Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-1B
~40
0/8 categoriesMiMo-V2-Pro
~85
Winner · 1/8 categoriesGranite-4.0-1B· MiMo-V2-Pro
Pick MiMo-V2-Pro if you want the stronger benchmark profile. Granite-4.0-1B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
MiMo-V2-Pro is clearly ahead on the aggregate, 85 to 40. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2-Pro's sharpest advantage is in knowledge, where it averages 87 against 31.7. The single biggest benchmark swing on the page is GPQA, 29.7% to 87%.
MiMo-V2-Pro is the reasoning model in the pair, while Granite-4.0-1B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. MiMo-V2-Pro gives you the larger context window at 1M, compared with 128K for Granite-4.0-1B.
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 | Granite-4.0-1B | MiMo-V2-Pro |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 86.7% |
| Coding | ||
| HumanEval | 73% | — |
| SWE-bench Verified | — | 78% |
| Multimodal & Grounded | ||
| Coming soon | ||
| Reasoning | ||
| BBH | 59.7% | — |
| KnowledgeMiMo-V2-Pro wins | ||
| MMLU | 59.7% | — |
| GPQA | 29.7% | 87% |
| MMLU-Pro | 32.9% | — |
| Instruction Following | ||
| IFEval | 78.5% | — |
| Multilingual | ||
| MGSM | 27.5% | — |
| Mathematics | ||
| Coming soon | ||
MiMo-V2-Pro is ahead overall, 85 to 40. The biggest single separator in this matchup is GPQA, where the scores are 29.7% and 87%.
MiMo-V2-Pro has the edge for knowledge tasks in this comparison, averaging 87 versus 31.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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