Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
2/8 categoriesMistral Large 2
52
Winner · 2/8 categoriesGemma 4 E4B· Mistral Large 2
Pick Mistral Large 2 if you want the stronger benchmark profile. Gemma 4 E4B only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Mistral Large 2 is clearly ahead on the aggregate, 52 to 47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mistral Large 2's sharpest advantage is in reasoning, where it averages 66.1 against 25.4. The single biggest benchmark swing on the page is BBH, 33.1% to 82%. Gemma 4 E4B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 E4B is the reasoning model in the pair, while Mistral Large 2 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.
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 E4B | Mistral Large 2 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 51% |
| BrowseComp | — | 57% |
| OSWorld-Verified | — | 50% |
| CodingGemma 4 E4B wins | ||
| LiveCodeBench | 52% | 38% |
| HumanEval | — | 60% |
| SWE-bench Verified | — | 49% |
| SWE-bench Pro | — | 44% |
| Multimodal & GroundedMistral Large 2 wins | ||
| MMMU-Pro | 52.6% | 56% |
| OfficeQA Pro | — | 67% |
| ReasoningMistral Large 2 wins | ||
| BBH | 33.1% | 82% |
| MRCRv2 | 25.4% | 68% |
| MuSR | — | 64% |
| LongBench v2 | — | 66% |
| KnowledgeGemma 4 E4B wins | ||
| GPQA | 58.6% | 68% |
| MMLU-Pro | 69.4% | 74% |
| MMLU | — | 68% |
| SuperGPQA | — | 66% |
| HLE | — | 12% |
| FrontierScience | — | 65% |
| SimpleQA | — | 66% |
| Instruction Following | ||
| IFEval | — | 83% |
| Multilingual | ||
| MGSM | — | 81% |
| MMLU-ProX | — | 78% |
| Mathematics | ||
| AIME 2023 | — | 68% |
| AIME 2024 | — | 70% |
| AIME 2025 | — | 69% |
| HMMT Feb 2023 | — | 64% |
| HMMT Feb 2024 | — | 66% |
| HMMT Feb 2025 | — | 65% |
| BRUMO 2025 | — | 67% |
| MATH-500 | — | 82% |
Mistral Large 2 is ahead overall, 52 to 47. The biggest single separator in this matchup is BBH, where the scores are 33.1% and 82%.
Gemma 4 E4B has the edge for knowledge tasks in this comparison, averaging 65.6 versus 55.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 E4B has the edge for coding in this comparison, averaging 52 versus 42.8. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Mistral Large 2 has the edge for reasoning in this comparison, averaging 66.1 versus 25.4. Inside this category, BBH is the benchmark that creates the most daylight between them.
Mistral Large 2 has the edge for multimodal and grounded tasks in this comparison, averaging 61 versus 52.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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