Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 4B
~44
Winner · 1/8 categoriesGPT-OSS 20B
35
1/8 categories1-bit Bonsai 4B· GPT-OSS 20B
Pick 1-bit Bonsai 4B if you want the stronger benchmark profile. GPT-OSS 20B only becomes the better choice if reasoning is the priority or you need the larger 128K context window.
1-bit Bonsai 4B is clearly ahead on the aggregate, 44 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
1-bit Bonsai 4B's sharpest advantage is in mathematics, where it averages 65.8 against 38.1. The single biggest benchmark swing on the page is MuSR, 41.4% to 27%. GPT-OSS 20B does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
GPT-OSS 20B 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 20B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 35% |
| OSWorld-Verified | — | 31% |
| Coding | ||
| HumanEval | — | 23% |
| SWE-bench Verified | — | 14% |
| LiveCodeBench | — | 11% |
| SWE-bench Pro | — | 18% |
| React Native Evals | — | 64.3% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 31% |
| OfficeQA Pro | — | 42% |
| ReasoningGPT-OSS 20B wins | ||
| MuSR | 41.4% | 27% |
| LongBench v2 | — | 48% |
| MRCRv2 | — | 48% |
| KnowledgeTie | ||
| GPQA | 28.7% | 30% |
| MMLU | — | 85.3% |
| SuperGPQA | — | 28% |
| MMLU-Pro | — | 53% |
| HLE | — | 1% |
| FrontierScience | — | 34% |
| SimpleQA | — | 29% |
| Instruction Following | ||
| IFEval | 69.6% | — |
| Multilingual | ||
| MGSM | — | 61% |
| MMLU-ProX | — | 59% |
| Mathematics1-bit Bonsai 4B wins | ||
| MATH-500 | 65.8% | 59% |
| AIME 2023 | — | 31% |
| AIME 2024 | — | 33% |
| AIME 2025 | — | 32% |
| HMMT Feb 2023 | — | 27% |
| HMMT Feb 2024 | — | 29% |
| HMMT Feb 2025 | — | 28% |
| BRUMO 2025 | — | 30% |
1-bit Bonsai 4B is ahead overall, 44 to 35. The biggest single separator in this matchup is MuSR, where the scores are 41.4% and 27%.
1-bit Bonsai 4B and GPT-OSS 20B are effectively tied for knowledge tasks here, both landing at 28.7 on average.
1-bit Bonsai 4B has the edge for math in this comparison, averaging 65.8 versus 38.1. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GPT-OSS 20B has the edge for reasoning in this comparison, averaging 42.4 versus 41.4. Inside this category, MuSR is the benchmark that creates the most daylight between them.
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