Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E2B
~39
3/8 categoriesQwen3 235B 2507
47
Winner · 1/8 categoriesGemma 4 E2B· Qwen3 235B 2507
Pick Qwen3 235B 2507 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.
Qwen3 235B 2507 is clearly ahead on the aggregate, 47 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3 235B 2507's sharpest advantage is in reasoning, where it averages 47.5 against 19.1. The single biggest benchmark swing on the page is BBH, 21.9% to 60%. 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 Qwen3 235B 2507 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 | Gemma 4 E2B | Qwen3 235B 2507 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 33% |
| BrowseComp | — | 40% |
| OSWorld-Verified | — | 30% |
| CodingGemma 4 E2B wins | ||
| LiveCodeBench | 44% | 51.8% |
| HumanEval | — | 31% |
| SWE-bench Verified | — | 15% |
| SWE-bench Pro | — | 19% |
| Multimodal & GroundedGemma 4 E2B wins | ||
| MMMU-Pro | 44.2% | 38% |
| OfficeQA Pro | — | 46% |
| ReasoningQwen3 235B 2507 wins | ||
| BBH | 21.9% | 60% |
| MRCRv2 | 19.1% | 52% |
| MuSR | — | 35% |
| LongBench v2 | — | 52% |
| KnowledgeGemma 4 E2B wins | ||
| GPQA | 43.4% | 77.5% |
| MMLU-Pro | 60% | 83% |
| MMLU | — | 39% |
| SuperGPQA | — | 62.6% |
| HLE | — | 1% |
| FrontierScience | — | 39% |
| SimpleQA | — | 54.3% |
| Instruction Following | ||
| IFEval | — | 88.7% |
| Multilingual | ||
| MGSM | — | 63% |
| MMLU-ProX | — | 79.4% |
| Mathematics | ||
| AIME 2023 | — | 39% |
| AIME 2024 | — | 41% |
| AIME 2025 | — | 70.3% |
| HMMT Feb 2023 | — | 35% |
| HMMT Feb 2024 | — | 37% |
| HMMT Feb 2025 | — | 36% |
| BRUMO 2025 | — | 38% |
| MATH-500 | — | 57% |
Qwen3 235B 2507 is ahead overall, 47 to 39. The biggest single separator in this matchup is BBH, where the scores are 21.9% and 60%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 49.4. 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 30.7. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 has the edge for reasoning in this comparison, averaging 47.5 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 41.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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