Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 1.7B
~39
Winner · 1/8 categoriesGLM-4.5-Air
35
2/8 categories1-bit Bonsai 1.7B· GLM-4.5-Air
Pick 1-bit Bonsai 1.7B if you want the stronger benchmark profile. GLM-4.5-Air only becomes the better choice if knowledge is the priority or you need the larger 128K context window.
1-bit Bonsai 1.7B is clearly ahead on the aggregate, 39 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
1-bit Bonsai 1.7B's sharpest advantage is in reasoning, where it averages 45.1 against 44.1. The single biggest benchmark swing on the page is MuSR, 45.1% to 31%. GLM-4.5-Air does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GLM-4.5-Air 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 | GLM-4.5-Air |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 28% |
| OSWorld-Verified | — | 28% |
| Coding | ||
| HumanEval | — | 27% |
| SWE-bench Verified | — | 15% |
| LiveCodeBench | — | 15% |
| SWE-bench Pro | — | 14% |
| SWE-Rebench | — | 38.3% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 36% |
| OfficeQA Pro | — | 44% |
| Reasoning1-bit Bonsai 1.7B wins | ||
| MuSR | 45.1% | 31% |
| BBH | — | 63% |
| LongBench v2 | — | 47% |
| MRCRv2 | — | 51% |
| KnowledgeGLM-4.5-Air wins | ||
| GPQA | 20.7% | 34% |
| MMLU | — | 35% |
| SuperGPQA | — | 32% |
| MMLU-Pro | — | 51% |
| HLE | — | 4% |
| FrontierScience | — | 37% |
| SimpleQA | — | 33% |
| Instruction Following | ||
| IFEval | 63% | — |
| Multilingual | ||
| Coming soon | ||
| MathematicsGLM-4.5-Air wins | ||
| MATH-500 | 34.4% | — |
| AIME 2023 | — | 35% |
| AIME 2024 | — | 37% |
| AIME 2025 | — | 36% |
| HMMT Feb 2023 | — | 31% |
| HMMT Feb 2024 | — | 33% |
| HMMT Feb 2025 | — | 32% |
| BRUMO 2025 | — | 34% |
1-bit Bonsai 1.7B is ahead overall, 39 to 35. The biggest single separator in this matchup is MuSR, where the scores are 45.1% and 31%.
GLM-4.5-Air has the edge for knowledge tasks in this comparison, averaging 31 versus 20.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for math in this comparison, averaging 35.1 versus 34.4. 1-bit Bonsai 1.7B stays close enough that the answer can still flip depending on your workload.
1-bit Bonsai 1.7B has the edge for reasoning in this comparison, averaging 45.1 versus 44.1. Inside this category, MuSR is the benchmark that creates the most daylight between them.
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