Gemma 4 31B IT
Gemma 4 31B IT is an open-weights language model from Google, released April 2, 2026. It has 31B parameters (dense). The context window is 256K tokens. On the Epoch Capabilities Index it scores 144.3, rank 100 of 256 rated models.
We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemma 4 model suite features dense and Mixture-of-Experts architectures, ranging from 2.3B to 31B parameters.
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Can you run Gemma 4 31B IT locally?
The smallest common GPU it runs on is 12 GB of VRAM (with 32 GB of RAM): IQ3_XXS, split GPU / CPU, roughly 5 tokens per second. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Very slow | IQ3_XXS (noticeable loss) | 5.2 GB | 10.6 GB | ~3 |
| 8 GB VRAM | Very slow | IQ3_XXS (noticeable loss) | 7.2 GB | 8.6 GB | ~3 |
| 12 GB VRAM | Runs, slowly | IQ3_XXS (noticeable loss) | 11.2 GB | 4.6 GB | ~5 |
| 16 GB VRAM | Runs, slowly | Q3_K_M (okay) | 15.2 GB | 3.9 GB | ~6 |
| 24 GB VRAM | Runs on GPU | Q4_K_M (very good) | 22.9 GB | – | ~29 |
| 32 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 29.4 GB | – | ~41 |
Strengths by category
ModelTape's 0–100 fit on Epoch AI benchmark results.
| Category | Score | Based on |
|---|---|---|
| Knowledge | 54.6 | GPQA diamond, SimpleQA Verified |
Benchmark results
| Benchmark (Epoch AI) | Score |
|---|---|
| OTIS Mock AIME | 73.3% |
| GPQA Diamond | 70.5% |
| SimpleQA Verified | 10.4% |
Links
Models with a similar score
Qwen3.5 397B-A17B · Qwen3.7-Plus · MiniMax-M3 · Claude Sonnet 4.5 · o3-pro · Qwen 3.5 Plus (hosted 397B-A17B) · o3 · Nemotron 3 Ultra
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