Google’s push to make Gemini the smartest assistant on Android has run into a hardware wall, and the fallout is now the top story in phone news. Multiple outlets, led by Android Authority, confirmed this week that Google’s new Gemini Intelligence layer only runs on a small handful of 2026 flagships, locking out most of the Android install base, including phones that are barely a year old. If you want the full set of Gemini’s smartest features, you need a phone built around Gemini Nano v3, at least 12GB of RAM, and a current-generation flagship chip. That currently means the Pixel 10 family, the Samsung Galaxy S26 series, and the OnePlus 15, and almost nothing else.
The story matters because Google has spent years telling Pixel owners that long software support means their phones stay current. Android Authority’s own reporting undercuts that promise directly: the Pixel 9 series, released just one generation back, is “stuck on Nano v2” and cannot run Gemini Intelligence, according to Google’s own ML Kit support documentation cited by the outlet. For a company that sells seven years of OS updates as a selling point, tying its best AI features to a single 2026 chip generation is a hard pivot, and it is reshaping how people shop for phones this fall.
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What Gemini Intelligence actually requires
Gemini Intelligence is Google’s umbrella name for a wave of proactive, agentic AI features that Google detailed on its official Gemini Intelligence pages and rolled out across 2026 on qualifying Android flagships. According to Google’s own developer documentation, updated as recently as May 2026 and referenced across multiple outlets including Android Authority, 9to5Google, which confirmed the AI Core and Gemini Nano v3+ dependency that same month, and Android Headlines, which independently reported the same Gemini Nano v3+ eligibility floor in its own May 2026 coverage, the requirements are strict: the device needs 12GB of RAM minimum, a flagship-grade chipset, and support for AI Core paired with Gemini Nano v3 or higher. TechRadar’s own May 2026 coverage adds another wrinkle, reporting that qualifying devices must also be eligible for five major Android version upgrades, a support commitment well beyond what most flagships outside the Pixel and Galaxy lines currently promise. That combination is a much narrower gate than typical Android feature rollouts, which usually key off OS version alone.
The RAM requirement is not just a spec-sheet minimum. A technical breakdown published in August 2026 notes that Tensor G5-based phones reserve roughly 3GB of system memory permanently for “always-resident AI models” that serve the on-device neural processing unit. That means a 12GB phone effectively has closer to 9GB free for apps, games, and background processes once Gemini Nano v3 is running. Google’s argument, echoed in its own blog posts, is that keeping the AI model resident in memory is what allows near-instant, on-device responses instead of waiting on a cloud round-trip. Critics see it differently: a deliberate tax on older or cheaper phones that keeps the newest AI features exclusive to hardware Google and its partners just started selling.
The short list of qualifying phones
Updated October 2026. Google’s official Gemini Intelligence page still gates the full feature set behind Gemini Nano v3 or newer, at least 12GB of RAM, and a qualified flagship SoC. As of this update the reported Nano v3 device list has widened beyond the launch flagships to include: Google Pixel 10, 10 Pro, 10 Pro XL and 10 Pro Fold, plus the newly listed Pixel 11, which Samsung/Google documentation confirms as compatible as of October 2026; Samsung Galaxy S26, S26+ and S26 Ultra, the three models Samsung confirmed for support back in May 2026, alongside the Galaxy Z Fold8, Z Fold8 Ultra and Z Flip8, all three of which Samsung and Google now list as compatible as of October 2026; OnePlus 15 and 15R; OPPO Find X9, Find X9 Pro, Find X8 and Find X8 Pro; and Xiaomi 17, 17 Ultra and the 15 series. Notably, several 2025 flagships remain excluded because they ship Gemini Nano v2 rather than v3, regardless of RAM or chipset: the Pixel 9 series, Samsung Galaxy Z Fold 7, OnePlus 13 and Honor Magic 7 Pro. The cutoff is the Nano model version, not memory alone.
