSpot, Slack, Attio, and Zapier.

Best for Personal & Flexible Notes

This category covers Reflect and Notion. Reflect delivers fast, private, single-user notes with backlinks, end-to-end encryption, and AI that acts as a thought partner. Meanwhile, Notion expands beyond notes to an all-in-one workspace with databases, wikis, project tracking, and team collaboration, plus AI for drafting and summarizing across the board.

6. Reflect

• Best For: the solo thinker who wants fast daily notes with light AI assistance and nothing to maintain.
• Key Strength: Backlinked, end-to-end encrypted notes with an AI that acts as a thought partner instead of a task manager.
• Price: $10/month, billed annually at roughly $100/year. No permanent free tier, but a 14-day free trial is available.

Reflect is a fast, networked daily-notes app built for one person. The AI assistant acts as a thought partner by transcribing voice notes, generating article outlines from scattered thoughts, listing key takeaways and action items from meeting notes, improving grammar and spelling, and following custom prompts.

The app mirrors the way your mind works by connecting notes through backlinks, forming a searchable graph of ideas. It supports instant capture from Chrome and Safari, syncs Kindle highlights via Readwise, and integrates with Google Calendar and Outlook to track meetings and agendas. Zapier connects Reflect to dozens of other applications without code, and everything syncs in real time across iOS and desktop, online or offline.

Reflect stops at single-user by design. There is no team or shared-workspace model, no CRM integrations, and no Salesforce or HubSpot write-back.

7. Notion

• Best For: Users who want their notes connected to broader organization, databases, project tracking, and shared docs, rather than a standalone notes app.
• Key Strength: Scales from solo daily notes to a full team workspace without switching tools, the flexibility Reflect deliberately doesn’t offer.
• Free Plan Available: Plus at $10/month, Business at $20/month, Enterprise with custom pricing. Notion AI and Custom Agents use additional credits.

Notion is an all-in-one workspace that combines notes, databases, wikis, and project tracking. Its AI tools support drafting, summarizing, and searching information across your workspace. Unlike pure note-taking apps, it treats notes as part of a larger system: you can link entries to tasks, embed live data, and build shared project boards in the same place.

The platform supports personal daily notes, team wikis, and shared project databases without forcing you to switch tools. You can create custom templates, automate workflows, and connect notes to calendars, docs, and roadmaps. Teams can use it for internal meetings, customer records, and deal tracking alongside meeting notes.

8. Best for Teams: Tana

• Best for: Teams that want notes to become actual tracked work, not just a cleaner personal document.
• Key strength: Turns meeting content into filed tickets, drafted docs, and updated records automatically, connected to HubSpot, Jira, Linear, and GitHub.
• Price: The Free plan covers 5 meetings per month with AI transcripts. Pro runs $20/user/month at the early-bird rate, with a botless meeting agent for Zoom, Teams, and Google Meet. Max runs $80/user/month for heavier AI use. Business is custom-priced and adds Single Sign-On (SSO) and audit logs.

Tana runs user-friendly video calls where AI agents work alongside you, capturing decisions and acting on them in real time. It listens to standups, design reviews, customer calls, and sales meetings, then creates the work your team needs, including PRDs, CRM updates, issue reports, client briefs, and follow-ups. 

The platform connects meetings with docs, projects, tasks, chats, decisions, contacts, and other work so information stays connected. It also integrates with tools including Slack, GitHub, HubSpot, Linear, Jira, Google Calendar, and Outlook. 

Tana lets teams customize agents and skills around their workflows. Agents can prepare agendas, surface previous decisions, draft content, update objectives and key results (OKRs), file issues, and organize follow-ups. For teams that spend significant time in meetings, the main advantage is turning conversations into completed work rather than leaving people with another list of notes to process.

