Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-H-350M
~24
0/8 categoriesMixtral 8x22B Instruct v0.1
36
Winner · 2/8 categoriesGranite-4.0-H-350M· Mixtral 8x22B Instruct v0.1
Pick Mixtral 8x22B Instruct v0.1 if you want the stronger benchmark profile. Granite-4.0-H-350M only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Mixtral 8x22B Instruct v0.1 is clearly ahead on the aggregate, 36 to 24. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mixtral 8x22B Instruct v0.1's sharpest advantage is in knowledge, where it averages 53 against 16.4. The single biggest benchmark swing on the page is MMLU, 35.0% to 77.8%.
Mixtral 8x22B Instruct v0.1 gives you the larger context window at 64K, compared with 32K for Granite-4.0-H-350M.
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 | Granite-4.0-H-350M | Mixtral 8x22B Instruct v0.1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 35% |
| BrowseComp | — | 32% |
| OSWorld-Verified | — | 28% |
| Coding | ||
| HumanEval | 39% | 54.8% |
| SWE-bench Pro | — | 40% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 35% |
| OfficeQA Pro | — | 36% |
| Reasoning | ||
| BBH | 33.1% | — |
| LongBench v2 | — | 39% |
| MRCRv2 | — | 38% |
| KnowledgeMixtral 8x22B Instruct v0.1 wins | ||
| MMLU | 35.0% | 77.8% |
| GPQA | 24.1% | — |
| MMLU-Pro | 12.1% | — |
| FrontierScience | — | 53% |
| Instruction Following | ||
| IFEval | 55.4% | — |
| MultilingualMixtral 8x22B Instruct v0.1 wins | ||
| MGSM | 14.7% | — |
| MMLU-ProX | — | 42% |
| Mathematics | ||
| Coming soon | ||
Mixtral 8x22B Instruct v0.1 is ahead overall, 36 to 24. The biggest single separator in this matchup is MMLU, where the scores are 35.0% and 77.8%.
Mixtral 8x22B Instruct v0.1 has the edge for knowledge tasks in this comparison, averaging 53 versus 16.4. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Mixtral 8x22B Instruct v0.1 has the edge for multilingual tasks in this comparison, averaging 42 versus 14.7. Granite-4.0-H-350M stays close enough that the answer can still flip depending on your workload.
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