Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen3.5-122B-A10B
71
Winner · 7/8 categoriesQwen3.5-35B-A3B
68
0/8 categoriesQwen3.5-122B-A10B· Qwen3.5-35B-A3B
Pick Qwen3.5-122B-A10B if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Qwen3.5-122B-A10B has the cleaner overall profile here, landing at 71 versus 68. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.5-122B-A10B's sharpest advantage is in agentic, where it averages 56 against 50.5. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 49.4% to 40.5%.
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 | Qwen3.5-122B-A10B | Qwen3.5-35B-A3B |
|---|---|---|
| AgenticQwen3.5-122B-A10B wins | ||
| Terminal-Bench 2.0 | 49.4% | 40.5% |
| BrowseComp | 63.8% | 61% |
| OSWorld-Verified | 58% | 54.5% |
| tau2-bench | 79.5% | 81.2% |
| CodingQwen3.5-122B-A10B wins | ||
| SWE-bench Verified | 72% | 69.2% |
| LiveCodeBench | 78.9% | 74.6% |
| Multimodal & GroundedQwen3.5-122B-A10B wins | ||
| MMMU-Pro | 76.9% | 75.1% |
| ReasoningQwen3.5-122B-A10B wins | ||
| LongBench v2 | 60.2% | 59% |
| KnowledgeQwen3.5-122B-A10B wins | ||
| MMLU-Pro | 86.7% | 85.3% |
| SuperGPQA | 67.1% | 63.4% |
| GPQA | 86.6% | 84.2% |
| Instruction FollowingQwen3.5-122B-A10B wins | ||
| IFEval | 93.4% | 91.9% |
| MultilingualQwen3.5-122B-A10B wins | ||
| MMLU-ProX | 82.2% | 81% |
| Mathematics | ||
| Coming soon | ||
Qwen3.5-122B-A10B is ahead overall, 71 to 68. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 49.4% and 40.5%.
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 79.3. 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 72.6. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for reasoning in this comparison, averaging 60.2 versus 59. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for agentic tasks in this comparison, averaging 56 versus 50.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for multimodal and grounded tasks in this comparison, averaging 76.9 versus 75.1. 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 91.9. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for multilingual tasks in this comparison, averaging 82.2 versus 81. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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