Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 2/8 categorieso1
64
2/8 categoriesGemma 4 31B· o1
Pick Gemma 4 31B if you want the stronger benchmark profile. o1 only becomes the better choice if reasoning is the priority.
Gemma 4 31B is clearly ahead on the aggregate, 73 to 64. 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 46.6. The single biggest benchmark swing on the page is MRCRv2, 66.4% to 77%. o1 does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 31B. That is roughly Infinityx on output cost alone. Gemma 4 31B gives you the larger context window at 256K, compared with 200K for o1.
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 | o1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 66% |
| BrowseComp | — | 72% |
| OSWorld-Verified | — | 60% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | — |
| SWE-bench Verified | — | 41% |
| SWE-bench Pro | — | 50% |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 76.9% | 68% |
| OfficeQA Pro | — | 74% |
| Reasoningo1 wins | ||
| BBH | 74.4% | — |
| MRCRv2 | 66.4% | 77% |
| LongBench v2 | — | 79% |
| Knowledgeo1 wins | ||
| GPQA | 84.3% | 75.7% |
| MMLU-Pro | 85.2% | — |
| HLE | 26.5% | — |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 91.8% |
| FrontierScience | — | 65% |
| Instruction Following | ||
| IFEval | — | 92.2% |
| Multilingual | ||
| MMLU-ProX | — | 77% |
| Mathematics | ||
| AIME 2024 | — | 74.3% |
Gemma 4 31B is ahead overall, 73 to 64. The biggest single separator in this matchup is MRCRv2, where the scores are 66.4% and 77%.
o1 has the edge for knowledge tasks in this comparison, averaging 69.3 versus 61.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 46.6. o1 stays close enough that the answer can still flip depending on your workload.
o1 has the edge for reasoning in this comparison, averaging 78.1 versus 66.4. 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 70.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.