Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
MiMo-V2-Flash
67
Winner · 2/8 categoriesSarvam 105B
60
3/8 categoriesMiMo-V2-Flash· Sarvam 105B
Pick MiMo-V2-Flash if you want the stronger benchmark profile. Sarvam 105B only becomes the better choice if knowledge is the priority.
MiMo-V2-Flash is clearly ahead on the aggregate, 67 to 60. 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 45. The single biggest benchmark swing on the page is SWE-bench Verified, 73.4% to 45%. Sarvam 105B 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 128K for Sarvam 105B.
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 105B |
|---|---|---|
| AgenticMiMo-V2-Flash wins | ||
| Terminal-Bench 2.0 | 63% | — |
| BrowseComp | 65% | 49.5% |
| OSWorld-Verified | 58% | — |
| Claw-Eval | 48.1% | — |
| CodingMiMo-V2-Flash wins | ||
| HumanEval | 84.8% | — |
| SWE-bench Verified | 73.4% | 45% |
| LiveCodeBench | 80.6% | — |
| SWE-bench Pro | 52% | — |
| SWE Multilingual | 71.7% | — |
| LiveCodeBench v6 | — | 71.7% |
| Multimodal & Grounded | ||
| MMMU-Pro | 78% | — |
| OfficeQA Pro | 73% | — |
| Reasoning | ||
| MuSR | 74% | — |
| BBH | 85% | — |
| LongBench v2 | 60.6% | — |
| MRCRv2 | 73% | — |
| gpqaDiamond | — | 78.7% |
| hle | — | 11.2% |
| KnowledgeSarvam 105B wins | ||
| MMLU | 86.7% | 90.6% |
| GPQA | 83.7% | — |
| SuperGPQA | 76% | — |
| MMLU-Pro | 84.9% | 81.7% |
| HLE | 14% | — |
| FrontierScience | 71% | — |
| SimpleQA | 76% | — |
| Instruction FollowingSarvam 105B wins | ||
| IFEval | 84% | 84.8% |
| Multilingual | ||
| MMLU-ProX | 77% | — |
| MathematicsSarvam 105B wins | ||
| AIME 2023 | 79% | — |
| AIME 2024 | 81% | — |
| AIME 2025 | 94.1% | 88.3% |
| HMMT Feb 2023 | 75% | — |
| HMMT Feb 2024 | 77% | — |
| HMMT Feb 2025 | 76% | — |
| BRUMO 2025 | 78% | — |
| MATH-500 | 90% | 98.6% |
| HMMT Feb 2025 | — | 85.8% |
| HMMT Nov 2025 | — | 85.8% |
MiMo-V2-Flash is ahead overall, 67 to 60. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.4% and 45%.
Sarvam 105B has the edge for knowledge tasks in this comparison, averaging 81.7 versus 63.7. Inside this category, MMLU 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 45. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Sarvam 105B has the edge for math in this comparison, averaging 92.3 versus 87.4. Inside this category, MATH-500 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 49.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Sarvam 105B has the edge for instruction following in this comparison, averaging 84.8 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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