Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-OSS 20B
35
1/8 categoriesGranite-4.0-H-1B
~43
Winner · 1/8 categoriesGPT-OSS 20B· Granite-4.0-H-1B
Pick Granite-4.0-H-1B if you want the stronger benchmark profile. GPT-OSS 20B only becomes the better choice if multilingual is the priority.
Granite-4.0-H-1B is clearly ahead on the aggregate, 43 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Granite-4.0-H-1B's sharpest advantage is in knowledge, where it averages 32.6 against 28.7. The single biggest benchmark swing on the page is HumanEval, 23% to 74%. GPT-OSS 20B does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
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 | GPT-OSS 20B | Granite-4.0-H-1B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 35% | — |
| OSWorld-Verified | 31% | — |
| Coding | ||
| HumanEval | 23% | 74% |
| SWE-bench Verified | 14% | — |
| LiveCodeBench | 11% | — |
| SWE-bench Pro | 18% | — |
| React Native Evals | 64.3% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 31% | — |
| OfficeQA Pro | 42% | — |
| Reasoning | ||
| MuSR | 27% | — |
| LongBench v2 | 48% | — |
| MRCRv2 | 48% | — |
| BBH | — | 60.4% |
| KnowledgeGranite-4.0-H-1B wins | ||
| MMLU | 85.3% | 59.4% |
| GPQA | 30% | 29.9% |
| SuperGPQA | 28% | — |
| MMLU-Pro | 53% | 34.0% |
| HLE | 1% | — |
| FrontierScience | 34% | — |
| SimpleQA | 29% | — |
| Instruction Following | ||
| IFEval | — | 77.4% |
| MultilingualGPT-OSS 20B wins | ||
| MGSM | 61% | 37.8% |
| MMLU-ProX | 59% | — |
| Mathematics | ||
| AIME 2023 | 31% | — |
| AIME 2024 | 33% | — |
| AIME 2025 | 32% | — |
| HMMT Feb 2023 | 27% | — |
| HMMT Feb 2024 | 29% | — |
| HMMT Feb 2025 | 28% | — |
| BRUMO 2025 | 30% | — |
| MATH-500 | 59% | — |
Granite-4.0-H-1B is ahead overall, 43 to 35. The biggest single separator in this matchup is HumanEval, where the scores are 23% and 74%.
Granite-4.0-H-1B has the edge for knowledge tasks in this comparison, averaging 32.6 versus 28.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-OSS 20B has the edge for multilingual tasks in this comparison, averaging 59.7 versus 37.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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