GLM-4.5 is a large language model foundation designed for agentic, reasoning, and coding tasks.
The project addresses the need for models that can handle complex multi-step workflows, mathematical reasoning, and software engineering challenges. GLM-4.5 introduces interleaved thinking, where the model reasons before each response and tool call to improve instruction following and generation quality. The architecture supports mixture-of-experts routing and is optimized for scenarios requiring extended reasoning chains and agent-based interactions.
Developers should adopt this tool if they are building coding agents, require strong mathematical reasoning capabilities, or need a model that can maintain reasoning consistency across multi-turn conversations. The project suits applications involving software engineering tasks, complex problem-solving, and interactive coding assistance. The repository includes technical documentation, API access information, and community channels for support, making it accessible for teams integrating the model into production systems.
The project maintains active development with regular model iterations, as evidenced by multiple versions released with incremental improvements across coding benchmarks, reasoning tasks, and tool-use capabilities. Documentation is comprehensive and available in multiple languages, supporting broad adoption. The team provides both full-scale and lightweight model variants to accommodate different deployment scenarios and performance requirements.