9. Best for Students and Research: NotebookLM

• Best For: Students and researchers organizing and querying their own source material, not capturing live conversation.
• Key Strength: Grounds every answer in documents you upload, rather than generating from general knowledge alone.
• Price: The Free plan covers 100 notebooks, 50 sources per notebook, and 50 daily AI chats. Plus is bundled into Google AI Plus at $4.99/month. Pro is bundled into Google AI Pro at $19.99/month. Ultra is bundled into Google AI Ultra at $99.99/month.

NotebookLM is built specifically around turning your uploaded documents into an interactive knowledge base. You upload lecture slides, research papers, textbook chapters, or any PDFs and text files, then ask questions that get answered using only that source material. Every response cites the exact passages it drew from, so you can verify claims and trace ideas back to the original context.

However, NotebookLM is not a meeting notetaker or personal notes app. It does not record meetings, transcribe calls, or capture live conversation. The tool excels at synthesizing multiple documents at once. You can upload a week’s worth of readings, then ask for summaries, comparisons, or AI chat queries that cross-reference all of them. 

It generates study guides, outlines, and key takeaways lists grounded in your files, not in general knowledge. Researchers use it to map arguments across papers; students use it to prepare for exams by querying their course materials, making NotebookLM one of the best AI tools for students.

10. Best AI Voice Recorder Hardware: Plaud Note Pro

• Best for: Professionals who want a dedicated recording device separate from their phone or laptop, particularly for in-person meetings or interviews.
• Key strength: A standalone hardware recorder paired with Plaud Intelligence, delivering high transcription accuracy without an app running in the background during a meeting.
• Price: The device costs $189 and is a one-time purchase. Every device includes the free Starter plan, which offers 300 transcription minutes per month. Team plans run $20/user/month, billed annually, or $28/user/month, billed monthly.

Plaud NotePro is distinct from every other AI tool on this list; it is the only AI notetaker that has a dedicated physical AI voice recorder device paired with an app, rather than pure software. The device records in-person conversations, lectures, and interviews with high-fidelity audio, then syncs to its companion app for AI transcription and summary generation.

The companion app produces structured transcripts, action items, and concise summaries optimized for quick review. Users can tag recordings, search across sessions, and export notes to email or cloud storage. Sales teams, consultants, and journalists use it for client meetings, field interviews, and on-the-go capture where phone recordings feel informal or unreliable.

Plaud’s hardware focuses on battery life, pocketable design, and one-button operation, making it practical for daily carry. The AI layer handles speaker diarization, topic tracking, and smart highlights without requiring manual setup. If you prioritize a dedicated device for in-person conversations, Plaud NotePro fills that niche.

How to Choose the Right AI Note-Taking App

Choosing the right AI note-taking app depends on your primary workflow, whether you need accurate client call transcripts, unlimited free recording, CRM integrations, or a dedicated hardware recorder. 

For recording client or business calls where accuracy and privacy matter most, Jamie might be the best option. However, if you want unlimited free recording with no minute cap, Fathom is the clear choice. 

Teams that need CRM or workspace integration should lean on Otter.ai. If your meetings span multiple platforms such as Zoom, Teams, Meet, and Webex, Fireflies offers the broadest bot compatibility.

Mac users who want a bot-free, natural note-taking feel during calls will prefer Granola. For personal daily journaling and connected thinking, Reflect delivers fast, private notes. 

If you manage team knowledge and want notes to auto-create follow-ups and tasks, Tana turns conversations into tracked work. Students and researchers working from their own documents should use NotebookLM to query and summarize source material.

All the above tools are software products, but if you want a dedicated hardware recorder for in-person meetings and interviews, Plaud NotePro provides a standalone device with AI summaries.

Final Verdict

The right AI note-taking app depends on where the information needs to go. Jamie earns its accuracy claim with a real head-to-head test, which matters when a transcript needs to hold up later. Otter and Tana push further, filing notes straight into a CRM or tracker instead of leaving them sitting in an app, while Notion keeps everything, including notes, meetings, and projects, inside one workspace. 

