Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 4/8 categoriesGPT-4o
50
0/8 categoriesGemma 4 31B· GPT-4o
Pick Gemma 4 31B if you want the stronger benchmark profile. GPT-4o 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 50. 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 30.4. The single biggest benchmark swing on the page is LiveCodeBench, 80% to 38%.
GPT-4o is also the more expensive model on tokens at $2.50 input / $10.00 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 is the reasoning model in the pair, while GPT-4o 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 128K for GPT-4o.
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 | GPT-4o |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 49% |
| OSWorld-Verified | — | 48% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | 38% |
| HumanEval | — | 58% |
| SWE-bench Verified | — | 20% |
| SWE-bench Pro | — | 29% |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 76.9% | — |
| OfficeQA Pro | — | 70% |
| VideoMMMU | — | 61.2% |
| ReasoningGemma 4 31B wins | ||
| BBH | 74.4% | 82% |
| MRCRv2 | 66.4% | 63% |
| MuSR | — | 62% |
| LongBench v2 | — | 62% |
| KnowledgeGemma 4 31B wins | ||
| GPQA | 84.3% | 66% |
| MMLU-Pro | 85.2% | 64% |
| HLE | 26.5% | 1% |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 66% |
| FrontierScience | — | 58% |
| Instruction Following | ||
| IFEval | — | 82% |
| Multilingual | ||
| MMLU-ProX | — | 72% |
| Mathematics | ||
| AIME 2023 | — | 66% |
| AIME 2024 | — | 68% |
| AIME 2025 | — | 67% |
| HMMT Feb 2023 | — | 62% |
| HMMT Feb 2024 | — | 64% |
| BRUMO 2025 | — | 65% |
Gemma 4 31B is ahead overall, 73 to 50. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80% and 38%.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 43.6. 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 30.4. 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 62.3. 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 70. GPT-4o stays close enough that the answer can still flip depending on your workload.
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.