Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 4B
~44
Winner · 4/8 categoriesMistral 8x7B v0.2
28
0/8 categories1-bit Bonsai 4B· Mistral 8x7B v0.2
Pick 1-bit Bonsai 4B if you want the stronger benchmark profile. Mistral 8x7B v0.2 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
1-bit Bonsai 4B is clearly ahead on the aggregate, 44 to 28. 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 36.6. The single biggest benchmark swing on the page is MuSR, 41.4% to 25%.
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 | Mistral 8x7B v0.2 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 24% |
| BrowseComp | — | 34% |
| OSWorld-Verified | — | 28% |
| Coding | ||
| HumanEval | — | 21% |
| SWE-bench Verified | — | 16% |
| LiveCodeBench | — | 12% |
| SWE-bench Pro | — | 14% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 26% |
| OfficeQA Pro | — | 40% |
| Reasoning1-bit Bonsai 4B wins | ||
| MuSR | 41.4% | 25% |
| BBH | — | 62% |
| LongBench v2 | — | 39% |
| MRCRv2 | — | 38% |
| Knowledge1-bit Bonsai 4B wins | ||
| GPQA | 28.7% | 28% |
| MMLU | — | 29% |
| SuperGPQA | — | 26% |
| MMLU-Pro | — | 52% |
| HLE | — | 3% |
| FrontierScience | — | 35% |
| SimpleQA | — | 27% |
| Instruction Following1-bit Bonsai 4B wins | ||
| IFEval | 69.6% | 67% |
| Multilingual | ||
| MGSM | — | 62% |
| MMLU-ProX | — | 57% |
| Mathematics1-bit Bonsai 4B wins | ||
| MATH-500 | 65.8% | 59% |
| AIME 2023 | — | 29% |
| AIME 2024 | — | 31% |
| AIME 2025 | — | 30% |
| HMMT Feb 2023 | — | 25% |
| HMMT Feb 2024 | — | 27% |
| HMMT Feb 2025 | — | 26% |
| BRUMO 2025 | — | 28% |
1-bit Bonsai 4B is ahead overall, 44 to 28. The biggest single separator in this matchup is MuSR, where the scores are 41.4% and 25%.
1-bit Bonsai 4B has the edge for knowledge tasks in this comparison, averaging 28.7 versus 28.4. 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 36.6. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
1-bit Bonsai 4B has the edge for reasoning in this comparison, averaging 41.4 versus 34.9. Inside this category, MuSR is the benchmark that creates the most daylight between them.
1-bit Bonsai 4B has the edge for instruction following in this comparison, averaging 69.6 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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