Some other apps offer similar core features at a lower price, but fall short when it comes to connecting notes to the rest of your workflow. So, start with what you actually need the note to do. Also, don’t forget to test the free tier before paying for anything.

FAQ

What is the most accurate AI note taker?

Jamie rates highest for English transcription accuracy in most 2026 testing, with Fathom and Fireflies close behind on clean, single-language audio.

Which AI is best for taking notes?

There’s no single best AI meeting assistant. Granola and Jamie lead for bot-free client calls, Fathom for unlimited free recording, Fireflies for CRM sync, and Notion or NotebookLM for combining notes with broader project or research work.

Are AI note-taking apps private and secure?

It depends on the app. Some keep meeting data inside your existing Microsoft or Google environment and never use it for AI training, while others store recordings on external servers and may train models on them unless you opt out. For any app you choose, check its data retention and training defaults before using it for sensitive meetings.

Can ChatGPT take notes?

Not on its own. ChatGPT doesn’t join meetings, record audio, or transcribe live conversation. It can help after the meeting, summarizing or restructuring notes and transcripts you paste in, but it isn’t a standalone note-taking or meeting-capture tool the way Jamie or Otter are.

The post 10 Best AI Note-Taking Apps in 2026: Top Picks by Use Case appeared first on Memeburn.

My dog Rosie was given months to live. Chemo and immunotherapy failed

I used chatgpt + computational genomics to design a personalised mRNA cancer vaccine for her tumour. Several of her tumours shrank

Today we launch Gamgee (YC S26): personalised mRNA cancer vaccines for dogs pic.twitter.com/wMAmNXXgQd

— Paul S. Conyngham (@paul_conyngham) August 11, 2026

That experiment is now a company. Gamgee launched as part of Y Combinator’s Summer 2026 batch, offering personalized mRNA cancer vaccines for dogs. The startup is running clinical trials in Australia and accepting cases from pet owners globally. Here’s how the science works and what the medical community thinks about it.

How ChatGPT Helped Design a Cancer Vaccine

The process behind Rosie’s vaccine wasn’t as simple as asking ChatGPT to cure cancer. It is a multi-step scientific workflow that Conyngham developed, combining AI tools with established genomics techniques.

The first step is sequencing. Scientists take samples from both the tumor and healthy tissue, then sequence the DNA of each. Comparing the two genomes reveals the specific mutations driving that individual cancer — the genetic changes that make cancer cells different from normal cells.

ChatGPT’s role comes in the analysis phase. Conyngham used the AI to help identify which mutations are most likely to be recognized by the immune system. Not every mutation makes a good vaccine target. The AI helped sort through the genomic data to find mutations that would produce proteins the immune system could learn to attack.

A lot of people have been asking if this can be done for their dogs and for people. I’m speaking with everyone involved to see what is possible here.

If you would like to be involved, please complete the following Google form:https://t.co/qs9WwDNgBH pic.twitter.com/ANvxF9LX47

— Paul S. Conyngham (@paul_conyngham) March 14, 2026

The final step is vaccine design. Based on the identified targets, scientists at UNSW’s RNA Institute synthesized an mRNA sequence that teaches the dog’s immune system to recognize and destroy cells carrying those specific mutations. The mRNA approach — the same technology behind COVID-19 vaccines from Moderna and BioNTech — instructs cells to produce small protein fragments that trigger an immune response without causing disease.

Noted that Rosie’s vaccine is believed to be the first fully computationally designed mRNA cancer vaccine ever delivered to a dog. The “fully computationally designed” distinction matters — it means AI was involved throughout the design pipeline, not just at one step.

Sam Altman Took Notice

The story gained significant attention in the AI community. OpenAI CEO Sam Altman met with Conyngham in March after the initial results went viral, saying the story had him thinking “this should be a company.” That meeting reportedly helped catalyze the transition from personal project to startup.

