Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 4B
~44
1/8 categoriesGPT-OSS 120B
51
Winner · 3/8 categories1-bit Bonsai 4B· GPT-OSS 120B
Pick GPT-OSS 120B if you want the stronger benchmark profile. 1-bit Bonsai 4B only becomes the better choice if mathematics is the priority.
GPT-OSS 120B is clearly ahead on the aggregate, 51 to 44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-OSS 120B's sharpest advantage is in knowledge, where it averages 51.6 against 28.7. The single biggest benchmark swing on the page is GPQA, 28.7% to 80.9%. 1-bit Bonsai 4B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-OSS 120B gives you the larger context window at 128K, compared with 32K for 1-bit Bonsai 4B.
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 | 1-bit Bonsai 4B | GPT-OSS 120B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 43% |
| BrowseComp | — | 50% |
| OSWorld-Verified | — | 43% |
| Coding | ||
| HumanEval | — | 43% |
| SWE-bench Verified | — | 29% |
| LiveCodeBench | — | 25% |
| SWE-bench Pro | — | 31% |
| SWE-Rebench | — | 33.3% |
| React Native Evals | — | 66.4% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 42% |
| OfficeQA Pro | — | 57% |
| ReasoningGPT-OSS 120B wins | ||
| MuSR | 41.4% | 47% |
| BBH | — | 73% |
| LongBench v2 | — | 58% |
| MRCRv2 | — | 59% |
| KnowledgeGPT-OSS 120B wins | ||
| GPQA | 28.7% | 80.9% |
| MMLU | — | 90% |
| SuperGPQA | — | 48% |
| MMLU-Pro | — | 90% |
| HLE | — | 5% |
| FrontierScience | — | 49% |
| SimpleQA | — | 49% |
| Instruction FollowingGPT-OSS 120B wins | ||
| IFEval | 69.6% | 79% |
| Multilingual | ||
| MGSM | — | 72% |
| MMLU-ProX | — | 70% |
| Mathematics1-bit Bonsai 4B wins | ||
| MATH-500 | 65.8% | 71% |
| AIME 2023 | — | 51% |
| AIME 2024 | — | 53% |
| AIME 2025 | — | 52% |
| HMMT Feb 2023 | — | 47% |
| HMMT Feb 2024 | — | 49% |
| HMMT Feb 2025 | — | 48% |
| BRUMO 2025 | — | 50% |
GPT-OSS 120B is ahead overall, 51 to 44. The biggest single separator in this matchup is GPQA, where the scores are 28.7% and 80.9%.
GPT-OSS 120B has the edge for knowledge tasks in this comparison, averaging 51.6 versus 28.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
1-bit Bonsai 4B has the edge for math in this comparison, averaging 65.8 versus 56.1. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GPT-OSS 120B has the edge for reasoning in this comparison, averaging 55.4 versus 41.4. Inside this category, MuSR is the benchmark that creates the most daylight between them.
GPT-OSS 120B has the edge for instruction following in this comparison, averaging 79 versus 69.6. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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