Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.2 (Thinking)
67
1/8 categoriesGemma 4 31B
73
Winner · 3/8 categoriesDeepSeek V3.2 (Thinking)· Gemma 4 31B
Pick Gemma 4 31B if you want the stronger benchmark profile. DeepSeek V3.2 (Thinking) only becomes the better choice if knowledge is the priority.
Gemma 4 31B is clearly ahead on the aggregate, 73 to 67. 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 50.7. The single biggest benchmark swing on the page is LiveCodeBench, 45% to 80%. DeepSeek V3.2 (Thinking) 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 128K for DeepSeek V3.2 (Thinking).
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 | DeepSeek V3.2 (Thinking) | Gemma 4 31B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 71% | — |
| BrowseComp | 70% | — |
| OSWorld-Verified | 67% | — |
| DeepPlanning | 27.4% | — |
| CodingGemma 4 31B wins | ||
| HumanEval | 79% | — |
| SWE-bench Verified | 48% | — |
| LiveCodeBench | 45% | 80% |
| SWE-bench Pro | 58% | — |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 66% | 76.9% |
| ReasoningGemma 4 31B wins | ||
| MuSR | 81% | — |
| BBH | 86% | 74.4% |
| LongBench v2 | 78% | — |
| MRCRv2 | 78% | 66.4% |
| ARC-AGI-2 | 4% | — |
| KnowledgeDeepSeek V3.2 (Thinking) wins | ||
| MMLU | 87% | — |
| GPQA | 85% | 84.3% |
| SuperGPQA | 83% | — |
| MMLU-Pro | 73% | 85.2% |
| HLE | 22% | 26.5% |
| FrontierScience | 77% | — |
| SimpleQA | 83% | — |
| HLE w/o tools | — | 19.5% |
| Instruction Following | ||
| IFEval | 85% | — |
| Multilingual | ||
| MGSM | 84% | — |
| MMLU-ProX | 79% | — |
| Mathematics | ||
| AIME 2023 | 87% | — |
| AIME 2024 | 89% | — |
| AIME 2025 | 88% | — |
| HMMT Feb 2023 | 83% | — |
| HMMT Feb 2024 | 85% | — |
| HMMT Feb 2025 | 84% | — |
| BRUMO 2025 | 86% | — |
| MATH-500 | 84% | — |
Gemma 4 31B is ahead overall, 73 to 67. The biggest single separator in this matchup is LiveCodeBench, where the scores are 45% and 80%.
DeepSeek V3.2 (Thinking) has the edge for knowledge tasks in this comparison, averaging 65.9 versus 61.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 50.7. 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 60.1. 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 66. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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