Developers have downloaded past Gemma generations over 400 million times, spawning more than 100,000 community variants. This release is the most ambitious one yet.
We just released Gemma 4 — our most intelligent open models to date.
Built from the same world-class research as Gemini 3, Gemma 4 brings breakthrough intelligence directly to your own hardware for advanced reasoning and agentic workflows.
The model is "built from the same world-class research and technology as Gemini 3," Google said in its announcement. Gemma 4 ships in four sizes: Effective 2B and 4B for phones and edge devices, a 26B Mixture of Experts model focused on speed, and a 31B Dense model optimized for raw quality.
We tested Gemma 4. It's capable, with some caveats. The model applies reasoning even to tasks that don't require it, which can make responses feel over-engineered for simple prompts. Creative writing is decent—serviceable, not inspired—and likely improves with more specific guidance and prompt engineering.
Where it delivered most clearly was code. Asked to generate a game, the output wasn't particularly flashy or elaborate, but it ran without errors on the first try. Not bad for a 41 billion parameter model. That zero-shot reliability is arguably more valuable than a prettier result that needs debugging.
The four variants cover the full hardware spectrum. The E2B and E4B models are built for Android phones, Raspberry Pi, and edge devices, running completely offline with near-zero latency, native audio input, and a 128K context window. The 26B and 31B models target workstations and cloud deployments, extending context to 256K and adding native function-calling and structured JSON output for building autonomous agents. All four models process images and video natively. The larger models' full-precision weights fit on a single 80GB NVIDIA H100 GPU; quantized versions run on consumer hardware.
