Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
2/8 categorieso4-mini (high)
58
Winner · 2/8 categoriesGemma 4 E4B· o4-mini (high)
Pick o4-mini (high) if you want the stronger benchmark profile. Gemma 4 E4B only becomes the better choice if coding is the priority.
o4-mini (high) is clearly ahead on the aggregate, 58 to 47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o4-mini (high)'s sharpest advantage is in reasoning, where it averages 57.2 against 25.4. The single biggest benchmark swing on the page is BBH, 33.1% to 83%. Gemma 4 E4B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
o4-mini (high) gives you the larger context window at 200K, compared with 128K for Gemma 4 E4B.
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 E4B | o4-mini (high) |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 58% |
| BrowseComp | — | 64% |
| OSWorld-Verified | — | 55% |
| CodingGemma 4 E4B wins | ||
| LiveCodeBench | 52% | 34% |
| HumanEval | — | 74% |
| SWE-bench Verified | — | 68.1% |
| SWE-bench Pro | — | 42% |
| Multimodal & Groundedo4-mini (high) wins | ||
| MMMU-Pro | 52.6% | 66% |
| OfficeQA Pro | — | 71% |
| Reasoningo4-mini (high) wins | ||
| BBH | 33.1% | 83% |
| MRCRv2 | 25.4% | 74% |
| MuSR | — | 78% |
| LongBench v2 | — | 75% |
| ARC-AGI-2 | — | 2.4% |
| KnowledgeGemma 4 E4B wins | ||
| GPQA | 58.6% | 82% |
| MMLU-Pro | 69.4% | 76% |
| MMLU | — | 82% |
| SuperGPQA | — | 80% |
| HLE | — | 13% |
| FrontierScience | — | 73% |
| SimpleQA | — | 80% |
| Instruction Following | ||
| IFEval | — | 83% |
| Multilingual | ||
| MGSM | — | 83% |
| MMLU-ProX | — | 81% |
| Mathematics | ||
| AIME 2023 | — | 83% |
| AIME 2024 | — | 93.4% |
| AIME 2025 | — | 92.7% |
| HMMT Feb 2023 | — | 79% |
| HMMT Feb 2024 | — | 81% |
| HMMT Feb 2025 | — | 80% |
| BRUMO 2025 | — | 82% |
| MATH-500 | — | 84% |
o4-mini (high) is ahead overall, 58 to 47. The biggest single separator in this matchup is BBH, where the scores are 33.1% and 83%.
Gemma 4 E4B has the edge for knowledge tasks in this comparison, averaging 65.6 versus 62.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 E4B has the edge for coding in this comparison, averaging 52 versus 44.9. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
o4-mini (high) has the edge for reasoning in this comparison, averaging 57.2 versus 25.4. Inside this category, BBH is the benchmark that creates the most daylight between them.
o4-mini (high) has the edge for multimodal and grounded tasks in this comparison, averaging 68.3 versus 52.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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