Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude Opus 4.5
78
Winner · 4/8 categoriesQwen3.5-122B-A10B
71
3/8 categoriesClaude Opus 4.5· Qwen3.5-122B-A10B
Pick Claude Opus 4.5 if you want the stronger benchmark profile. Qwen3.5-122B-A10B only becomes the better choice if coding is the priority or you need the larger 262K context window.
Claude Opus 4.5 is clearly ahead on the aggregate, 78 to 71. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.5's sharpest advantage is in multimodal & grounded, where it averages 90.9 against 76.9. The single biggest benchmark swing on the page is SuperGPQA, 95% to 67.1%. Qwen3.5-122B-A10B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Qwen3.5-122B-A10B is the reasoning model in the pair, while Claude Opus 4.5 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. Qwen3.5-122B-A10B gives you the larger context window at 262K, compared with 200K for Claude Opus 4.5.
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 4.5 | Qwen3.5-122B-A10B |
|---|---|---|
| AgenticClaude Opus 4.5 wins | ||
| Terminal-Bench 2.0 | 59.3% | 49.4% |
| BrowseComp | 73% | 63.8% |
| OSWorld-Verified | 68% | 58% |
| tau2-bench | — | 79.5% |
| CodingQwen3.5-122B-A10B wins | ||
| HumanEval | 91% | — |
| SWE-bench Verified | 80.9% | 72% |
| LiveCodeBench | 57% | 78.9% |
| SWE-bench Pro | 62% | — |
| Multimodal & GroundedClaude Opus 4.5 wins | ||
| MMMU-Pro | 94% | 76.9% |
| OfficeQA Pro | 87% | — |
| ReasoningClaude Opus 4.5 wins | ||
| MuSR | 93% | — |
| BBH | 87% | — |
| LongBench v2 | 82% | 60.2% |
| MRCRv2 | 81% | — |
| ARC-AGI-2 | 37.6% | — |
| KnowledgeQwen3.5-122B-A10B wins | ||
| MMLU | 90.8% | — |
| GPQA | 87% | 86.6% |
| SuperGPQA | 95% | 67.1% |
| MMLU-Pro | 81% | 86.7% |
| HLE | 20% | — |
| FrontierScience | 84% | — |
| SimpleQA | 95% | — |
| Instruction FollowingQwen3.5-122B-A10B wins | ||
| IFEval | 90% | 93.4% |
| MultilingualClaude Opus 4.5 wins | ||
| MGSM | 90% | — |
| MMLU-ProX | 84% | 82.2% |
| 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 | 89% | — |
Claude Opus 4.5 is ahead overall, 78 to 71. The biggest single separator in this matchup is SuperGPQA, where the scores are 95% and 67.1%.
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 71.7. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for coding in this comparison, averaging 76.3 versus 64.4. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for reasoning in this comparison, averaging 72.9 versus 60.2. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for agentic tasks in this comparison, averaging 65.8 versus 56. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for multimodal and grounded tasks in this comparison, averaging 90.9 versus 76.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for instruction following in this comparison, averaging 93.4 versus 90. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for multilingual tasks in this comparison, averaging 86.1 versus 82.2. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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