Review of Gemma 4
Gemma 4 is the latest open-source model family from Google DeepMind, derived from Gemini 3 research. The lineup includes pre-trained and instruction-tuned variants with a context window up to 256K tokens and native support for over 140 languages. Models include a configurable thinking mode, native multimodal capabilities for image, video and audio, plus native function calling that makes them ideal for AI agents.
Gemma 4: La famille open source de Google DeepMind, taillée pour l'edge, les agents IA et le raisonnement avancé.
Best for
- AI teams building open-source agents in-house
- Developers targeting edge and mobile deployments
- Regulated organizations seeking auditable on-premise models
- Researchers working on reasoning and multilingual stacks
Not ideal for
- Users seeking a turnkey SaaS product like ChatGPT
- Cases requiring Anthropic-like commercial support
- Small projects without dedicated inference infrastructure
- Scenarios needing top-tier image generation specifically
Pros & cons
- ✅ Open-source models under permissive Apache 2.0 license
- ✅ Full family: 2B and 4B for the edge, 31B dense and 26B MoE
- ✅ Context window up to 256K tokens on medium models
- ✅ Native multimodality: image, video, audio with strong OCR
- ✅ Multilingual support across 140+ languages including French
- ✅ Native function calling to build autonomous agents
- ⚠️ Raw performance still trails Gemini 3 on some benchmarks
- ⚠️ Advanced multimodal versions need high-end GPUs
- ⚠️ French docs and community resources still limited
- ⚠️ Variable interop depending on the inference framework
- ⚠️ Production deployment requires structured MLOps skills
Our verdict
Gemma 4 confirms Google DeepMind's central role in the open-source AI ecosystem. The new generation directly benefits from Gemini 3 research, which shows in reasoning quality, multimodal depth and multilingual support. The family covers a rare spectrum: 2B and 4B models perfect for the edge and mobile, plus a 31B dense and a 26B MoE model built for servers. The Apache 2.0 license — commercially permissive — removes traditional friction and lets enterprises fine-tune, audit and deploy without legal constraints. Native function calling and a configurable thinking mode make it an excellent foundation for ambitious AI agents. Limits stem from the residual gap with Gemini 3 on top benchmarks and the MLOps sophistication required to fully exploit multimodal versions. For AI teams building agents and open assistants on a top-tier model, Gemma 4 is probably the best open-source pick available in 2026.
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FAQ
Is Gemma 4 truly open source?
Yes, the Gemma 4 family ships under the Apache 2.0 license, allowing unrestricted commercial use.
What models are part of the family?
Gemma 4 includes 2B and 4B models for edge, a 31B dense model for advanced reasoning and a 26B MoE optimized for throughput.
Which languages are supported?
Over 140 languages are natively supported, including French, English, Spanish, German and many Asian languages.
Does the model handle images and videos?
Yes, Gemma 4 natively processes text, images and video, with strong OCR and chart understanding.
Can it run on mobile?
Yes, the 2B and 4B variants target edge, mobile and browser deployments, via LiteRT-LM or Cactus.