Google’s Gemini Intelligence is one of the more talked-about Android announcements this week, but the fine print tells a different story from the marketing. The requirements are strict, and the vast majority of Galaxy phones simply won’t make the cut.
Google has published (via AssembleDebug on X) the eligibility criteria for Gemini Intelligence on Android, and each requirement is designed to ensure the on-device AI workloads actually run reliably. Together, they paint a picture of a feature built for a very specific tier of hardware.
What does your Galaxy phone actually need?
The most obvious barrier is the processor. Gemini Intelligence demands a flagship-class chip with a capable NPU, since the feature depends heavily on on-device inference rather than cloud processing. That immediately rules out midrange chips and older flagship silicon that doesn’t have proper AI acceleration built in.
RAM is the next hurdle. Devices need at least 12GB to qualify, which reflects how memory-hungry on-device AI has become. Features like real-time transcription and contextual suggestions run as persistent background processes, and anything below 12GB creates bottlenecks when multitasking is thrown into the mix.
Perhaps the most critical requirement is support for Gemini Nano v3, the latest version of Google’s on-device language model. It brings faster inference, improved prompt handling, and broader API support compared to Nano v2. Devices still running the older version simply lack the framework needed to run key Gemini Intelligence features, so there’s no workaround there.
Google is also tying eligibility to long-term software support commitments. Qualifying devices must be guaranteed at least five Android OS upgrades and around six years of security patches. The idea is that AI capabilities should evolve alongside the device rather than become a dead end after a couple of update cycles. On that front, Samsung’s One UI 8.5 eligible devices list gives a sense of which Galaxy models are still in the software support window.
On top of all that, Google has internal quality-of-service benchmarks that devices must pass. These cover crash rates, latency, and general stability during AI workloads. It’s not enough to have the right chip and memory on paper; the device has to perform consistently under pressure.
In short, the combination of a modern flagship chip, 12GB of RAM, Nano v3 support, and a long update guarantee narrows the eligible Galaxy lineup considerably. Only three Galaxy phones reportedly have full support at this point, which is a telling sign of just how high Google has set the bar. For context on what Samsung’s update commitments look like going forward, our One UI 8.5 overview covers the broader rollout picture.
