Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude Opus 4.6
84
Winner · 4/8 categoriesQwen3.5-35B-A3B
67
2/8 categoriesClaude Opus 4.6· Qwen3.5-35B-A3B
Pick Claude Opus 4.6 if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Claude Opus 4.6 is clearly ahead on the aggregate, 84 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.6's sharpest advantage is in reasoning, where it averages 82.4 against 59. The single biggest benchmark swing on the page is LongBench v2, 92% to 59%. Qwen3.5-35B-A3B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Opus 4.6 is also the more expensive model on tokens at $15.00 input / $75.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. Qwen3.5-35B-A3B is the reasoning model in the pair, while Claude Opus 4.6 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Opus 4.6 gives you the larger context window at 1M, compared with 262K for Qwen3.5-35B-A3B.
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 | Claude Opus 4.6 | Qwen3.5-35B-A3B |
|---|---|---|
| AgenticClaude Opus 4.6 wins | ||
| Terminal-Bench 2.0 | 65.4% | 40.5% |
| BrowseComp | 84% | 61% |
| OSWorld-Verified | — | 54.5% |
| tau2-bench | — | 81.2% |
| CodingQwen3.5-35B-A3B wins | ||
| SWE-bench Verified | 80.8% | 69.2% |
| LiveCodeBench | 76% | 74.6% |
| FLTEval | 39.6% | — |
| SWE-Rebench | 65.3% | — |
| React Native Evals | 84.4% | — |
| Multimodal & GroundedClaude Opus 4.6 wins | ||
| MMMU-Pro | 77.3% | 75.1% |
| OfficeQA Pro | 94% | — |
| ReasoningClaude Opus 4.6 wins | ||
| MuSR | 93% | — |
| BBH | 94% | — |
| LongBench v2 | 92% | 59% |
| MRCRv2 | 76% | — |
| ARC-AGI-2 | 68.8% | — |
| KnowledgeQwen3.5-35B-A3B wins | ||
| MMLU | 99% | — |
| GPQA | 91.3% | 84.2% |
| SuperGPQA | 95% | 63.4% |
| MMLU-Pro | 82% | 85.3% |
| HLE | 53% | — |
| FrontierScience | 88% | — |
| SimpleQA | 72% | — |
| Instruction Following | ||
| IFEval | — | 91.9% |
| MultilingualClaude Opus 4.6 wins | ||
| MGSM | 96% | — |
| MMLU-ProX | — | 81% |
| Mathematics | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 98% | — |
| HMMT Feb 2023 | 95% | — |
| HMMT Feb 2024 | 97% | — |
| HMMT Feb 2025 | 96% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | 98% | — |
Claude Opus 4.6 is ahead overall, 84 to 67. The biggest single separator in this matchup is LongBench v2, where the scores are 92% and 59%.
Qwen3.5-35B-A3B has the edge for knowledge tasks in this comparison, averaging 79.3 versus 77.8. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for coding in this comparison, averaging 72.6 versus 72. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Claude Opus 4.6 has the edge for reasoning in this comparison, averaging 82.4 versus 59. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Claude Opus 4.6 has the edge for agentic tasks in this comparison, averaging 72.6 versus 50.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Claude Opus 4.6 has the edge for multimodal and grounded tasks in this comparison, averaging 84.8 versus 75.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Claude Opus 4.6 has the edge for multilingual tasks in this comparison, averaging 96 versus 81. Qwen3.5-35B-A3B stays close enough that the answer can still flip depending on your workload.
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