Gemini Intelligence exposes the problem with Google's 7-year Pixel promise

At a glance:

• Google's Gemini Intelligence requires 12GB of RAM, leaving behind budget devices including the Pixel 10a
• Only the Pixel 10 series currently supports the Nano v3 on-device AI model, with Pixel 9 and older limited to Nano v2
• Google's seven-year update promise for Pixel devices doesn't guarantee access to all AI features, creating uncertainty for consumers

The AI hardware barrier

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. This creates a significant accessibility issue for consumers who want the latest AI experiences but may not have access to premium hardware.

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. This creates a situation where even relatively recent flagship devices are being left behind in terms of AI capabilities.

Developer limitations confirm the divide

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. This indicates that the hardware requirements for advanced AI features are becoming increasingly demanding across the industry.

What worries you most about agentic AI on smartphones? 492 votes reveal consumer concerns about AI fragmentation and accessibility. This sentiment highlights the growing tension between technological advancement and inclusive access to cutting-edge features. As AI becomes central to the mobile experience, the gap between high-end and mid-range devices is widening, potentially creating a tiered experience based on hardware capabilities rather than software support longevity.

The update promise paradox

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.

This does reinforce something Android users are increasingly running into: long-term update promises don't guarantee access to every new feature. Seven-year update promises feel hollow in the age of AI fragmentation. 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.

AI as a "bolt-on" layer

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. This architectural decision enables quicker deployment of new AI capabilities but also creates the fragmentation we're seeing.

Still, that doesn't let Pixels off the hook. 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. This hardware strategy seems at odds with the company's ambitious AI vision.

The hardware arms race

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. This creates a significant challenge for manufacturers who must balance performance, power efficiency, and cost in an increasingly competitive market.

Even so, it's hard to fully excuse older devices falling behind this quickly. When phones like the 2025 vivo X100 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. This suggests that either Google's hardware strategy needs reevaluation or the company is intentionally creating differentiation between its flagship models to drive upgrades. Either way, it creates uncertainty for consumers who expect their premium devices to remain competitive for longer periods.

Consumer uncertainty

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.

As AI becomes central to the mobile experience, the industry faces a fundamental challenge: how to deliver cutting-edge capabilities without creating a tiered system where only the latest hardware can access the most advanced features. This tension between innovation and accessibility will likely define the next phase of mobile development, with companies like Google needing to balance their technical ambitions with the practical realities of device longevity and consumer expectations.