Intelligence index
Outperforms 51% of compared models

Compared with GLM-4.5, this generation brings several key improvements:
Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex agentic tasks. Superior coding performance: The model achieves higher scores on code benchmarks and demonstrates better real-world performance in applications such as Claude Code、Cline、Roo Code and Kilo Code, including improvements in generating visually polished front-end pages. Advanced reasoning: GLM-4.6 shows a clear improvement in reasoning performance and supports tool use during inference, leading to stronger overall capability. More capable agents: GLM-4.6 exhibits stronger performance in tool using and search-based agents, and integrates more effectively within agent frameworks. Refined writing: Better aligns with human preferences in style and readability, and performs more naturally in role-playing scenarios.
Outperforms 51% of compared models
Outperforms 48% of compared models
Elo scores and win rates across design and agent tasks.
1105Elo
Win rate 52.1%
1149Elo
Win rate 54.8%
1161Elo
Win rate 52.6%
1126Elo
Win rate 54.2%
1164Elo
Win rate 54.3%
1174Elo
Win rate 54.3%
1142Elo
Win rate 52.5%
1180Elo
Win rate 53.2%
1082Elo
Win rate 52.6%
1029Elo
Win rate 42.3%
1096Elo
Win rate 47.2%