Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1-preview
72
Winner · 4/8 categoriesQwen3.6 Plus
69
3/8 categorieso1-preview· Qwen3.6 Plus
Pick o1-preview if you want the stronger benchmark profile. Qwen3.6 Plus only becomes the better choice if instruction following is the priority or you need the larger 1M context window.
o1-preview has the cleaner overall profile here, landing at 72 versus 69. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
o1-preview's sharpest advantage is in reasoning, where it averages 85.4 against 62. The single biggest benchmark swing on the page is LongBench v2, 87% to 62%. Qwen3.6 Plus does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
Qwen3.6 Plus gives you the larger context window at 1M, compared with 200K for o1-preview.
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 | o1-preview | Qwen3.6 Plus |
|---|---|---|
| Agentico1-preview wins | ||
| Terminal-Bench 2.0 | 77% | 61.6% |
| BrowseComp | 79% | — |
| OSWorld-Verified | 71% | 62.5% |
| Claw-Eval | — | 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% |
| CodingQwen3.6 Plus wins | ||
| HumanEval | 86% | — |
| SWE-bench Verified | 65% | 78.8% |
| LiveCodeBench | 60% | — |
| SWE-bench Pro | 69% | 56.6% |
| SWE Multilingual | — | 73.8% |
| LiveCodeBench v6 | — | 87.1% |
| NL2Repo | — | 37.9% |
| Multimodal & GroundedQwen3.6 Plus wins | ||
| MMMU-Pro | 72% | 78.8% |
| OfficeQA Pro | 80% | — |
| MMMU | — | 86.0% |
| 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% |
| Reasoningo1-preview wins | ||
| MuSR | 86% | — |
| BBH | 93% | — |
| LongBench v2 | 87% | 62% |
| MRCRv2 | 83% | — |
| AI-Needle | — | 68.3% |
| Knowledgeo1-preview wins | ||
| MMLU | 92% | — |
| GPQA | 90% | 90.4% |
| SuperGPQA | 88% | 71.6% |
| MMLU-Pro | 80% | 88.5% |
| HLE | 32% | 28.8% |
| FrontierScience | 83% | — |
| SimpleQA | 88% | — |
| MMLU-Redux | — | 94.5% |
| C-Eval | — | 93.3% |
| Instruction FollowingQwen3.6 Plus wins | ||
| IFEval | 88% | 94.3% |
| IFBench | — | 74.2% |
| Multilingualo1-preview wins | ||
| MGSM | 90% | — |
| MMLU-ProX | 86% | 84.7% |
| NOVA-63 | — | 57.9% |
| INCLUDE | — | 85.1% |
| PolyMath | — | 77.4% |
| VWT2k-lite | — | 84.3% |
| MAXIFE | — | 88.2% |
| Mathematics | ||
| AIME 2023 | 94% | — |
| AIME 2024 | 96% | — |
| AIME 2025 | 95% | — |
| HMMT Feb 2023 | 90% | — |
| HMMT Feb 2024 | 92% | — |
| HMMT Feb 2025 | 91% | — |
| BRUMO 2025 | 93% | — |
| MATH-500 | 94% | — |
| AIME26 | — | 95.3% |
| HMMT Feb 2025 | — | 96.7% |
| HMMT Nov 2025 | — | 94.6% |
| HMMT Feb 2026 | — | 87.8% |
| MMAnswerBench | — | 83.8% |
o1-preview is ahead overall, 72 to 69. The biggest single separator in this matchup is LongBench v2, where the scores are 87% and 62%.
o1-preview has the edge for knowledge tasks in this comparison, averaging 72.7 versus 66. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.
Qwen3.6 Plus has the edge for coding in this comparison, averaging 64.9 versus 64.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o1-preview has the edge for reasoning in this comparison, averaging 85.4 versus 62. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
o1-preview has the edge for agentic tasks in this comparison, averaging 75.4 versus 62. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.6 Plus has the edge for multimodal and grounded tasks in this comparison, averaging 78.8 versus 75.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3.6 Plus has the edge for instruction following in this comparison, averaging 94.3 versus 88. Inside this category, IFEval is the benchmark that creates the most daylight between them.
o1-preview has the edge for multilingual tasks in this comparison, averaging 87.4 versus 84.7. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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