Gemma 4 is a family of open models, purpose-built for advanced reasoning and agentic workflows.
Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in four distinct sizes: E2B, E4B, 26B A4B, and 31B.
Today, we’re bringing Gemma 4 to you on Google Cloud, including Vertex AI, Cloud Run, GKE, and Sovereign Cloud.
Google DeepMind introduces Gemma 4, a family of state-of-the-art open models designed for on-device agentic workflows. Learn how to leverage multi-step planning, 140+ language support, and LiteRT-LM to build powerful, autonomous AI experiences across mobile, desktop, and IoT.
Gemma 4 models are designed to deliver frontier-level performance at each size. They are well-suited for reasoning, agentic workflows, coding, and multimodal understanding.
The Gemma 4 multimodal and multilingual model family was launched to support a wide range of AI tasks, offering improved efficiency and accuracy, and can be deployed across the full spectrum of NVIDIA hardware, from Blackwell data centers to Jetson edge devices. Four models are included, featuring Gemmas first MoE model, and support for over 140 languages; these models enable reasoning, code ...
Gemma 4 E4B scores -20 on AA-Omniscience and Gemma 4 E2B scores -24, both substantially better than Gemma 4 31B (-45) and comparable to or better than much larger models like DeepSeek V3.2 (Reasoning, -21). The larger Gemma 4 models' AA-Omniscience scores are in line with Qwen3.5 27B (-42) and Gemma 4 26B A4B (-48)