As of late August 2026, the roster of phones that actually ship with Gemini Nano v3 support is small enough to list in full. Android Authority’s mid-range chip coverage names three families explicitly: the Galaxy S26 series, the Google Pixel 10 range, and the OnePlus 15. Google’s own developer notes add one more exception worth flagging: the Oppo Find X9 series, called out as an “odd one out” because it beat most of the 2026 flagship pack to Nano v3 support despite launching on 2025-era timing.
| Phone | Chip | RAM | Gemini Nano v3 support |
|---|---|---|---|
| Pixel 10 (base) | Google Tensor G5 | 12GB LPDDR5X | Yes |
| Pixel 10 Pro / Pro XL / Pro Fold | Google Tensor G5 | 16GB LPDDR5X | Yes |
| Galaxy S26 / S26+ / S26 Ultra | Flagship Snapdragon/Exynos tier | 12GB+ | Yes |
| OnePlus 15 | Flagship Snapdragon tier | 12GB+ | Yes |
| Oppo Find X9 series | Flagship tier | 12GB+ | Yes (early exception) |
| Pixel 9 series | Google Tensor G4 | Up to 16GB | No, capped at Nano v2 |
| Galaxy S25 Ultra | Flagship Snapdragon tier | 12GB | No, capped at Nano v2 |
| Galaxy Z Fold 7 | Flagship Snapdragon tier | 12GB | No |
Notice what is missing from the “yes” column: the Galaxy S25 Ultra, a phone Samsung was still selling as its top-tier flagship earlier this year, does not qualify, despite having 12GB of RAM and a flagship chip of its own. Android Authority’s reporting is explicit on this point, noting that the S25 Ultra is excluded specifically because it does not run Gemini Nano v3, not because it lacks RAM or processing power. Google’s cutoff is tied to the on-device model version each chip generation was validated against, not to a phone’s raw spec sheet.
Pixel 10: the chip built around Gemini Nano
Google positions the Pixel 10 lineup, launched in August 2025 and still Google’s current flagship family as of this month, as the reference design for Gemini Intelligence. All Pixel 10 models run on the Tensor G5, a 3nm chip built on TSMC’s process and co-designed with Google DeepMind. Google co-designed Tensor G5 with DeepMind to run the Gemini Nano model on-device through Android’s AICore layer, pairing a more capable on-device AI engine with faster CPU performance than the previous Tensor G4. Google’s published requirement names a “qualified flagship SoC” rather than a single mandated chipset.
The base Pixel 10 ships with 12GB of RAM and starts at $799, while the Pixel 10 Pro, Pro XL, and Pro Fold step up to 16GB of RAM and up to 1TB of storage. For a closer look at how the Pixel 10 Pro stacks up against Apple’s current flagship, see our Pixel 10 Pro vs iPhone 17 Pro comparison. Google says the on-device stack unlocks more than 20 generative AI experiences that run without a network call, including Magic Cue, a context-aware assistant feature; Camera Coach; and real-time 10-language Voice Translate. Those features depend on Gemini Nano v3 being resident in memory, which is exactly the requirement that keeps them off the Pixel 9 and every earlier Pixel generation.
Galaxy S26 and the Samsung side of the story
Samsung’s Galaxy S26 series is the other half of what Google calls the “first wave” of Gemini Intelligence hardware. Samsung launched the S26 line in February 2026 running Android 16 with One UI 8.5 on top, and Google’s official Gemini Intelligence documentation lists the Galaxy S26 and Pixel 10 series together in the first wave of supported hardware, treating the two lines as parallel launch partners rather than a Google-exclusive rollout. SamMobile’s May 2026 reporting adds that Gemini Intelligence-qualifying Galaxy devices carry Samsung’s six-year security update commitment, with Google’s own May 2026 documentation specifying those patches must land on a quarterly cadence rather than Samsung’s older monthly schedule, tying the AI feature set to the same long-support tier Samsung uses to market its flagships. Where the S26 lands against Samsung’s own former flagship is covered in our Galaxy S26 Ultra vs iPhone 17 Pro Max comparison. That is a notable shift from earlier Android AI pushes, which tended to land on Pixel hardware months ahead of Samsung.
