Gemma 4 introduces multimodal support (text, image, video, audio on small models), extended context windows (128K-256K tokens), configurable reasoning modes, and native function calling. Available in four sizes with both dense and MoE architectures.
Google DeepMind introduces Gemma 4 31B with multimodal input (text and images), 256K context window, configurable reasoning mode, and native function calling. Free release under Apache 2.0 license.
NVIDIA released NVFP4-quantized version of Google DeepMind's Gemma 4 31B IT model optimized for consumer GPU inference. Maintains 256K context window and multimodal capabilities with <0.5% performance degradation on reasoning and coding benchmarks.
NVIDIA has released a quantized version of Google DeepMind's Gemma 4 31B IT model, compressed to NVFP4 format for efficient inference on consumer GPUs. The 30.7B-parameter multimodal model supports 256K token context windows, handles text and image inputs with video frame processing, and maintains near-baseline performance across reasoning and coding benchmarks.
Google DeepMind has released Gemma 4, a family of open-weights multimodal models ranging from 2.3B to 31B parameters with support for text, images, video, and audio. The models feature context windows up to 256K tokens, built-in reasoning modes, and native function calling for agentic workflows.
Google DeepMind has released Gemma 4 31B, a 30.7-billion-parameter multimodal model supporting text and image input. The model features a 262,144-token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages under Apache 2.0 license.
Google DeepMind released the Gemma 4 family of open-weights models ranging from 2.3B to 31B parameters, featuring up to 256K token context windows and native support for text, image, video, and audio inputs. The flagship 31B model scores 85.2% on MMLU Pro and 89.2% on AIME 2026, with a smaller 26B MoE variant requiring only 3.8B active parameters for faster inference.