The coolest meeting I had this week with was Paul, who used ChatGPT and other LLMs to create an mRNA vaccine protocol to save his dog Rosie. It is amazing story.

“The chat bots empowered me as an individual to act with the power of a research institute – planning, education,… https://t.co/akgD2Wz7d0

— Sam Altman (@sama) March 27, 2026

Y Combinator’s acceptance validates the commercial potential. The accelerator’s Summer 2026 batch includes Gamgee alongside dozens of other AI-focused startups, but few combine AI with such a direct biological application. The company’s positioning — personalized cancer treatment for pets — sits at the intersection of veterinary medicine, AI, and mRNA technology.

Personalized mRNA cancer vaccines for humans are already in clinical trials at companies like Moderna and BioNTech. ChatGPT’s growing role in scientific research has been well documented throughout 2026. Gamgee essentially applies both trends to veterinary oncology, where regulatory barriers are lower and treatment timelines are faster.

What Oncologists Say About the Approach

Not everyone shares the optimism. The Conversation published an analysis from an oncologist urging caution about drawing broad conclusions from a single case.

The core concern is sample size. One dog responding positively to a treatment doesn’t prove the approach works reliably. Cancer is heterogeneous — different tumor types, different mutation profiles, different immune responses. What worked for Rosie’s specific cancer may not translate to other dogs with different tumor genetics.

There’s also the question of attribution. Tumors can sometimes shrink temporarily for reasons unrelated to treatment — a phenomenon oncologists call spontaneous regression. Without a controlled study comparing vaccinated dogs to unvaccinated ones with similar cancers, it’s difficult to confirm that the mRNA vaccine caused the tumor shrinkage.

The oncologist also flagged concerns about using AI for vaccine target selection without extensive validation. AI models can identify patterns in genomic data, but they can also produce false positives — mutations that look like good targets but don’t actually trigger an effective immune response in practice.

These are legitimate scientific concerns, not dismissals. The clinical trials Gamgee is now running in Australia should address them directly. Controlled studies with multiple dogs across different cancer types will determine whether the approach is broadly effective or a fortunate one-off.

How Gamgee’s Process Works for Pet Owners

For dog owners interested in Gamgee’s service, the process starts with a veterinary referral. The dog’s tumor and healthy tissue are sampled and sent for genomic sequencing. Gamgee’s platform — powered by computational genomics and AI analysis — identifies the optimal vaccine targets.

The mRNA vaccine is then synthesized specifically for that individual dog’s cancer mutations. No two vaccines are the same, because no two cancers have identical mutation profiles. After synthesis, the vaccine is administered by a veterinarian.

(Conyngham and his dog Rosie)

The company is running formal clinical trials in Australia while also accepting individual cases globally. The global acceptance suggests Gamgee is using a compassionate-use framework for dogs that have exhausted standard treatment options — similar to how experimental human treatments become available to terminal patients before formal approval.

Pricing and availability details haven’t been publicly disclosed. Personalized mRNA vaccine production is expensive — each vaccine requires individual sequencing, analysis, and synthesis. The AI funding landscape in 2026 suggests Gamgee likely has runway to subsidize early cases while building clinical evidence.

Why Veterinary AI Matters Beyond Pets

Gamgee’s approach has implications beyond veterinary medicine. If personalized mRNA cancer vaccines prove effective in dogs across multiple cancer types, the data could accelerate human clinical trials. Dogs develop many of the same cancers humans do — lymphoma, melanoma, osteosarcoma — and their shorter lifespans mean treatment outcomes become visible faster.

This “one health” approach — using veterinary medicine to inform human medicine — has precedent. Several human cancer treatments were first tested in dogs. The regulatory path is also simpler: veterinary treatments face fewer approval hurdles than human drugs, allowing faster iteration on vaccine design and delivery protocols.

