Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E2B
~39
0/8 categoriesQwen2.5-72B
60
Winner · 4/8 categoriesGemma 4 E2B· Qwen2.5-72B
Pick Qwen2.5-72B if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if you want the stronger reasoning-first profile.
Qwen2.5-72B is clearly ahead on the aggregate, 60 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-72B's sharpest advantage is in reasoning, where it averages 73.3 against 19.1. The single biggest benchmark swing on the page is BBH, 21.9% to 81%.
Gemma 4 E2B is the reasoning model in the pair, while Qwen2.5-72B 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 | Qwen2.5-72B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 56% |
| BrowseComp | — | 64% |
| OSWorld-Verified | — | 55% |
| CodingQwen2.5-72B wins | ||
| LiveCodeBench | 44% | 40% |
| HumanEval | — | 75% |
| SWE-bench Verified | — | 46% |
| SWE-bench Pro | — | 47% |
| Multimodal & GroundedQwen2.5-72B wins | ||
| MMMU-Pro | 44.2% | 64% |
| OfficeQA Pro | — | 70% |
| ReasoningQwen2.5-72B wins | ||
| BBH | 21.9% | 81% |
| MRCRv2 | 19.1% | 71% |
| MuSR | — | 78% |
| LongBench v2 | — | 72% |
| KnowledgeQwen2.5-72B wins | ||
| GPQA | 43.4% | 82% |
| MMLU-Pro | 60% | 75% |
| MMLU | — | 83% |
| SuperGPQA | — | 80% |
| HLE | — | 11% |
| FrontierScience | — | 70% |
| SimpleQA | — | 80% |
| Instruction Following | ||
| IFEval | — | 85% |
| Multilingual | ||
| MGSM | — | 84% |
| MMLU-ProX | — | 79% |
| Mathematics | ||
| AIME 2023 | — | 84% |
| AIME 2024 | — | 86% |
| AIME 2025 | — | 85% |
| HMMT Feb 2023 | — | 80% |
| HMMT Feb 2024 | — | 82% |
| HMMT Feb 2025 | — | 81% |
| BRUMO 2025 | — | 83% |
| MATH-500 | — | 84% |
Qwen2.5-72B is ahead overall, 60 to 39. The biggest single separator in this matchup is BBH, where the scores are 21.9% and 81%.
Qwen2.5-72B has the edge for knowledge tasks in this comparison, averaging 61.5 versus 54.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for coding in this comparison, averaging 44.1 versus 44. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for reasoning in this comparison, averaging 73.3 versus 19.1. Inside this category, BBH is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for multimodal and grounded tasks in this comparison, averaging 66.7 versus 44.2. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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