Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E2B
~39
0/8 categorieso1
64
Winner · 4/8 categoriesGemma 4 E2B· o1
Pick o1 if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if you want the cheaper token bill.
o1 is clearly ahead on the aggregate, 64 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1's sharpest advantage is in reasoning, where it averages 78.1 against 19.1. The single biggest benchmark swing on the page is MRCRv2, 19.1% to 77%.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 E2B. That is roughly Infinityx on output cost alone. o1 gives you the larger context window at 200K, compared with 128K for Gemma 4 E2B.
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 | o1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 66% |
| BrowseComp | — | 72% |
| OSWorld-Verified | — | 60% |
| Codingo1 wins | ||
| LiveCodeBench | 44% | — |
| SWE-bench Verified | — | 41% |
| SWE-bench Pro | — | 50% |
| Multimodal & Groundedo1 wins | ||
| MMMU-Pro | 44.2% | 68% |
| OfficeQA Pro | — | 74% |
| Reasoningo1 wins | ||
| BBH | 21.9% | — |
| MRCRv2 | 19.1% | 77% |
| LongBench v2 | — | 79% |
| Knowledgeo1 wins | ||
| GPQA | 43.4% | 75.7% |
| MMLU-Pro | 60% | — |
| MMLU | — | 91.8% |
| FrontierScience | — | 65% |
| Instruction Following | ||
| IFEval | — | 92.2% |
| Multilingual | ||
| MMLU-ProX | — | 77% |
| Mathematics | ||
| AIME 2024 | — | 74.3% |
o1 is ahead overall, 64 to 39. The biggest single separator in this matchup is MRCRv2, where the scores are 19.1% and 77%.
o1 has the edge for knowledge tasks in this comparison, averaging 69.3 versus 54.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
o1 has the edge for coding in this comparison, averaging 46.6 versus 44. Gemma 4 E2B stays close enough that the answer can still flip depending on your workload.
o1 has the edge for reasoning in this comparison, averaging 78.1 versus 19.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
o1 has the edge for multimodal and grounded tasks in this comparison, averaging 70.7 versus 44.2. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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