Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 26B A4B
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2/8 categorieso3
64
2/8 categoriesGemma 4 26B A4B· o3
Treat this as a split decision. Gemma 4 26B A4B makes more sense if coding is the priority or you want the cheaper token bill; o3 is the better fit if reasoning is the priority.
Gemma 4 26B A4B and o3 finish on the same overall score, so this is less about a single winner and more about where the edge shows up. The headline says tie; the benchmark table is where the real choice happens.
o3 is also the more expensive model on tokens at $10.00 input / $40.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 26B A4B. That is roughly Infinityx on output cost alone. Gemma 4 26B A4B gives you the larger context window at 256K, compared with 200K for o3.
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 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 71% |
| BrowseComp | — | 75% |
| OSWorld-Verified | — | 65% |
| CodingGemma 4 26B A4B wins | ||
| LiveCodeBench | 77.1% | 40% |
| HumanEval | — | 78% |
| SWE-bench Verified | — | 71.7% |
| SWE-bench Pro | — | 58% |
| Multimodal & GroundedGemma 4 26B A4B wins | ||
| MMMU-Pro | 73.8% | 70% |
| OfficeQA Pro | — | 75% |
| VideoMMMU | — | 83.3% |
| Reasoningo3 wins | ||
| BBH | 64.8% | 86% |
| MRCRv2 | 44.1% | 81% |
| MuSR | — | 82% |
| LongBench v2 | — | 82% |
| ARC-AGI-2 | — | 3% |
| Knowledgeo3 wins | ||
| GPQA | 82.3% | — |
| MMLU-Pro | 82.6% | 75% |
| HLE | 17.2% | 24% |
| HLE w/o tools | 8.7% | — |
| MMLU | — | 86% |
| FrontierScience | — | 77% |
| Instruction Following | ||
| IFEval | — | 85% |
| Multilingual | ||
| MGSM | — | 83% |
| MMLU-ProX | — | 80% |
| Mathematics | ||
| AIME 2023 | — | 88% |
| AIME 2024 | — | 90% |
| AIME 2025 | — | 89% |
| HMMT Feb 2023 | — | 84% |
| HMMT Feb 2024 | — | 86% |
| HMMT Feb 2025 | — | 85% |
| BRUMO 2025 | — | 87% |
| MATH-500 | — | 88% |
Gemma 4 26B A4B and o3 are tied on overall score, so the right pick depends on which category matters most for your use case.
o3 has the edge for knowledge tasks in this comparison, averaging 57 versus 56.1. Inside this category, MMLU-Pro 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 54.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
o3 has the edge for reasoning in this comparison, averaging 62 versus 44.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemma 4 26B A4B has the edge for multimodal and grounded tasks in this comparison, averaging 73.8 versus 72.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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