Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 3/8 categorieso4-mini (high)
58
1/8 categoriesGemma 4 31B· o4-mini (high)
Pick Gemma 4 31B if you want the stronger benchmark profile. o4-mini (high) only becomes the better choice if knowledge is the priority.
Gemma 4 31B is clearly ahead on the aggregate, 73 to 58. 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 coding, where it averages 80 against 44.9. The single biggest benchmark swing on the page is LiveCodeBench, 80% to 34%. o4-mini (high) does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 31B gives you the larger context window at 256K, compared with 200K for o4-mini (high).
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 | o4-mini (high) |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 58% |
| BrowseComp | — | 64% |
| OSWorld-Verified | — | 55% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | 34% |
| HumanEval | — | 74% |
| SWE-bench Verified | — | 68.1% |
| SWE-bench Pro | — | 42% |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 76.9% | 66% |
| OfficeQA Pro | — | 71% |
| ReasoningGemma 4 31B wins | ||
| BBH | 74.4% | 83% |
| MRCRv2 | 66.4% | 74% |
| MuSR | — | 78% |
| LongBench v2 | — | 75% |
| ARC-AGI-2 | — | 2.4% |
| Knowledgeo4-mini (high) wins | ||
| GPQA | 84.3% | 82% |
| MMLU-Pro | 85.2% | 76% |
| HLE | 26.5% | 13% |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 82% |
| SuperGPQA | — | 80% |
| FrontierScience | — | 73% |
| SimpleQA | — | 80% |
| Instruction Following | ||
| IFEval | — | 83% |
| Multilingual | ||
| MGSM | — | 83% |
| MMLU-ProX | — | 81% |
| Mathematics | ||
| AIME 2023 | — | 83% |
| AIME 2024 | — | 93.4% |
| AIME 2025 | — | 92.7% |
| HMMT Feb 2023 | — | 79% |
| HMMT Feb 2024 | — | 81% |
| HMMT Feb 2025 | — | 80% |
| BRUMO 2025 | — | 82% |
| MATH-500 | — | 84% |
Gemma 4 31B is ahead overall, 73 to 58. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80% and 34%.
o4-mini (high) has the edge for knowledge tasks in this comparison, averaging 62.7 versus 61.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 44.9. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for reasoning in this comparison, averaging 66.4 versus 57.2. Inside this category, BBH 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 68.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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