Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-350M
~27
0/8 categoriesMoonshot v1
43
Winner · 3/8 categoriesGranite-4.0-350M· Moonshot v1
Pick Moonshot v1 if you want the stronger benchmark profile. Granite-4.0-350M only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Moonshot v1 is clearly ahead on the aggregate, 43 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Moonshot v1's sharpest advantage is in multilingual, where it averages 69.8 against 16.2. The single biggest benchmark swing on the page is MGSM, 16.2% to 73%.
Moonshot v1 gives you the larger context window at 128K, compared with 32K for Granite-4.0-350M.
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-4.0-350M | Moonshot v1 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 39% |
| BrowseComp | — | 49% |
| Coding | ||
| HumanEval | 38% | 45% |
| SWE-bench Verified | — | 34% |
| LiveCodeBench | — | 21% |
| SWE-bench Pro | — | 30% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 49% |
| OfficeQA Pro | — | 57% |
| Reasoning | ||
| BBH | 33.3% | 73% |
| MuSR | — | 49% |
| LongBench v2 | — | 58% |
| MRCRv2 | — | 56% |
| KnowledgeMoonshot v1 wins | ||
| MMLU | 36.2% | 53% |
| GPQA | 26.1% | 52% |
| MMLU-Pro | 14.4% | 64% |
| SuperGPQA | — | 50% |
| HLE | — | 5% |
| FrontierScience | — | 49% |
| SimpleQA | — | 51% |
| Instruction FollowingMoonshot v1 wins | ||
| IFEval | 61.6% | 77% |
| MultilingualMoonshot v1 wins | ||
| MGSM | 16.2% | 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 27. The biggest single separator in this matchup is MGSM, where the scores are 16.2% and 73%.
Moonshot v1 has the edge for knowledge tasks in this comparison, averaging 42.9 versus 18.5. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Moonshot v1 has the edge for instruction following in this comparison, averaging 77 versus 61.6. 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 16.2. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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