Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 1.7B
~39
0/8 categoriesClaude 3 Haiku
42
Winner · 4/8 categories1-bit Bonsai 1.7B· Claude 3 Haiku
Pick Claude 3 Haiku 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.
Claude 3 Haiku has the cleaner overall profile here, landing at 42 versus 39. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Claude 3 Haiku's sharpest advantage is in mathematics, where it averages 59.8 against 34.4. The single biggest benchmark swing on the page is MATH-500, 34.4% to 71%.
Claude 3 Haiku gives you the larger context window at 200K, 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 | Claude 3 Haiku |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 40% |
| BrowseComp | — | 53% |
| OSWorld-Verified | — | 42% |
| Coding | ||
| HumanEval | — | 73% |
| SWE-bench Verified | — | 17% |
| LiveCodeBench | — | 20% |
| SWE-bench Pro | — | 19% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 70% |
| OfficeQA Pro | — | 67% |
| ReasoningClaude 3 Haiku wins | ||
| MuSR | 45.1% | 52% |
| BBH | — | 74% |
| LongBench v2 | — | 63% |
| MRCRv2 | — | 63% |
| KnowledgeClaude 3 Haiku wins | ||
| GPQA | 20.7% | 56% |
| MMLU | — | 75.2% |
| SuperGPQA | — | 54% |
| MMLU-Pro | — | 63% |
| HLE | — | 2% |
| FrontierScience | — | 50% |
| SimpleQA | — | 54% |
| Instruction FollowingClaude 3 Haiku wins | ||
| IFEval | 63% | 76% |
| Multilingual | ||
| MGSM | — | 73% |
| MMLU-ProX | — | 70% |
| MathematicsClaude 3 Haiku wins | ||
| MATH-500 | 34.4% | 71% |
| AIME 2023 | — | 56% |
| AIME 2024 | — | 58% |
| AIME 2025 | — | 57% |
| HMMT Feb 2023 | — | 52% |
| HMMT Feb 2024 | — | 54% |
| HMMT Feb 2025 | — | 53% |
| BRUMO 2025 | — | 55% |
Claude 3 Haiku is ahead overall, 42 to 39. The biggest single separator in this matchup is MATH-500, where the scores are 34.4% and 71%.
Claude 3 Haiku has the edge for knowledge tasks in this comparison, averaging 43.5 versus 20.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Claude 3 Haiku has the edge for math in this comparison, averaging 59.8 versus 34.4. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Claude 3 Haiku has the edge for reasoning in this comparison, averaging 60.1 versus 45.1. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Claude 3 Haiku has the edge for instruction following in this comparison, averaging 76 versus 63. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.