Gemma 4
Our most intelligent open models, built from Gemini 3 research and technology to maximize intelligence-per-parameter
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Maximum compute and memory efficiency
A new level of intelligence for mobile and IoT devices
Unprecedented intelligence-per-parameter
Frontier intelligence on personal computers
Maximum compute and memory efficiency
A new level of intelligence for mobile and IoT devices
Unprecedented intelligence-per-parameter
Frontier intelligence on personal computers
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Agentic workflows
Build autonomous agents that plan, navigate apps, and complete tasks on your behalf, with native support for function calling.
Multimodal reasoning
Develop applications with strong audio and visual understanding, for rich multimodal support.
Support for 140 languages
Create multilingual experiences that go beyond translation and understand cultural context.
Fine tuning
Improve performance for specific tasks by training Gemma using your preferred frameworks and techniques.
Efficient architecture
Run models on your own hardware for efficient development and deployment.
| Benchmark | | Gemma 4
31B IT Thinking | Gemma 4
26B A4B IT Thinking | Gemma 4
E4B IT Thinking | Gemma 4
E2B IT Thinking | Gemma 3
27B IT |
| --- | --- | --- | --- | --- | --- | --- |
| Arena AI (text) As of 4/2/26 | | 1452 | 1441 | — | — | 1365 |
| MMMLU Multilingual Q&A | No tools | 85.2% | 82.6% | 69.4% | 60.0% | 67.6% |
| MMMU Pro Multimodal reasoning | | 76.9% | 73.8% | 52.6% | 44.2% | 49.7% |
| AIME 2026 Mathematics | No tools | 89.2% | 88.3% | 42.5% | 37.5% | 20.8% |
| LiveCodeBench v6 Competitive coding problems | | 80.0% | 77.1% | 52.0% | 44.0% | 29.1% |
| GPQA Diamond Scientific knowledge | No tools | 84.3% | 82.3% | 58.6% | 43.4% | 42.4% |
| τ2-bench Agentic tool use | Retail | 86.4% | 85.5% | 57.5% | 29.4% | 6.6% |
These models were evaluated against a large collection of datasets and metrics to cover different aspects of text generation. See additional benchmarks in model card.
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