Gemma 4 26B A4B IT
Gemma 4 26B A4B is the Mixture-of-Experts model in Google DeepMind's Gemma 4 family: 25.2 billion total parameters with only 3.8B active per token, native text and image input, a 256K-token context window, configurable thinking and function calling, released as open weights under Apache 2.0.
Model
Gemma 4 26B A4B is a 30-layer Mixture-of-Experts transformer with 128 routed experts plus one shared expert, of which 8 are active per token, so only 3.8B of its 25.2B parameters run at inference and it decodes at close to the speed of a 4B dense model. A ~550M-parameter vision encoder accepts images at variable aspect ratios and resolutions with a configurable visual token budget. Interleaved local sliding-window and global attention, with unified keys and values and Proportional RoPE in the global layers, supports a 256K-token context. It has a switchable thinking mode, native function calling and a system role, and scores 82.6% on MMLU Pro and 77.1% on LiveCodeBench v6.
This is the instruction-tuned variant, released as open weights under the Apache 2.0 license. Google recommends sampling at temperature 1.0, top-p 0.95 and top-k 64, with thinking enabled by prefixing the system prompt with the think control token. Full details are in Google's announcement and the model card.
Dedicated Endpoint
DocsA Dedicated Endpoint is your own deployment of Gemma 4 26B A4B IT, on an inference stack that Modal tunes and autoscales. Bring fine-tuned weights if you have them. Compute is billed by the second, and only while it runs.
modal endpoint create --model google/gemma-4-26B-A4B-it