
An AI foundation model optimized for complex, dynamic, and long-chain agent tasks.
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The 'OpenClaw scenario' refers to complex, dynamic, and long-chain agent workflows that involve tasks like environment setup, software development, information retrieval, data analysis, and content creation, often requiring interaction with external tools and persistent execution.
GLM-5-Turbo is specifically optimized for 'Scheduled and Persistent Tasks,' meaning it has a better understanding of time-related requirements and can maintain execution continuity during complex, long-running tasks, including those with scheduled triggers.
ZClawBench is an end-to-end benchmark designed specifically for evaluating model performance in agent tasks within the OpenClaw ecosystem. GLM-5-Turbo has shown substantial improvements over previous models in OpenClaw scenarios when evaluated against ZClawBench.
Yes, GLM-5-Turbo features 'Function Call' capabilities for powerful tool invocation and 'MCP Integration' to flexibly integrate external MCP tools and data sources, expanding its use cases and enabling interaction with various external systems.
GLM-5-Turbo supports a context length of 200K tokens and a maximum output of 128K tokens, allowing it to process and generate extensive responses for complex tasks.
Yes, GLM-5-Turbo supports 'Streaming Output,' which enables real-time streaming responses to enhance the user interaction experience, making it suitable for applications requiring immediate feedback.
Source: docs.z.ai