Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.1
41
Winner · 1/8 categoriesGemma 4 E2B
~39
3/8 categoriesDeepSeek V3.1· Gemma 4 E2B
Pick DeepSeek V3.1 if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
DeepSeek V3.1 has the cleaner overall profile here, landing at 41 versus 39. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
DeepSeek V3.1's sharpest advantage is in reasoning, where it averages 42.1 against 19.1. The single biggest benchmark swing on the page is BBH, 61% to 21.9%. Gemma 4 E2B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemma 4 E2B is the reasoning model in the pair, while DeepSeek V3.1 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.
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 V3.1 | Gemma 4 E2B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 29% | — |
| BrowseComp | 39% | — |
| OSWorld-Verified | 33% | — |
| CodingGemma 4 E2B wins | ||
| HumanEval | 25% | — |
| SWE-bench Verified | 13% | — |
| LiveCodeBench | 15% | 44% |
| SWE-bench Pro | 15% | — |
| Multimodal & GroundedGemma 4 E2B wins | ||
| MMMU-Pro | 35% | 44.2% |
| OfficeQA Pro | 45% | — |
| ReasoningDeepSeek V3.1 wins | ||
| MuSR | 29% | — |
| BBH | 61% | 21.9% |
| LongBench v2 | 46% | — |
| MRCRv2 | 48% | 19.1% |
| KnowledgeGemma 4 E2B wins | ||
| MMLU | 33% | — |
| GPQA | 32% | 43.4% |
| SuperGPQA | 30% | — |
| MMLU-Pro | 53% | 60% |
| HLE | 2% | — |
| FrontierScience | 37% | — |
| SimpleQA | 31% | — |
| Instruction Following | ||
| IFEval | 67% | — |
| Multilingual | ||
| MGSM | 64% | — |
| MMLU-ProX | 59% | — |
| Mathematics | ||
| AIME 2023 | 33% | — |
| AIME 2024 | 35% | — |
| AIME 2025 | 34% | — |
| HMMT Feb 2023 | 29% | — |
| HMMT Feb 2024 | 31% | — |
| HMMT Feb 2025 | 30% | — |
| BRUMO 2025 | 32% | — |
| MATH-500 | 59% | — |
DeepSeek V3.1 is ahead overall, 41 to 39. The biggest single separator in this matchup is BBH, where the scores are 61% and 21.9%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 30.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 E2B has the edge for coding in this comparison, averaging 44 versus 14.5. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
DeepSeek V3.1 has the edge for reasoning in this comparison, averaging 42.1 versus 19.1. Inside this category, BBH is the benchmark that creates the most daylight between them.
Gemma 4 E2B has the edge for multimodal and grounded tasks in this comparison, averaging 44.2 versus 39.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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