Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 1.7B
~39
0/8 categoriesMistral 8x7B
44
Winner · 4/8 categories1-bit Bonsai 1.7B· Mistral 8x7B
Pick Mistral 8x7B if you want the stronger benchmark profile. 1-bit Bonsai 1.7B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Mistral 8x7B is clearly ahead on the aggregate, 44 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mistral 8x7B's sharpest advantage is in mathematics, where it averages 67.1 against 34.4. The single biggest benchmark swing on the page is GPQA, 20.7% to 64%.
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 1.7B | Mistral 8x7B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 40% |
| BrowseComp | — | 47% |
| OSWorld-Verified | — | 38% |
| Coding | ||
| HumanEval | — | 32.3% |
| SWE-bench Verified | — | 28% |
| LiveCodeBench | — | 23% |
| SWE-bench Pro | — | 28% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 42% |
| OfficeQA Pro | — | 56% |
| ReasoningMistral 8x7B wins | ||
| MuSR | 45.1% | 61% |
| BBH | — | 67.1% |
| LongBench v2 | — | 57% |
| MRCRv2 | — | 53% |
| KnowledgeMistral 8x7B wins | ||
| GPQA | 20.7% | 64% |
| MMLU | — | 71.3% |
| SuperGPQA | — | 62% |
| MMLU-Pro | — | 65% |
| HLE | — | 8% |
| FrontierScience | — | 56% |
| SimpleQA | — | 63% |
| Instruction FollowingMistral 8x7B wins | ||
| IFEval | 63% | 78% |
| Multilingual | ||
| MGSM | — | 74% |
| MMLU-ProX | — | 71% |
| MathematicsMistral 8x7B wins | ||
| MATH-500 | 34.4% | 73% |
| AIME 2023 | — | 65% |
| AIME 2024 | — | 67% |
| AIME 2025 | — | 66% |
| HMMT Feb 2023 | — | 61% |
| HMMT Feb 2024 | — | 63% |
| HMMT Feb 2025 | — | 62% |
| BRUMO 2025 | — | 64% |
Mistral 8x7B is ahead overall, 44 to 39. The biggest single separator in this matchup is GPQA, where the scores are 20.7% and 64%.
Mistral 8x7B has the edge for knowledge tasks in this comparison, averaging 49.5 versus 20.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Mistral 8x7B has the edge for math in this comparison, averaging 67.1 versus 34.4. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Mistral 8x7B has the edge for reasoning in this comparison, averaging 56.7 versus 45.1. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Mistral 8x7B has the edge for instruction following in this comparison, averaging 78 versus 63. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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