The practical effect is that Samsung’s most recent former flagship, the Galaxy S25 Ultra, becomes a cautionary tale for buyers who assumed last year’s top-of-the-line phone would keep pace with Google’s AI roadmap. It won’t, at least not for Gemini Intelligence’s flagship feature set. Samsung has not published a public timeline for retrofitting Nano v3 support to older Galaxy hardware, and given that the block is tied to on-device model validation rather than a software toggle, a future software update patching it in looks unlikely.
Why Google drew the line at Nano v3
Google’s stated rationale, repeated across its own blog posts and product pages, is that Gemini Intelligence is meant for “the most advanced devices” with “premium hardware.” The company frames the RAM and chip requirements as necessary for running a genuinely capable AI model on-device rather than shipping a stripped-down version that would disappoint users. Keeping Gemini Nano permanently resident in memory, instead of loading it on demand, is what makes features like Magic Cue and Camera Coach feel instant rather than laggy.
That explanation only goes so far with critics. Android Authority’s analysis argues that Gemini Intelligence “exposes the problem with Google’s 7-year Pixel update promise,” pointing out that even developers cannot access Nano v3, or the newer Nano v4 models Google has started referencing, on hardware barely two years old. 9to5Google first reported Gemini Nano 4 device support in August 2026, naming just seven qualifying models, a list even shorter than the Nano v3 rollout it is meant to succeed. A long support window that covers security patches and OS versions means little to a user who bought a phone expecting to stay current on AI capability and finds themselves locked out within twelve months of a new Gemini feature wave.
The fragmentation problem, by the numbers
| Requirement | Reported detail | Effect on eligible devices |
|---|---|---|
| Minimum RAM | 12GB | Excludes most sub-flagship and 2024-era phones |
| On-device model floor | Gemini Nano v3 or higher | Excludes Pixel 9, Galaxy S25 Ultra, Galaxy Z Fold 7 |
| Chip tier | “Flagship chip” (Tensor G5 or equivalent) | Excludes nearly all mid-range Android chipsets |
| RAM reserved for AI residency | ~3GB on Tensor G5 devices | Cuts usable RAM on 12GB phones to roughly 9GB |
| Qualifying phone families (Aug. 2026) | Pixel 10, Galaxy S26, OnePlus 15, Oppo Find X9 | A small fraction of the active Android install base |
Google has signaled it wants to widen that list. Android Authority reported in May 2026, with the story updated as recently as July, on a new mid-range chip described as “mostly identical to the Dimensity 8500” but built with Gemini Nano v3 support baked in. The goal, per that reporting, is to bring Gemini Intelligence to non-flagship Android phones from OEMs like Xiaomi and Oppo. As of the most recent coverage, that chip has not yet shipped in a named consumer device, so the near-term reality remains a short list of expensive 2026 flagships.
Historical context: how Android AI exclusivity has evolved
This is not the first time Google has gated a headline AI feature behind specific silicon. Earlier Gemini Nano releases were themselves tied to Tensor chips going back to the Pixel 8 generation, and Google’s Circle to Search and some Magic Editor features arrived on Samsung and Pixel flagships before spreading to the rest of the lineup. What is different this time is the scale of exclusion. Past AI rollouts eventually trickled down to two- or three-year-old hardware within a software update cycle. Gemini Intelligence’s dependency on a specific on-device model version, rather than just an OS release, makes that kind of backport far less likely, because the model itself has to be validated against the chip’s neural processing hardware rather than distributed as a generic APK update.
Apple has faced a similar, if less severe, version of this dynamic with Apple Intelligence, which initially required an iPhone 15 Pro or newer due to RAM and Neural Engine requirements before expanding to the standard iPhone 16 lineup. The difference is that Apple controls a much smaller number of device variants than Android’s fragmented OEM ecosystem, making its rollout easier to manage even with hardware gating in place. For how the assistants themselves compare once you clear the hardware bar, see our ChatGPT vs Gemini vs Claude Pro breakdown.
