Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 1/8 categoriesGranite-4.0-H-350M
~22
0/8 categoriesGemma 4 31B· Granite-4.0-H-350M
Pick Gemma 4 31B if you want the stronger benchmark profile. Granite-4.0-H-350M 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 22. 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 knowledge, where it averages 61.3 against 16.4. The single biggest benchmark swing on the page is MMLU-Pro, 85.2% to 12.1%.
Gemma 4 31B is the reasoning model in the pair, while Granite-4.0-H-350M 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 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 | Gemma 4 31B | Granite-4.0-H-350M |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| LiveCodeBench | 80% | — |
| HumanEval | — | 39% |
| Multimodal & Grounded | ||
| MMMU-Pro | 76.9% | — |
| Reasoning | ||
| BBH | 74.4% | 33.1% |
| MRCRv2 | 66.4% | — |
| KnowledgeGemma 4 31B wins | ||
| GPQA | 84.3% | 24.1% |
| MMLU-Pro | 85.2% | 12.1% |
| HLE | 26.5% | — |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 35.0% |
| Instruction Following | ||
| IFEval | — | 55.4% |
| Multilingual | ||
| MGSM | — | 14.7% |
| Mathematics | ||
| Coming soon | ||
Gemma 4 31B is ahead overall, 73 to 22. The biggest single separator in this matchup is MMLU-Pro, where the scores are 85.2% and 12.1%.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 16.4. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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