Whether Gamgee succeeds or fails, the story illustrates something meaningful about AI’s role in 2026. A tech entrepreneur with no formal medical training used publicly available AI tools and academic collaborators to develop a novel cancer treatment. The barriers to biological innovation are dropping, and that’s simultaneously exciting and worth approaching with scientific rigor.

FAQs

What is Gamgee and how does it use ChatGPT? 

Gamgee is a Y Combinator-backed startup that creates personalized mRNA cancer vaccines for dogs. Founder Paul Conyngham used ChatGPT and computational genomics to help identify cancer-driving mutations and design vaccine targets for his dog Rosie.

Did the mRNA vaccine actually cure the dog’s cancer? 

Several of Rosie’s tumors shrank after receiving the vaccine, but oncologists urge caution about concluding it’s a cure from one case. Clinical trials are underway to test the approach across multiple dogs and cancer types.

How can I get Gamgee’s vaccine for my dog? 

Gamgee runs clinical trials in Australia and accepts cases globally. Contact the company through their website with a veterinary referral. The service is typically for dogs that have exhausted standard treatment options.

Is Gamgee backed by Y Combinator? 

Yes. Gamgee was accepted into Y Combinator’s Summer 2026 batch. OpenAI CEO Sam Altman also met with founder Paul Conyngham after the story went viral.

Can this mRNA vaccine approach work for human cancer? 

Personalized mRNA cancer vaccines for humans are already in clinical trials at companies like Moderna and BioNTech. Gamgee’s veterinary data could inform human research since dogs develop many of the same cancers humans do.

The post A Dying Dog, ChatGPT, and the mRNA Vaccine Startup That Came Out of It appeared first on Memeburn.

Why Apple’s Global AI Plan Failed in China 

Apple Intelligence was built as a single global system, mixing Apple’s own models with outside partners. That approach hits a wall in China. AI tools there need government approval, strict content rules, and help from local companies. Neither ChatGPT nor Claude can be used there.

So Apple built a separate path instead:

• Its own AI model, built for Chinese users.
• Alibaba’s Qwen, built into iOS, iPadOS, macOS and visionOS.
• A partnership with Baidu for other features.
• Following China’s approval and content rules from the start.

Three people close to the matter told Reuters that Apple built the model with Alibaba’s help. Neither company has said how the work was split, or whether this new model will replace Qwen or run alongside it. Reuters described the approach as a “dual-track strategy,” letting Apple lean on local partners now while building more of its own technology over time.

Here’s the bigger deal: this reportedly makes Apple the first foreign company allowed to build and run its own AI model in China. Beijing almost never lets outsiders that close to its technology.

Why Apple Still Needs Alibaba and Baidu 

Even with its own model in the works, Apple isn’t cutting its local partners loose. Alibaba confirmed in July 2026 that Qwen would be built into Apple Intelligence across iPhone, iPad, Mac and Vision Pro. It powers text and image features behind familiar tools like Siri and Writing Tools. 

Baidu is involved too. A company spokesperson confirmed the month that it’s helping build features for Chinese iPhone users. That reportedly includes search. Neither company has shared the full details. But together they point to the same conclusion: Apple’s China AI relies on several partners, not just one outside company.

Apple’s China AI Launch Is Not Ready Yet 

China’s internet regulator approved Apple’s AI service on July 15, 2026. That’s roughly 22 months after Apple Intelligence launched elsewhere. The gap shows how carefully China checks foreign AI. Even after that approval, the details keep changing. On August 8, 2026, Apple published a Chinese-language guide for eligible Mac users. It explained how to connect Qwen to Siri and Writing Tools on macOS 26.6 and later. Apple then quietly took it down without explanation. The pattern is clear. Apple’s China AI launch isn’t one single event; it’s a slow, changing process.

