Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
MiMo-V2-Flash
67
Winner · 3/8 categoriesSarvam 30B
48
1/8 categoriesMiMo-V2-Flash· Sarvam 30B
Pick MiMo-V2-Flash if you want the stronger benchmark profile. Sarvam 30B only becomes the better choice if knowledge is the priority.
MiMo-V2-Flash is clearly ahead on the aggregate, 67 to 48. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2-Flash's sharpest advantage is in coding, where it averages 67.9 against 34. The single biggest benchmark swing on the page is SWE-bench Verified, 73.4% to 34%. Sarvam 30B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
MiMo-V2-Flash gives you the larger context window at 256K, compared with 64K for Sarvam 30B.
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 | MiMo-V2-Flash | Sarvam 30B |
|---|---|---|
| AgenticMiMo-V2-Flash wins | ||
| Terminal-Bench 2.0 | 63% | — |
| BrowseComp | 65% | 35.5% |
| OSWorld-Verified | 58% | — |
| Claw-Eval | 48.1% | — |
| CodingMiMo-V2-Flash wins | ||
| HumanEval | 84.8% | 92.1% |
| SWE-bench Verified | 73.4% | 34% |
| LiveCodeBench | 80.6% | — |
| SWE-bench Pro | 52% | — |
| SWE Multilingual | 71.7% | — |
| LiveCodeBench v6 | — | 70.0% |
| Multimodal & Grounded | ||
| MMMU-Pro | 78% | — |
| OfficeQA Pro | 73% | — |
| Reasoning | ||
| MuSR | 74% | — |
| BBH | 85% | — |
| LongBench v2 | 60.6% | — |
| MRCRv2 | 73% | — |
| gpqaDiamond | — | 66.5% |
| KnowledgeSarvam 30B wins | ||
| MMLU | 86.7% | 85.1% |
| GPQA | 83.7% | — |
| SuperGPQA | 76% | — |
| MMLU-Pro | 84.9% | 80% |
| HLE | 14% | — |
| FrontierScience | 71% | — |
| SimpleQA | 76% | — |
| Instruction Following | ||
| IFEval | 84% | — |
| Multilingual | ||
| MMLU-ProX | 77% | — |
| MathematicsMiMo-V2-Flash wins | ||
| AIME 2023 | 79% | — |
| AIME 2024 | 81% | — |
| AIME 2025 | 94.1% | 80% |
| HMMT Feb 2023 | 75% | — |
| HMMT Feb 2024 | 77% | — |
| HMMT Feb 2025 | 76% | — |
| BRUMO 2025 | 78% | — |
| MATH-500 | 90% | 97% |
| HMMT Feb 2025 | — | 73.3% |
| HMMT Nov 2025 | — | 74.2% |
MiMo-V2-Flash is ahead overall, 67 to 48. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.4% and 34%.
Sarvam 30B has the edge for knowledge tasks in this comparison, averaging 80 versus 63.7. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
MiMo-V2-Flash has the edge for coding in this comparison, averaging 67.9 versus 34. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
MiMo-V2-Flash has the edge for math in this comparison, averaging 87.4 versus 86.5. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
MiMo-V2-Flash has the edge for agentic tasks in this comparison, averaging 61.8 versus 35.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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