Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.2 (Thinking)
68
1/8 categoriesQwen3.6 Plus
69
Winner · 6/8 categoriesDeepSeek V3.2 (Thinking)· Qwen3.6 Plus
Pick Qwen3.6 Plus if you want the stronger benchmark profile. DeepSeek V3.2 (Thinking) only becomes the better choice if agentic is the priority.
Qwen3.6 Plus finishes one point ahead overall, 69 to 68. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Qwen3.6 Plus's sharpest advantage is in coding, where it averages 64.9 against 50.7. The single biggest benchmark swing on the page is SWE-bench Verified, 48% to 78.8%. DeepSeek V3.2 (Thinking) does hit back in agentic, 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 128K for DeepSeek V3.2 (Thinking).
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 | DeepSeek V3.2 (Thinking) | Qwen3.6 Plus |
|---|---|---|
| AgenticDeepSeek V3.2 (Thinking) wins | ||
| Terminal-Bench 2.0 | 71% | 61.6% |
| BrowseComp | 70% | — |
| OSWorld-Verified | 67% | 62.5% |
| DeepPlanning | 27.4% | 41.5% |
| Claw-Eval | — | 58.7% |
| QwenClawBench | — | 57.2% |
| QwenWebBench | — | 1502 |
| TAU3-Bench | — | 70.7% |
| VITA-Bench | — | 44.3% |
| Toolathlon | — | 39.8% |
| MCP Atlas | — | 48.2% |
| MCP-Tasks | — | 74.1% |
| WideResearch | — | 74.3% |
| CodingQwen3.6 Plus wins | ||
| HumanEval | 79% | — |
| SWE-bench Verified | 48% | 78.8% |
| LiveCodeBench | 45% | — |
| SWE-bench Pro | 58% | 56.6% |
| SWE Multilingual | — | 73.8% |
| LiveCodeBench v6 | — | 87.1% |
| NL2Repo | — | 37.9% |
| Multimodal & GroundedQwen3.6 Plus wins | ||
| MMMU-Pro | 66% | 78.8% |
| OfficeQA Pro | 77% | — |
| 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% |
| ReasoningQwen3.6 Plus wins | ||
| MuSR | 81% | — |
| BBH | 86% | — |
| LongBench v2 | 78% | 62% |
| MRCRv2 | 78% | — |
| ARC-AGI-2 | 4% | — |
| AI-Needle | — | 68.3% |
| KnowledgeQwen3.6 Plus wins | ||
| MMLU | 87% | — |
| GPQA | 85% | 90.4% |
| SuperGPQA | 83% | 71.6% |
| MMLU-Pro | 73% | 88.5% |
| HLE | 22% | 28.8% |
| FrontierScience | 77% | — |
| SimpleQA | 83% | — |
| MMLU-Redux | — | 94.5% |
| C-Eval | — | 93.3% |
| Instruction FollowingQwen3.6 Plus wins | ||
| IFEval | 85% | 94.3% |
| IFBench | — | 74.2% |
| MultilingualQwen3.6 Plus wins | ||
| MGSM | 84% | — |
| MMLU-ProX | 79% | 84.7% |
| NOVA-63 | — | 57.9% |
| INCLUDE | — | 85.1% |
| PolyMath | — | 77.4% |
| VWT2k-lite | — | 84.3% |
| MAXIFE | — | 88.2% |
| Mathematics | ||
| AIME 2023 | 87% | — |
| AIME 2024 | 89% | — |
| AIME 2025 | 88% | — |
| HMMT Feb 2023 | 83% | — |
| HMMT Feb 2024 | 85% | — |
| HMMT Feb 2025 | 84% | — |
| BRUMO 2025 | 86% | — |
| MATH-500 | 84% | — |
| AIME26 | — | 95.3% |
| HMMT Feb 2025 | — | 96.7% |
| HMMT Nov 2025 | — | 94.6% |
| HMMT Feb 2026 | — | 87.8% |
| MMAnswerBench | — | 83.8% |
Qwen3.6 Plus is ahead overall, 69 to 68. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 48% and 78.8%.
Qwen3.6 Plus has the edge for knowledge tasks in this comparison, averaging 66 versus 65.9. Inside this category, MMLU-Pro 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 50.7. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Qwen3.6 Plus has the edge for reasoning in this comparison, averaging 62 versus 60.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for agentic tasks in this comparison, averaging 69.4 versus 62. Inside this category, DeepPlanning 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 71. 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 85. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.6 Plus has the edge for multilingual tasks in this comparison, averaging 84.7 versus 80.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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