The AI era is making Google’s 7-year Pixel promise harder to trust

The future of Android is here, and it looks a lot like Gemini Intelligence. But, as with most paradigm shifts, there’s a catch: the looming hardware requirements are already leaving plenty of phones behind. Starting with a minimum of 12GB of RAM, many affordable devices simply won’t make the cut — including Google’s own budget-friendly Pixel 10a.

The bigger issue, though, is Google’s on-device AI stack. Gemini Intelligence relies on the tiny but mighty Nano v3 on-device model. According to Google’s ML Kit support documentation, the Pixel 10 is currently the only Google-branded series that supports it. The Pixel 9 lineup — and seemingly everything older — is stuck on Nano v2.

I installed the AICore developer preview on last year’s flagship to confirm it myself. Even developers can’t access Nano v3 or the upcoming Nano v4 on barely two-year-old hardware, which suggests support isn’t coming anytime soon. And it’s not just Pixels: many phones launched in 2025 and even some in early 2026, including the Xiaomi 17 Ultra, also appear limited to older on-device models — at least for now.

That doesn’t necessarily mean the Pixel 9 series and other recent flagships will never support Nano v3. These models can theoretically be upgraded via over-the-air and/or AICore updates, and Google may backport Gemini Intelligence in the future (it hasn’t commented either way). The problem is that users have no control over that process, and Google hasn’t clarified what hardware or software requirements stand in the way. We don’t know whether the barriers are technical, commercial, or simply a matter of OEM effort.

What this does reinforce is something Android users are increasingly running into: long-term update promises don’t guarantee access to every new feature.

AI features exist in an especially gray area. Google may be positioning Gemini as central to the latest Pixel experience, but technically, these features sit outside core Android. Gemini is effectively a bolt-on layer rapidly augmenting the OS, not something bundled into AOSP itself. That distinction matters because it gives Google — and its hardware partners — far more flexibility in deciding which devices receive what, and allows for faster innovation than baking everything into the core.

Still, that doesn’t let Pixels off the hook.

Google has spent the better part of two years selling Gemini as the future of Pixel. Leaving devices behind after a single generation is a terrible look, especially when buyers were promised seven years of support. If anything, Google should want its best AI experiences available across as many Pixel generations as possible to strengthen the brand’s leadership position. Otherwise, it risks making “seven years of updates” sound increasingly conditional.

Maybe it does. I’d like to believe there’s a legitimate technical reason behind all this. Google says the Tensor G5’s third-generation TPU is 60% faster than its predecessor, and that could genuinely matter for Gemini Intelligence. The company’s next wave of AI features appears heavily focused on real-time contextual awareness and rapid on-device inference — workloads where latency matters just as much as raw capability.

The push toward on-device AI was always going to reignite the mobile hardware arms race. “Agentic” AI systems and context-aware assistants demand larger models, more RAM, higher memory bandwidth, and significantly faster matrix-processing performance. Modern mobile chips already juggle gaming, imaging, networking, and multimedia workloads; now AI wants a much larger slice of the silicon budget too.

Even so, it’s hard to fully excuse older devices falling behind this quickly.

Google controls both Pixel hardware and Tensor silicon, yet its AI roadmap already feels oddly fragmented. Part of the problem is that the Tensor G4 reused the same TPU found in the G3, meaning the Pixel 9 series is effectively running AI hardware that was already aging before it even launched. Google has also been relatively conservative with CPU and GPU upgrades, limiting opportunities for older hardware to make up for it elsewhere.

And when phones like the 2025 vivo X200 already support Nano v3 while the Pixel 9 series doesn’t, you have to question whether Google’s custom TPU investments are delivering the advantage they were supposed to.

Whether this fragmentation stems from hardware limitations, development costs, or artificial product segmentation, one thing is already clear: the AI era is making long-term software promises much harder to define.

That leaves consumers in an awkward position. Buy a $1,200 Pixel 10 Pro XL today, and there’s no guarantee it won’t miss out on next-gen flagship AI experiences the moment Google unveils Gemini Intelligence 2.0 at next year’s I/O. Sure, the phone will still receive Android updates for years. But if AI truly is the future of Android, companies need to be far clearer about what those long-term update promises actually include — and, increasingly, what they don’t.​