Why Apple Had to Change Its AI Plan 

China is Apple’s toughest smartphone market. Rivals like Huawei, Xiaomi, Oppo and Vivo have already been selling phones with approved local AI for months. That gap kept widening every month Apple Intelligence stayed unavailable. Competition explains the urgency, but the deeper story is about control. Apple still owns the hardware and the software, and the way the phone looks and feels. Yet the AI running underneath is no longer entirely its own in China.

Apple didn’t team up with two Chinese tech giants and build a separate model because it wanted to. It did so because China wouldn’t let its global AI plan in as is. This trade-off could become how Apple works in any country with its own rules. The real test comes when Apple Intelligence launches in China in the coming months. 

FAQs

What AI model does Apple use in China?

Apple is building Alibaba’s Qwen into Apple Intelligence in China. It’s also building its own China-only AI model with Alibaba’s help, according to Reuters.

Is Apple’s new model replacing Qwen?

That hasn’t been confirmed. Reports don’t say whether Apple’s model will replace Qwen or run alongside it once Apple Intelligence launches in China.

When was Apple Intelligence approved in China?

China’s internet regulator approved the service on July 15, 2026, about 22 months after Apple Intelligence launched in other markets.

What role does Baidu play?

Baidu confirmed in July 2026 that it’s helping build features for Chinese iPhone users, reportedly including search. The full details haven’t been shared.

Can Chinese Mac users already use Qwen with Siri?

Apple published a guide on August 8, 2026. It explained how eligible Macs on macOS 26.6 or later could connect Qwen to Siri and Writing Tools. Apple has since removed the guide without giving a reason.

Will China’s version of Apple Intelligence match the global one?

Probably not exactly. It’s expected to rely on local partners and a locally built model. That model is made to meet Chinese rules, not to copy the international version.

The post Apple Is Building a China AI Model With Alibaba’s Help appeared first on Memeburn.

Dynamic ANC Fixes the Biggest Earbuds Problem

Active noise cancellation on most earbuds works well in a controlled environment. The moment you start moving — chewing, talking, adjusting the fit — the seal shifts slightly. That creates gaps in noise cancellation. Most earbuds don’t adapt; they just let the noise leak through until the seal resets.

Dynamic ANC changes that. According to Google’s blog post, the Pixel Buds Pro 2 will continuously monitor the seal and adjust noise cancellation to compensate. Whether you’re working out, eating, or just shifting in your seat, the system detects seal changes and recalibrates automatically.

Dynamic ANC is exclusive to the Pixel Buds Pro 2. The more affordable Pixel Buds 2a will receive the other software updates but not this feature. The Tensor A1 chip is likely the differentiator. Real-time seal monitoring and ANC recalibration need computational headroom that the 2a’s simpler chip can’t provide.

This is the update that matters most for daily use. ANC inconsistency during physical activity is the top complaint we see across all premium earbuds. If Dynamic ANC works as described, it solves a problem that Apple’s AirPods Pro 2 and Sony’s WF-1000XM6 haven’t cracked either.

Gemini Voice Controls Replace the Settings App

The second feature brings Gemini directly into earbud management. Pixel Buds Pro 2 users can now adjust settings by voice through Gemini. No need to open the Pixel Buds app.

Want to switch between ANC and transparency mode? Ask Gemini. Need to adjust the equalizer? Tell Gemini. Want to change the touch control mapping? Voice command. No more pulling out your phone, opening the app, navigating to settings, and tapping through menus. One voice request handles it.

This builds on Google’s broader push to make Gemini the default interface across all Pixel hardware. The Pixel 11’s HiLight LED already serves as a visual indicator for Gemini interactions. Adding voice-controlled earbud settings extends that ecosystem to wearables.

The practical question is accuracy. Voice control only works if Gemini correctly reads vague requests. Does “make it louder in noisy places” mean ANC adjustment or volume change? Google hasn’t detailed how nuanced the understanding is. The Tensor A1 chip handles on-device Gemini processing on the Buds Pro 2.

