Google Launches Gemma 4: Open AI Model Family Built on Gemini 3 Research

Google Unveils Fourth-Generation Open AI Models

Google has officially released Gemma 4, the fourth generation of its open AI model family designed for advanced reasoning and agentic workflows. The new lineup is built on the same research and technology that powers the Gemini 3 chatbot.

"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. Released under a commercially…" — Google (@Google), original post

According to the company, Gemma 4 delivers "unprecedented intelligence per parameter." Since the first generation launched, developers have downloaded Gemma models over 400 million times and created more than 100,000 model variants within the Gemmaverse ecosystem.

Why This Matters

Open-weight AI models are central to democratizing access to advanced AI capabilities. Gemma 4 enables powerful neural networks to run on consumer devices — from smartphones to laptops — without relying on cloud services. For the crypto industry and Web3 developers, this opens the door to building autonomous AI agents that operate locally, which is essential for applications requiring data privacy and decentralized computing infrastructure.

Four Models for Different Use Cases

The Gemma 4 family consists of four models at varying scales:

• Effective 2B (E2B) — 2.3 billion active parameters;
• Effective 4B (E4B) — 4.5 billion active parameters;
• 26B Mixture of Experts (MoE) — 26 billion parameters;
• 31B Dense — 31 billion parameters (flagship).

The compact E2B and E4B versions focus on multimodality, low latency, and seamless integration. They can run on a standard smartphone or laptop. The larger 26B MoE and flagship 31B Dense models require hardware on the level of an Nvidia H100 with 80 GB of memory, targeting researchers and professional developers.

On the Arena AI global leaderboard for open text models, the flagship 31B ranks third while the 26B MoE holds sixth place. Google claims the new lineup outperforms competing models that are 20 times larger.

Core Capabilities of Gemma 4

The defining feature of the new family is its advanced reasoning ability. The models construct complex logical chains and plan multi-step tasks, showing significant improvement in math benchmarks and instruction-following accuracy.

Additional capabilities include:

• Agentic workflows — built-in support for function calling, structured JSON output, and system instructions enables creation of autonomous assistants that interact with external tools and APIs;
• Code generation — high-quality offline code writing that turns any workstation into a local AI coding assistant;
• Vision and audio processing — all models handle video and variable-resolution images, recognize text, and analyze diagrams. E2B and E4B also support speech recognition and understanding;
• Extended context window — compact versions support up to 128,000 tokens, while larger models handle up to 256,000. This is sufficient to process entire code repositories or lengthy documents in a single prompt;
• Multilingual support — the model family works with more than 140 languages.

Availability and Platform Support

Gemma 4 is already accessible through Google AI Studio and Google AI Edge Gallery. Integration is supported across popular third-party tools and frameworks including Hugging Face, vLLM, llama.cpp, MLX, Ollama, NVIDIA NIM, and LM Studio. Fine-tuning can be done via Google Colab, Vertex AI, or on local GPUs.

For production deployment, Google offers infrastructure through Google Cloud, including Cloud Run, GKE, and Sovereign Cloud. The models are released under a commercial license, enabling broad business applications.