Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 2/8 categoriesQwen3.5 397B
68
2/8 categoriesGemma 4 31B· Qwen3.5 397B
Pick Gemma 4 31B if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if knowledge is the priority or 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 68. 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 52.2. The single biggest benchmark swing on the page is LiveCodeBench, 80% to 39%. Qwen3.5 397B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 31B is the reasoning model in the pair, while Qwen3.5 397B 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 Qwen3.5 397B.
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 | Qwen3.5 397B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 52.5% |
| BrowseComp | — | 62% |
| OSWorld-Verified | — | 62.2% |
| Claw-Eval | — | 48.1% |
| QwenClawBench | — | 51.8% |
| QwenWebBench | — | 1162 |
| TAU3-Bench | — | 68.4% |
| DeepPlanning | — | 37.6% |
| Toolathlon | — | 36.3% |
| MCP Atlas | — | 46.1% |
| MCP-Tasks | — | 74.2% |
| WideResearch | — | 74.0% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | 39% |
| HumanEval | — | 75% |
| SWE-bench Verified | — | 76.2% |
| LiveCodeBench v6 | — | 83.6% |
| SWE-bench Pro | — | 50.9% |
| SWE Multilingual | — | 69.3% |
| NL2Repo | — | 32.2% |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 76.9% | 79% |
| OfficeQA Pro | — | 68% |
| RealWorldQA | — | 83.9% |
| Video-MME (w/o subtitle) | — | 84.2% |
| MathVision | — | 88.6% |
| We-Math | — | 87.9% |
| DynaMath | — | 86.3% |
| MStar | — | 83.8% |
| SimpleVQA | — | 67.1% |
| ChatCVQA | — | 80.8% |
| AI2D_TEST | — | 93.9% |
| CountBench | — | 97.2% |
| RefCOCO (avg) | — | 92.3% |
| ODINW13 | — | 47.0% |
| MLVU (M-Avg) | — | 86.7% |
| ScreenSpot Pro | — | 65.6% |
| ReasoningQwen3.5 397B wins | ||
| BBH | 74.4% | 82% |
| MRCRv2 | 66.4% | 71% |
| MuSR | — | 78% |
| LongBench v2 | — | 63.2% |
| AI-Needle | — | 68.7% |
| KnowledgeQwen3.5 397B wins | ||
| GPQA | 84.3% | 88.4% |
| MMLU-Pro | 85.2% | 87.8% |
| HLE | 26.5% | 28.7% |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 83% |
| SuperGPQA | — | 70.4% |
| MMLU-Redux | — | 94.9% |
| C-Eval | — | 93% |
| FrontierScience | — | 71% |
| SimpleQA | — | 80% |
| Instruction Following | ||
| IFEval | — | 92.6% |
| IFBench | — | 76.5% |
| Multilingual | ||
| MGSM | — | 82% |
| MMLU-ProX | — | 84.7% |
| NOVA-63 | — | 59.1% |
| INCLUDE | — | 85.6% |
| PolyMath | — | 73.3% |
| VWT2k-lite | — | 78.9% |
| MAXIFE | — | 88.2% |
| Mathematics | ||
| AIME 2023 | — | 83% |
| AIME 2024 | — | 85% |
| AIME 2025 | — | 84% |
| AIME26 | — | 93.3% |
| HMMT Feb 2023 | — | 79% |
| HMMT Feb 2024 | — | 81% |
| HMMT Feb 2025 | — | 80% |
| HMMT Feb 2025 | — | 94.8% |
| HMMT Nov 2025 | — | 92.7% |
| HMMT Feb 2026 | — | 87.9% |
| MMAnswerBench | — | 80.9% |
| BRUMO 2025 | — | 82% |
| MATH-500 | — | 81% |
Gemma 4 31B is ahead overall, 73 to 68. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80% and 39%.
Qwen3.5 397B has the edge for knowledge tasks in this comparison, averaging 68.2 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 52.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for reasoning in this comparison, averaging 69.7 versus 66.4. 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 74.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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