Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 1.7B
~39
0/8 categoriesZ-1
44
Winner · 4/8 categories1-bit Bonsai 1.7B· Z-1
Pick Z-1 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.
Z-1 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.
Z-1's sharpest advantage is in mathematics, where it averages 57.3 against 34.4. The single biggest benchmark swing on the page is MATH-500, 34.4% to 73%.
Z-1 gives you the larger context window at 128K, compared with 32K for 1-bit Bonsai 1.7B.
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 | Z-1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 39% |
| BrowseComp | — | 49% |
| OSWorld-Verified | — | 41% |
| Coding | ||
| HumanEval | — | 44% |
| SWE-bench Verified | — | 33% |
| LiveCodeBench | — | 22% |
| SWE-bench Pro | — | 30% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 46% |
| OfficeQA Pro | — | 56% |
| ReasoningZ-1 wins | ||
| MuSR | 45.1% | 48% |
| BBH | — | 74% |
| LongBench v2 | — | 56% |
| MRCRv2 | — | 57% |
| KnowledgeZ-1 wins | ||
| GPQA | 20.7% | 51% |
| MMLU | — | 52% |
| SuperGPQA | — | 49% |
| MMLU-Pro | — | 64% |
| HLE | — | 6% |
| FrontierScience | — | 51% |
| SimpleQA | — | 50% |
| Instruction FollowingZ-1 wins | ||
| IFEval | 63% | 80% |
| Multilingual | ||
| MGSM | — | 74% |
| MMLU-ProX | — | 72% |
| MathematicsZ-1 wins | ||
| MATH-500 | 34.4% | 73% |
| AIME 2023 | — | 52% |
| AIME 2024 | — | 54% |
| AIME 2025 | — | 53% |
| HMMT Feb 2023 | — | 48% |
| HMMT Feb 2024 | — | 50% |
| HMMT Feb 2025 | — | 49% |
| BRUMO 2025 | — | 51% |
Z-1 is ahead overall, 44 to 39. The biggest single separator in this matchup is MATH-500, where the scores are 34.4% and 73%.
Z-1 has the edge for knowledge tasks in this comparison, averaging 43.1 versus 20.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Z-1 has the edge for math in this comparison, averaging 57.3 versus 34.4. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Z-1 has the edge for reasoning in this comparison, averaging 54.2 versus 45.1. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Z-1 has the edge for instruction following in this comparison, averaging 80 versus 63. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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