GLM-5-Turbo is a large language model developed by Z.ai (formerly Zhipu AI) as an optimized variant of the flagship GLM-5 architecture. Released in March 2026, the model is specifically engineered for "agentic engineering" and execution-heavy workflows within the OpenClaw ecosystem. Unlike general-purpose chat models, GLM-5-Turbo is positioned as a native execution engine, prioritizing tool-calling stability and multi-step task completion over conversational variety.
The model inherits a Mixture-of-Experts (MoE) architecture, featuring a total of 744 billion parameters with approximately 40 billion active parameters per token. It utilizes DeepSeek Sparse Attention (DSA) to maintain efficiency while supporting a 200,000-token context window and a maximum output capacity of 128,000 tokens. A key technical advancement in its development is the "Slime" asynchronous reinforcement learning framework, which facilitates the training of complex, long-horizon behaviors and improves training throughput.
Key Capabilities and Features
GLM-5-Turbo introduces several features tailored for autonomous agents, including a dedicated Thinking Mode for interleaved reasoning, support for the Model Context Protocol (MCP), and context caching. It is optimized for "timed" and "persistent" tasks, allowing it to maintain coherence across long-running sessions where external tools are frequently invoked. Benchmarks like ZClawBench indicate that the model provides significant improvements in tool-call reliability and instruction decomposition compared to the base GLM-5 model.
For developers, the model supports streaming output and structured formats such as JSON to facilitate integration into production software. While the flagship GLM-5 model is open-source under an MIT license, GLM-5-Turbo is a proprietary, closed-source offering available via API. It focuses on reducing latency and operational costs, offering a cost-effective alternative for enterprise-grade automation, research workflows, and software development tasks.