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Zhipu Launches GLM-5-Turbo: First Lobster-Specific Scene Native Model, Self-Developed Benchmark Tops Domestically
Zhipu has officially launched the GLM-5-Turbo base model, specifically optimized for complex Agent scenarios to solve the common industry problem of general large models slowing down during long-chain tasks.
The model incorporates "OpenClaw" scenario-native features from the training phase, boosting core capabilities like tool calling, complex instruction decomposition, scheduled triggers, and high-throughput continuous execution. In Zhipu's proprietary benchmark ZClawBench, GLM-5-Turbo achieved the top spot among domestic models and earned a 90% approval rating in developer blind tests.

As the usage ratio of Skills within the OpenClaw ecosystem surged from 26% to 45%, Agents are transitioning from conversational tools to modular productivity solutions. In response, Zhipu introduced the "OpenClaw Subscription" system and an enterprise security management system (Claw for Enterprise Security), which turns complex multi-Agent collaboration from a "black box" into a visual management process through permission orchestration and real-time monitoring.

The model is now initially integrated into the world's first native AI Agent terminal, the "OpenClaw Box." Starting March 16, 2026, developers can access the corresponding API through Zhipu's open platform, BigModel.cn.
The launch of GLM-5-Turbo signals a shift in the large model competition from mere semantic understanding to end-to-end execution efficiency. By optimizing core capabilities and enhancing commercial support, Zhipu is speeding up the critical transition of large models from "productivity tools" to "enterprise digital workforce," setting a benchmark for the large-scale commercialization of AI Agents.
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Zhipu has officially launched the GLM-5-Turbo base model, specifically optimized for complex Agent scenarios to solve the common industry problem of general large models slowing down during long-chain tasks.
The model incorporates "OpenClaw" scenario-native features from the training phase, boosting core capabilities like tool calling, complex instruction decomposition, scheduled triggers, and high-throughput continuous execution. In Zhipu's proprietary benchmark ZClawBench, GLM-5-Turbo achieved the top spot among domestic models and earned a 90% approval rating in developer blind tests.

As the usage ratio of Skills within the OpenClaw ecosystem surged from 26% to 45%, Agents are transitioning from conversational tools to modular productivity solutions. In response, Zhipu introduced the "OpenClaw Subscription" system and an enterprise security management system (Claw for Enterprise Security), which turns complex multi-Agent collaboration from a "black box" into a visual management process through permission orchestration and real-time monitoring.

The model is now initially integrated into the world's first native AI Agent terminal, the "OpenClaw Box." Starting March 16, 2026, developers can access the corresponding API through Zhipu's open platform, BigModel.cn.
The launch of GLM-5-Turbo signals a shift in the large model competition from mere semantic understanding to end-to-end execution efficiency. By optimizing core capabilities and enhancing commercial support, Zhipu is speeding up the critical transition of large models from "productivity tools" to "enterprise digital workforce," setting a benchmark for the large-scale commercialization of AI Agents.
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Fortune recently featured an interview with Demis Hassabis, CEO of Google DeepMind, revealing his unconventional approach to rest and productivity. Hassabis disclosed that he sleeps very little, structuring his waking hours into two distinct work blo
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