Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-5
75
Winner · 0/8 categoriesQwen3.6 Plus Preview
Coming soon
0/8 categoriesGLM-5· Qwen3.6 Plus Preview
Benchmark data for GLM-5 and Qwen3.6 Plus Preview is coming soon on BenchLM.
BenchLM does not have sourced benchmark coverage for Qwen3.6 Plus Preview yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Qwen3.6 Plus Preview has the larger context window at 1M, 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 | Qwen3.6 Plus Preview |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 56.2% | — |
| BrowseComp | 62% | — |
| OSWorld-Verified | 58% | — |
| Coding | ||
| HumanEval | 80% | — |
| SWE-bench Verified | 77.8% | — |
| LiveCodeBench | 52% | — |
| SWE-bench Pro | 46% | — |
| SWE-Rebench | 62.8% | — |
| React Native Evals | 74.2% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 66% | — |
| OfficeQA Pro | 73% | — |
| Reasoning | ||
| MuSR | 82% | — |
| BBH | 83% | — |
| LongBench v2 | 77% | — |
| MRCRv2 | 73% | — |
| Knowledge | ||
| MMLU | 91.7% | — |
| GPQA | 86% | — |
| SuperGPQA | 84% | — |
| MMLU-Pro | 82% | — |
| HLE | 30.5% | — |
| FrontierScience | 74% | — |
| SimpleQA | 84% | — |
| Instruction Following | ||
| IFEval | 85% | — |
| Multilingual | ||
| MGSM | 84% | — |
| MMLU-ProX | 81% | — |
| 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% | — |
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
GLM-5: $0.00 input / $0.00 output per 1M tokens Qwen3.6 Plus Preview: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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