Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 4/8 categoriesMixtral 8x22B Instruct v0.1
36
0/8 categoriesGemma 4 31B· Mixtral 8x22B Instruct v0.1
Pick Gemma 4 31B if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 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 36. 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 multimodal & grounded, where it averages 76.9 against 35.5. The single biggest benchmark swing on the page is MMMU-Pro, 76.9% to 35%.
Gemma 4 31B is the reasoning model in the pair, while Mixtral 8x22B Instruct v0.1 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 64K for Mixtral 8x22B Instruct v0.1.
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 | Mixtral 8x22B Instruct v0.1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 35% |
| BrowseComp | — | 32% |
| OSWorld-Verified | — | 28% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | — |
| HumanEval | — | 54.8% |
| SWE-bench Pro | — | 40% |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 76.9% | 35% |
| OfficeQA Pro | — | 36% |
| ReasoningGemma 4 31B wins | ||
| BBH | 74.4% | — |
| MRCRv2 | 66.4% | 38% |
| LongBench v2 | — | 39% |
| KnowledgeGemma 4 31B wins | ||
| GPQA | 84.3% | — |
| MMLU-Pro | 85.2% | — |
| HLE | 26.5% | — |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 77.8% |
| FrontierScience | — | 53% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| MMLU-ProX | — | 42% |
| Mathematics | ||
| Coming soon | ||
Gemma 4 31B is ahead overall, 73 to 36. The biggest single separator in this matchup is MMMU-Pro, where the scores are 76.9% and 35%.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 53. Mixtral 8x22B Instruct v0.1 stays close enough that the answer can still flip depending on your workload.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 40. Mixtral 8x22B Instruct v0.1 stays close enough that the answer can still flip depending on your workload.
Gemma 4 31B has the edge for reasoning in this comparison, averaging 66.4 versus 38.5. 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 35.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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