Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 26B A4B
64
1/8 categorieso3-pro
67
Winner · 3/8 categoriesGemma 4 26B A4B· o3-pro
Pick o3-pro if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if coding is the priority or you need the larger 256K context window.
o3-pro has the cleaner overall profile here, landing at 67 versus 64. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
o3-pro's sharpest advantage is in reasoning, where it averages 81.8 against 44.1. The single biggest benchmark swing on the page is MRCRv2, 44.1% to 81%. Gemma 4 26B A4B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemma 4 26B A4B gives you the larger context window at 256K, compared with 200K for o3-pro.
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 26B A4B | o3-pro |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 69% |
| BrowseComp | — | 76% |
| OSWorld-Verified | — | 68% |
| CodingGemma 4 26B A4B wins | ||
| LiveCodeBench | 77.1% | 44% |
| HumanEval | — | 80% |
| SWE-bench Verified | — | 46% |
| SWE-bench Pro | — | 55% |
| Multimodal & Groundedo3-pro wins | ||
| MMMU-Pro | 73.8% | 70% |
| OfficeQA Pro | — | 79% |
| Reasoningo3-pro wins | ||
| BBH | 64.8% | 89% |
| MRCRv2 | 44.1% | 81% |
| MuSR | — | 84% |
| LongBench v2 | — | 81% |
| Knowledgeo3-pro wins | ||
| GPQA | 82.3% | 89% |
| MMLU-Pro | 82.6% | 75% |
| HLE | 17.2% | 26% |
| HLE w/o tools | 8.7% | — |
| MMLU | — | 88% |
| SuperGPQA | — | 87% |
| FrontierScience | — | 77% |
| SimpleQA | — | 86% |
| Instruction Following | ||
| IFEval | — | 82% |
| Multilingual | ||
| MGSM | — | 83% |
| MMLU-ProX | — | 80% |
| Mathematics | ||
| AIME 2023 | — | 90% |
| AIME 2024 | — | 92% |
| AIME 2025 | — | 91% |
| HMMT Feb 2023 | — | 86% |
| HMMT Feb 2024 | — | 88% |
| HMMT Feb 2025 | — | 87% |
| BRUMO 2025 | — | 89% |
| MATH-500 | — | 89% |
o3-pro is ahead overall, 67 to 64. The biggest single separator in this matchup is MRCRv2, where the scores are 44.1% and 81%.
o3-pro has the edge for knowledge tasks in this comparison, averaging 68.6 versus 56.1. Inside this category, HLE is the benchmark that creates the most daylight between them.
Gemma 4 26B A4B has the edge for coding in this comparison, averaging 77.1 versus 48.7. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
o3-pro has the edge for reasoning in this comparison, averaging 81.8 versus 44.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
o3-pro has the edge for multimodal and grounded tasks in this comparison, averaging 74.1 versus 73.8. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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