Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
MiMo-V2-Pro
~85
Winner · 3/8 categoriesQwen3.6 Plus
69
0/8 categoriesMiMo-V2-Pro· Qwen3.6 Plus
Pick MiMo-V2-Pro if you want the stronger benchmark profile. Qwen3.6 Plus only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
MiMo-V2-Pro is clearly ahead on the aggregate, 85 to 69. 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 agentic, where it averages 86.7 against 62. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 86.7% to 61.6%.
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-Pro | Qwen3.6 Plus |
|---|---|---|
| AgenticMiMo-V2-Pro wins | ||
| Terminal-Bench 2.0 | 86.7% | 61.6% |
| Claw-Eval | 61.5% | 58.7% |
| QwenClawBench | — | 57.2% |
| QwenWebBench | — | 1502 |
| TAU3-Bench | — | 70.7% |
| VITA-Bench | — | 44.3% |
| DeepPlanning | — | 41.5% |
| Toolathlon | — | 39.8% |
| MCP Atlas | — | 48.2% |
| MCP-Tasks | — | 74.1% |
| WideResearch | — | 74.3% |
| OSWorld-Verified | — | 62.5% |
| CodingMiMo-V2-Pro wins | ||
| SWE-bench Verified | 78% | 78.8% |
| SWE-bench Pro | — | 56.6% |
| SWE Multilingual | — | 73.8% |
| LiveCodeBench v6 | — | 87.1% |
| NL2Repo | — | 37.9% |
| Multimodal & Grounded | ||
| MMMU | — | 86.0% |
| MMMU-Pro | — | 78.8% |
| RealWorldQA | — | 85.4% |
| OmniDocBench 1.5 | — | 91.2% |
| Video-MME (with subtitle) | — | 87.8% |
| Video-MME (w/o subtitle) | — | 84.2% |
| MathVision | — | 88.0% |
| We-Math | — | 89.0% |
| DynaMath | — | 88.0% |
| MStar | — | 83.3% |
| SimpleVQA | — | 67.3% |
| ChatCVQA | — | 81.5% |
| MMLongBench-Doc | — | 62.0% |
| CC-OCR | — | 83.4% |
| AI2D_TEST | — | 94.4% |
| CountBench | — | 97.6% |
| RefCOCO (avg) | — | 93.5% |
| ODINW13 | — | 51.8% |
| ERQA | — | 65.7% |
| VideoMMMU | — | 84.0% |
| MLVU (M-Avg) | — | 86.7% |
| ScreenSpot Pro | — | 68.2% |
| Reasoning | ||
| AI-Needle | — | 68.3% |
| LongBench v2 | — | 62% |
| KnowledgeMiMo-V2-Pro wins | ||
| GPQA | 87% | 90.4% |
| SuperGPQA | — | 71.6% |
| MMLU-Pro | — | 88.5% |
| MMLU-Redux | — | 94.5% |
| C-Eval | — | 93.3% |
| HLE | — | 28.8% |
| Instruction Following | ||
| IFEval | — | 94.3% |
| IFBench | — | 74.2% |
| Multilingual | ||
| MMLU-ProX | — | 84.7% |
| NOVA-63 | — | 57.9% |
| INCLUDE | — | 85.1% |
| PolyMath | — | 77.4% |
| VWT2k-lite | — | 84.3% |
| MAXIFE | — | 88.2% |
| Mathematics | ||
| AIME26 | — | 95.3% |
| HMMT Feb 2025 | — | 96.7% |
| HMMT Nov 2025 | — | 94.6% |
| HMMT Feb 2026 | — | 87.8% |
| MMAnswerBench | — | 83.8% |
MiMo-V2-Pro is ahead overall, 85 to 69. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 86.7% and 61.6%.
MiMo-V2-Pro has the edge for knowledge tasks in this comparison, averaging 87 versus 66. Inside this category, GPQA is the benchmark that creates the most daylight between them.
MiMo-V2-Pro has the edge for coding in this comparison, averaging 78 versus 64.9. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
MiMo-V2-Pro has the edge for agentic tasks in this comparison, averaging 86.7 versus 62. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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