Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude Haiku 4.5
63
Winner · 3/8 categoriesGranite-4.0-H-1B
~43
0/8 categoriesClaude Haiku 4.5· Granite-4.0-H-1B
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. Granite-4.0-H-1B only becomes the better choice if you want the cheaper token bill.
Claude Haiku 4.5 is clearly ahead on the aggregate, 63 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Haiku 4.5's sharpest advantage is in multilingual, where it averages 80.1 against 37.8. The single biggest benchmark swing on the page is MGSM, 82% to 37.8%.
Claude Haiku 4.5 is also the more expensive model on tokens at $0.80 input / $4.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Granite-4.0-H-1B. That is roughly Infinityx on output cost alone. Claude Haiku 4.5 gives you the larger context window at 200K, compared with 128K for Granite-4.0-H-1B.
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 | Claude Haiku 4.5 | Granite-4.0-H-1B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 41% | — |
| BrowseComp | 62% | — |
| OSWorld-Verified | 57% | — |
| Coding | ||
| HumanEval | 60% | 74% |
| SWE-bench Verified | 73.3% | — |
| LiveCodeBench | 36% | — |
| SWE-bench Pro | 46% | — |
| FLTEval | 23% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 82% | — |
| OfficeQA Pro | 74% | — |
| Reasoning | ||
| MuSR | 63% | — |
| BBH | 81% | 60.4% |
| LongBench v2 | 72% | — |
| MRCRv2 | 70% | — |
| KnowledgeClaude Haiku 4.5 wins | ||
| MMLU | 68% | 59.4% |
| GPQA | 67% | 29.9% |
| SuperGPQA | 65% | — |
| MMLU-Pro | 73% | 34.0% |
| HLE | 11% | — |
| FrontierScience | 64% | — |
| SimpleQA | 65% | — |
| Instruction FollowingClaude Haiku 4.5 wins | ||
| IFEval | 86% | 77.4% |
| MultilingualClaude Haiku 4.5 wins | ||
| MGSM | 82% | 37.8% |
| MMLU-ProX | 79% | — |
| Mathematics | ||
| AIME 2023 | 68% | — |
| AIME 2024 | 70% | — |
| AIME 2025 | 69% | — |
| HMMT Feb 2023 | 64% | — |
| HMMT Feb 2024 | 66% | — |
| HMMT Feb 2025 | 65% | — |
| BRUMO 2025 | 67% | — |
| MATH-500 | 81% | — |
Claude Haiku 4.5 is ahead overall, 63 to 43. The biggest single separator in this matchup is MGSM, where the scores are 82% and 37.8%.
Claude Haiku 4.5 has the edge for knowledge tasks in this comparison, averaging 54.4 versus 32.6. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for instruction following in this comparison, averaging 86 versus 77.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for multilingual tasks in this comparison, averaging 80.1 versus 37.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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