Pixel Watch Sleep Sync Turns Your Earbuds Into Sleep Mode

Fall asleep wearing Pixel Buds Pro 2 while listening to podcasts, white noise, or music? The new Pixel Watch sleep sync detects when you drift off and takes three actions. It pauses whatever audio is playing. It disables touch controls so accidental ear bumps don’t restart playback. And it silences notifications so incoming alerts don’t wake you.

This requires a Pixel Watch (any generation) paired alongside the Buds Pro 2. The watch uses heart rate monitoring and movement tracking to detect sleep. It then sends the signal to the earbuds.

This is a genuinely useful cross-device feature that competitors haven’t replicated. Apple’s AirPods detect when you remove them. Samsung’s Galaxy Buds link with Galaxy Watch for fitness tracking. But automatic sleep-triggered audio management across watch and earbuds is new territory.

The limitation is obvious: you need both a Pixel Watch and Pixel Buds Pro 2. Google is building an ecosystem play that rewards users who buy multiple Pixel products. If you’re using a Samsung watch or an Apple Watch with Pixel Buds, sleep sync won’t work.

Live Translate Gets Tap-to-Trigger for 70+ Languages

Live Translate on the Pixel Buds Pro 2 already provided real-time translation through the earbuds. The update adds a tap-to-trigger mode. Tapping the earbuds activates listening mode for translation. It supports over 70 languages in near real time without touching your phone.

The workflow becomes simpler: tap the earbud, speak or listen to someone speaking a foreign language, and hear the translation through the buds. Previously, triggering translation required opening the Google Translate app or using a voice command. Tap-to-trigger removes that friction.

For travelers and multilingual environments, this is a practical upgrade. Translation happens in near real time using on-device processing for supported languages. That means it works without a reliable internet connection for common language pairs.

Olive Color and Pricing Details

The new Olive colorway joins the existing Porcelain, Hazel, Peony, and Wintergreen options. Olive replaces Moonstone, so the total number of color options stays the same. The Olive finish matches the Pixel 11 and Pixel Watch 5, creating a unified look across Google’s 2026 hardware.

Pricing stays at $229 — no increase from the original launch price. Google ran a limited promotional discount, but the standard retail price remains unchanged. For comparison, the Xiaomi Buds 6 launched globally at roughly half that price, though without the Tensor A1 chip’s AI processing capabilities.

We should note that the software features — Dynamic ANC, Gemini controls, sleep sync, and enhanced Live Translate — arrive as a free update in September for all existing Pixel Buds Pro 2 owners regardless of color. You don’t need to buy the Olive version to get the new features.

FAQs

What new features do Pixel Buds Pro 2 get in 2026? 

The September 2026 update adds Dynamic ANC (real-time seal adjustment), Gemini voice controls for settings, Pixel Watch sleep sync, and tap-to-trigger Live Translate in 70+ languages.

What is Dynamic ANC on Pixel Buds Pro 2? 

Dynamic ANC continuously monitors the acoustic seal between the earbud and your ear. When the seal shifts during movement or chewing, it automatically recalibrates noise cancellation to maintain consistent performance.

Do I need to buy new Pixel Buds Pro 2 for the update? 

No. All software features roll out as a free update in September 2026 to existing Pixel Buds Pro 2 owners. The Olive color is the only thing exclusive to new purchases.

How does Pixel Watch sleep sync work with Pixel Buds? 

A paired Pixel Watch detects when you fall asleep using heart rate and movement sensors. It then signals the Buds Pro 2 to pause audio, disable touch controls, and silence notifications automatically.

How much do Pixel Buds Pro 2 cost in 2026? 

The Pixel Buds Pro 2 retail at $229 for all colors, including the new Olive option. Google offered a limited promotional discount alongside the Pixel 11 launch, but standard pricing remains unchanged.

The post Google’s Pixel Buds Pro 2 Just Got Smarter and the New Color Is the Least Interesting Part appeared first on Memeburn.