Competitive comparison: Gemini Intelligence vs. Apple Intelligence vs. Galaxy AI
| Platform | Minimum hardware gate | On-device model dependency | Rollout breadth (as reported) |
|---|---|---|---|
| Google Gemini Intelligence | 12GB RAM, flagship chip | Gemini Nano v3+, validated per chip | Pixel 10, Galaxy S26, OnePlus 15, Oppo Find X9 |
| Apple Intelligence | A17 Pro / M-series or newer | Apple’s on-device foundation model | iPhone 15 Pro and newer, expanded to iPhone 16 base |
| Samsung Galaxy AI (pre-Gemini Intelligence tier) | Varies by feature, often cloud-assisted | Mix of on-device and Google cloud models | Broader, spans multiple Galaxy generations |
The comparison underscores why the Gemini Intelligence story has resonated: Samsung’s earlier Galaxy AI features, many of which leaned on cloud processing rather than a fully resident on-device model, reached a much wider range of hardware. Gemini Intelligence’s insistence on keeping Nano v3 permanently loaded in memory is a deliberate trade-off toward speed and privacy at the cost of reach, and it is a trade-off Google is making unilaterally across both its own Pixel line and its partnership with Samsung.
Market impact: what this means for phone sales
For carriers and retailers, a hardware-gated AI feature set is a marketing gift. the reality that Google’s smartest AI now requires current-generation hardware is a much easier sell than an abstract spec bump, and reporting from Forbes and other outlets has already framed the story that way, with Forbes contributor coverage titled around the idea that this Android upgrade is a genuine reason to buy new hardware in 2026 rather than wait for a discount on last year’s flagship.
For Google and Samsung, the near-term effect should be a modest tailwind on flagship upgrade rates heading into the holiday quarter, particularly among buyers who track AI features closely. The risk sits with everyone else: owners of a Galaxy S25 Ultra or Pixel 9 Pro who paid flagship prices within the last twelve to eighteen months and now find themselves permanently excluded from the features Google is using to market its current lineup. That gap could dent trust in Google’s long-support pitch and give ammunition to analysts who already argue Android’s AI rollout is too fragmented to compete cleanly with Apple’s tighter hardware-software loop.
Developer ecosystem concerns
The fragmentation cuts both ways for developers building on Gemini Nano. Android Authority’s coverage notes that even developers cannot access Nano v3, or the newer Nano v4 models referenced in Google’s most recent documentation, on hardware just two years old. That narrows the practical addressable market for any app that wants to build around on-device Gemini features, since a developer targeting Nano v3 today is effectively building for Pixel 10, Galaxy S26, and OnePlus 15 owners only, a tiny slice of the roughly 3 billion active Android devices Google has historically cited for its platform.
That is a meaningfully different calculus than targeting a minimum Android OS version, which developers have done for over a decade with predictable, broadening reach each year. A model-version dependency resets with every new chip generation, which means the addressable base for Nano-dependent features could stay narrow indefinitely unless Google’s promised mid-range chip effort actually ships in volume. Developers who want to build against Gemini’s cloud API instead of the on-device model can sidestep the hardware gate entirely; see our Gemini API tutorial for that setup.
What happens next: rollout beyond phones
Google has said Gemini Intelligence features will expand beyond phones “later this year” to watches, cars, glasses, and laptops, according to Google’s own blog post on the announcement. No specific hardware requirements for those categories have been published yet, but given the phone rollout’s dependency on RAM and a validated Nano v3 chip, it is reasonable to expect similarly tight hardware gates on wearables and in-car systems, categories that typically carry even less RAM headroom than a flagship phone.
5 predictions for the next 12 months
- Google’s promised Nano v3-capable mid-range chip, described as similar to a Dimensity 8500 derivative, will likely appear in at least one named Xiaomi or Oppo device before mid-2027, widening the qualifying list beyond four families.
- Samsung’s Galaxy Z Fold 8 and Z Flip 8, expected around July 2026 per earlier reporting, are strong candidates to carry Gemini Nano v3 given their launch timing alongside the Galaxy S26 wave, though this has not been officially confirmed. See our foldable phone comparison for how the Z Fold 8 and Pixel 10 Fold stack up today.
