Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 4/8 categoriesMistral 7B v0.3
29
0/8 categoriesGemma 4 31B· Mistral 7B v0.3
Pick Gemma 4 31B if you want the stronger benchmark profile. Mistral 7B v0.3 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 31B is clearly ahead on the aggregate, 73 to 29. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 31B's sharpest advantage is in coding, where it averages 80 against 13.5. The single biggest benchmark swing on the page is LiveCodeBench, 80% to 14%.
Gemma 4 31B is the reasoning model in the pair, while Mistral 7B v0.3 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemma 4 31B gives you the larger context window at 256K, compared with 32K for Mistral 7B v0.3.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | Gemma 4 31B | Mistral 7B v0.3 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 24% |
| BrowseComp | — | 32% |
| OSWorld-Verified | — | 25% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | 14% |
| HumanEval | — | 30.5% |
| SWE-bench Verified | — | 15% |
| SWE-bench Pro | — | 12% |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 76.9% | 27% |
| OfficeQA Pro | — | 39% |
| ReasoningGemma 4 31B wins | ||
| BBH | 74.4% | 63% |
| MRCRv2 | 66.4% | 41% |
| MuSR | — | 26% |
| LongBench v2 | — | 38% |
| KnowledgeGemma 4 31B wins | ||
| GPQA | 84.3% | 29% |
| MMLU-Pro | 85.2% | 54% |
| HLE | 26.5% | 5% |
| HLE w/o tools | 19.5% | — |
| SuperGPQA | — | 27% |
| FrontierScience | — | 34% |
| SimpleQA | — | 28% |
| Instruction Following | ||
| IFEval | — | 68% |
| Multilingual | ||
| MGSM | — | 62% |
| MMLU-ProX | — | 60% |
| Mathematics | ||
| AIME 2023 | — | 30% |
| AIME 2024 | — | 32% |
| AIME 2025 | — | 31% |
| HMMT Feb 2023 | — | 26% |
| HMMT Feb 2024 | — | 28% |
| HMMT Feb 2025 | — | 27% |
| BRUMO 2025 | — | 29% |
| MATH-500 | — | 60% |
Gemma 4 31B is ahead overall, 73 to 29. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80% and 14%.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 29.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 13.5. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for reasoning in this comparison, averaging 66.4 versus 35.8. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for multimodal and grounded tasks in this comparison, averaging 76.9 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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