Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-5
75
Winner · 2/8 categoriesQwen3.5-122B-A10B
71
5/8 categoriesGLM-5· Qwen3.5-122B-A10B
Pick GLM-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.
GLM-5 is clearly ahead on the aggregate, 75 to 71. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5's sharpest advantage is in reasoning, where it averages 77 against 60.2. The single biggest benchmark swing on the page is LiveCodeBench, 52% to 78.9%. 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 GLM-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 GLM-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 | GLM-5 | Qwen3.5-122B-A10B |
|---|---|---|
| AgenticGLM-5 wins | ||
| Terminal-Bench 2.0 | 56.2% | 49.4% |
| BrowseComp | 62% | 63.8% |
| OSWorld-Verified | 58% | 58% |
| tau2-bench | — | 79.5% |
| CodingQwen3.5-122B-A10B wins | ||
| HumanEval | 80% | — |
| SWE-bench Verified | 77.8% | 72% |
| LiveCodeBench | 52% | 78.9% |
| SWE-bench Pro | 46% | — |
| SWE-Rebench | 62.8% | — |
| React Native Evals | 74.2% | — |
| Multimodal & GroundedQwen3.5-122B-A10B wins | ||
| MMMU-Pro | 66% | 76.9% |
| OfficeQA Pro | 73% | — |
| ReasoningGLM-5 wins | ||
| MuSR | 82% | — |
| BBH | 83% | — |
| LongBench v2 | 77% | 60.2% |
| MRCRv2 | 73% | — |
| KnowledgeQwen3.5-122B-A10B wins | ||
| MMLU | 91.7% | — |
| GPQA | 86% | 86.6% |
| SuperGPQA | 84% | 67.1% |
| MMLU-Pro | 82% | 86.7% |
| HLE | 30.5% | — |
| FrontierScience | 74% | — |
| SimpleQA | 84% | — |
| Instruction FollowingQwen3.5-122B-A10B wins | ||
| IFEval | 85% | 93.4% |
| MultilingualQwen3.5-122B-A10B wins | ||
| MGSM | 84% | — |
| MMLU-ProX | 81% | 82.2% |
| Mathematics | ||
| AIME 2023 | 88% | — |
| AIME 2024 | 90% | — |
| AIME 2025 | 93.3% | — |
| HMMT Feb 2023 | 84% | — |
| HMMT Feb 2024 | 86% | — |
| HMMT Feb 2025 | 85% | — |
| BRUMO 2025 | 87% | — |
| MATH-500 | 97.4% | — |
GLM-5 is ahead overall, 75 to 71. The biggest single separator in this matchup is LiveCodeBench, where the scores are 52% and 78.9%.
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 69.7. 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 58.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GLM-5 has the edge for reasoning in this comparison, averaging 77 versus 60.2. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GLM-5 has the edge for agentic tasks in this comparison, averaging 58.3 versus 56. 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 69.2. 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 85. 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 82.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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