GLM-4.7-Flash

from the model card

GLM-4.7-Flash 👋 Join our Discord community. 📖 Check out the GLM-4.7 technical blog, technical report(GLM-4.5). 📍 Use GLM-4.7-Flash API services on Z.ai API Platform. 👉 One click to GLM-4.7. Introduction GLM-4.7-Flash is a 30B-A3B MoE model. As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency. Performances on Benchmarks | Benchmark | GLM-4.7-Flash | Qwen3-30B-A3B-Thinking-2507 | GPT-OSS-20B | |--------------------|---------------|-----------------------------|-------------| | AIME 25 | 91.6 | 85.0 | 91.7 | | GPQA | 75.2 | 73.4 | 71.5 | | LCB v6 | 64.0 | 66.0 | 61.0 | | HLE | 14.4 | 9.8 | 10.9 | | SWE-bench Verified | 59.2 | 22.0 | 34.0 | | τ²-Bench | 79.5 | 49.0 | 47.7 | | BrowseComp | 42.8 | 2.29 | 28.3 | Evaluation Parameters Default Settings (Most Tasks) temperature: 1.0 top-p: 0.95 max new tokens: 131072 For multi-turn agentic tasks (τ²-Bench and Terminal Bench 2), please turn on Preserved Thinking mode. Terminal Bench, SWE Bench Verified temperature: 0.7 top-p: 1.0 max new tokens: 16384 τ^2-Bench Temperature: 0 Max new tokens: 16384 For τ^2-Bench evaluation, we added an additional prompt to the Retail and Telecom user interaction to avoid failure modes caused by users ending the interaction incorrectly. For the Airline domain, we applied the domain fixes as proposed in the Claude Opus…