GLM-5 Turbo (Tencent Cloud)

GLM-5 Turbo is positioned as a foundation model tailored for the OpenClaw "Lobster Agent" use case, with training-phase work aimed squarely at agent behavior rather than general chat. According to Z.AI's developer documentation, the model was specifically optimized for the core requirements of OpenClaw tasks, enhancing tool invocation, command following, timed and persistent tasks, and long-chain execution. This "agent-first" orientation shapes how the model is meant to be deployed: as a base for orchestrating multi-step workflows, persistent state, and external tool calls rather than as a one-shot conversational assistant.

In practical terms, GLM-5 Turbo combines a wide working memory with capabilities that suit complex agent pipelines. The documentation advertises multiple thinking modes for different scenarios, real-time streaming for interactive use, and powerful function calling for integrating external toolsets, alongside structured output support for system integration. CometAPI's 2026 guide similarly highlights the large capacity window, agent primitives baked into training, and a focus on throughput and execution stability, pointing to ClawBench as the natural evaluation surface for this "ClawBench Enhanced Model." The overall fit is teams building long-running, tool-heavy automation where reliable command following and stable execution chains matter more than open-ended dialogue.