Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
Winner · 3/8 categoriesMixtral 8x22B Instruct v0.1
36
1/8 categoriesGemma 4 E4B· Mixtral 8x22B Instruct v0.1
Pick Gemma 4 E4B if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if reasoning is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 E4B is clearly ahead on the aggregate, 47 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 E4B's sharpest advantage is in multimodal & grounded, where it averages 52.6 against 35.5. The single biggest benchmark swing on the page is MMMU-Pro, 52.6% to 35%. Mixtral 8x22B Instruct v0.1 does hit back in reasoning, 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 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 E4B gives you the larger context window at 128K, 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 E4B | Mixtral 8x22B Instruct v0.1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 35% |
| BrowseComp | — | 32% |
| OSWorld-Verified | — | 28% |
| CodingGemma 4 E4B wins | ||
| LiveCodeBench | 52% | — |
| HumanEval | — | 54.8% |
| SWE-bench Pro | — | 40% |
| Multimodal & GroundedGemma 4 E4B wins | ||
| MMMU-Pro | 52.6% | 35% |
| OfficeQA Pro | — | 36% |
| ReasoningMixtral 8x22B Instruct v0.1 wins | ||
| BBH | 33.1% | — |
| MRCRv2 | 25.4% | 38% |
| LongBench v2 | — | 39% |
| KnowledgeGemma 4 E4B wins | ||
| GPQA | 58.6% | — |
| MMLU-Pro | 69.4% | — |
| MMLU | — | 77.8% |
| FrontierScience | — | 53% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| MMLU-ProX | — | 42% |
| Mathematics | ||
| Coming soon | ||
Gemma 4 E4B is ahead overall, 47 to 36. The biggest single separator in this matchup is MMMU-Pro, where the scores are 52.6% and 35%.
Gemma 4 E4B has the edge for knowledge tasks in this comparison, averaging 65.6 versus 53. Mixtral 8x22B Instruct v0.1 stays close enough that the answer can still flip depending on your workload.
Gemma 4 E4B has the edge for coding in this comparison, averaging 52 versus 40. Mixtral 8x22B Instruct v0.1 stays close enough that the answer can still flip depending on your workload.
Mixtral 8x22B Instruct v0.1 has the edge for reasoning in this comparison, averaging 38.5 versus 25.4. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemma 4 E4B has the edge for multimodal and grounded tasks in this comparison, averaging 52.6 versus 35.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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