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Summary
GLM 4.7 is a powerful coding model designed to advance the capabilities of artificial intelligence in programming tasks. It builds upon its predecessors by introducing new features such as Interleaved Thinking, Preserved Thinking, and Turn-level Thinking, which enhance the stability and controllability of complex coding assignments. These innovations allow GLM-4.7 to maintain consistency across multiple interactions and provide more reliable, context-aware responses during coding sessions, making it a valuable tool for developers and teams working on intricate software projects.
Key Features
Enhanced Interleaved Thinking for better context handling
Preserved Thinking for consistent multi-turn tasks
Turn-level Thinking for improved task controllability
Strong performance across reasoning, coding, and agent benchmarks
Accessible via Z.ai API and OpenRouter
Public model weights on HuggingFace and ModelScope
Supports local deployment with vLLM and SGLang
Comprehensive documentation and integration guides
About GLM-4.7
The model excels not only in coding but also in a variety of other scenarios, including chat, creative writing, and role-play. It has demonstrated strong performance on numerous benchmarks, often matching or exceeding leading models in reasoning, coding, and agent-based tasks. The detailed benchmark comparisons highlight GLM-4.7's strengths in both general reasoning and specialized coding scenarios, positioning it as a versatile and competitive option in the AI landscape.
GLM-4.7 is accessible through the Z.ai API platform and is also available globally via OpenRouter. Subscribers to the GLM Coding Plan are automatically upgraded to GLM-4.7, and new users can access a Claude-level coding model at a significantly lower cost with a higher usage quota. The model weights are publicly available on HuggingFace and ModelScope, supporting local deployment with frameworks such as vLLM and SGLang. Comprehensive documentation and deployment instructions are provided to ensure smooth integration and usage.