- Expect continued criticism of Google’s 7-year Pixel support promise as AI-capability gaps become a bigger part of how reviewers evaluate “future-proofing” a phone purchase.
- Carrier and retailer marketing will increasingly lean on “Gemini Nano v3 ready” as a spec-sheet bullet point, similar to how 5G and RAM tiers were marketed in prior device cycles.
- Apple’s next Apple Intelligence expansion is likely to be positioned defensively against this story, emphasizing broader device compatibility as a point of contrast with Google’s narrower rollout.
How to check if your phone qualifies
There is no single settings toggle that says “Gemini Nano v3 supported,” and the confusion is compounded by the fact that the base Gemini app itself is far less demanding: Google’s own September 2026 system requirements list the standard Gemini app as compatible with any Android phone running Android 9 or later with as little as 2GB of RAM, meaning the app installs and opens fine on hardware that will never see a single Gemini Intelligence feature. The most reliable signal reported across coverage is the combination of three checks: confirm your phone has 12GB of RAM or more, confirm it launched with a 2026-era flagship chip (Tensor G5, or the equivalent current-generation Snapdragon or Dimensity flagship silicon used in the Galaxy S26 and OnePlus 15), and check whether Gemini app settings surface Gemini Intelligence features directly, since Google is rolling the underlying capability out through app and system updates on qualifying hardware rather than a single universal switch.
If your phone is a Pixel 9, a Galaxy S25 series device, a Galaxy Z Fold 7, or older, current reporting indicates you are not eligible for the full Gemini Intelligence feature set regardless of software updates, because the gate sits at the on-device model layer rather than the OS version.
Frequently Asked Questions
What is Gemini Intelligence?
Gemini Intelligence is Google’s umbrella term for a set of proactive, agentic AI features built around an on-device Gemini Nano model, announced at the Google’s official Gemini Intelligence pages and rolled out across 2026 on qualifying Android flagships.
Which phones support Gemini Nano v3 right now?
As of October 2026, reported qualifying families are the Pixel 10 series (Pixel 10, Pixel 10 Pro, Pixel 10 Pro XL, Pixel 10 Pro Fold) plus the newly listed Pixel 11, the Samsung Galaxy S26 series alongside the newly compatible Galaxy Z Fold8, Z Fold8 Ultra and Z Flip8, the OnePlus 15, and the Oppo Find X9 series.
Why doesn’t the Galaxy S25 Ultra support Gemini Intelligence?
Android Authority’s reporting states the Galaxy S25 Ultra is excluded specifically because it runs Gemini Nano v2, not v3, despite meeting the 12GB RAM threshold and having a flagship chip.
How much RAM does Gemini Intelligence actually need?
Google’s published requirement is 12GB minimum, though a technical breakdown of Tensor G5 devices found roughly 3GB of that gets permanently reserved for AI models resident in memory, leaving about 9GB free for everything else.
Will older Pixel phones ever get Gemini Nano v3?
No official timeline has been given, and Android Authority’s analysis suggests it is unlikely in the near term, since the requirement is tied to on-device model validation against specific chip hardware rather than a standard software update.
Is Gemini Intelligence coming to mid-range phones?
Google and chip partners have discussed a Nano v3-capable mid-range chip, reported as similar to a Dimensity 8500 derivative, intended for non-flagship Android phones, but no named consumer device using it had shipped as of the most recent coverage.
Does Gemini Intelligence work without an internet connection?
The features tied to Gemini Nano v3, such as Magic Cue and Camera Coach on Pixel 10, run on-device, which is the reason Google cites for the strict RAM and chip requirements in the first place.
How does this compare to Apple Intelligence’s hardware requirements?
Apple Intelligence required an iPhone 15 Pro or newer at launch before expanding to the standard iPhone 16, a narrower initial gate than Gemini Intelligence’s multi-brand rollout but one that widened faster given Apple’s smaller device lineup.
