Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-1B
~40
1/8 categoriesMoonshot v1
43
Winner · 2/8 categoriesGranite-4.0-1B· Moonshot v1
Pick Moonshot v1 if you want the stronger benchmark profile. Granite-4.0-1B only becomes the better choice if instruction following is the priority.
Moonshot v1 has the cleaner overall profile here, landing at 43 versus 40. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Moonshot v1's sharpest advantage is in multilingual, where it averages 69.8 against 27.5. The single biggest benchmark swing on the page is MGSM, 27.5% to 73%. Granite-4.0-1B does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
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 | Granite-4.0-1B | Moonshot v1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 39% |
| BrowseComp | — | 49% |
| Coding | ||
| HumanEval | 73% | 45% |
| SWE-bench Verified | — | 34% |
| LiveCodeBench | — | 21% |
| SWE-bench Pro | — | 30% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 49% |
| OfficeQA Pro | — | 57% |
| Reasoning | ||
| BBH | 59.7% | 73% |
| MuSR | — | 49% |
| LongBench v2 | — | 58% |
| MRCRv2 | — | 56% |
| KnowledgeMoonshot v1 wins | ||
| MMLU | 59.7% | 53% |
| GPQA | 29.7% | 52% |
| MMLU-Pro | 32.9% | 64% |
| SuperGPQA | — | 50% |
| HLE | — | 5% |
| FrontierScience | — | 49% |
| SimpleQA | — | 51% |
| Instruction FollowingGranite-4.0-1B wins | ||
| IFEval | 78.5% | 77% |
| MultilingualMoonshot v1 wins | ||
| MGSM | 27.5% | 73% |
| MMLU-ProX | — | 68% |
| Mathematics | ||
| AIME 2023 | — | 53% |
| AIME 2024 | — | 55% |
| AIME 2025 | — | 54% |
| HMMT Feb 2023 | — | 49% |
| HMMT Feb 2024 | — | 51% |
| HMMT Feb 2025 | — | 50% |
| BRUMO 2025 | — | 52% |
Moonshot v1 is ahead overall, 43 to 40. The biggest single separator in this matchup is MGSM, where the scores are 27.5% and 73%.
Moonshot v1 has the edge for knowledge tasks in this comparison, averaging 42.9 versus 31.7. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Granite-4.0-1B has the edge for instruction following in this comparison, averaging 78.5 versus 77. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Moonshot v1 has the edge for multilingual tasks in this comparison, averaging 69.8 versus 27.5. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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