Gemma 4 introduces multimodal capabilities (text, image, video support), reasoning modes, 256K context windows, and Mixture-of-Experts architecture. The 26B A4B variant uses sparse activation for near-dense-31B performance with 4B-model inference speed.
Google releases Gemma 4 26B, a free sparse MoE model with multimodal capabilities including video support, 256K context window, and reasoning mode.
Google DeepMind has released Gemma 4 26B A4B, a free instruction-tuned Mixture-of-Experts model with 262,144 token context window and multimodal capabilities including text, images, and video input. Despite 25.2B total parameters, only 3.8B activate per token, delivering performance comparable to larger 31B models at reduced compute cost.
Google DeepMind released the Gemma 4 family of open-weights multimodal models in four sizes: E2B (2.3B effective), E4B (4.5B effective), 26B A4B (25.2B total, 3.8B active), and 31B dense. All models support text and image input with 128K-256K context windows, reasoning modes, and native function calling for agentic workflows.