1M-Token Context and Agentic Workflow

Z.ai has released GLM-5.2, a significant update to its flagship coding model line. The standout feature is a 1,000,000-token context window, which represents a 5x increase over the previous GLM-5.1 release. This capacity is designed specifically for agentic coding workflows, allowing the model to ingest entire mid-sized repositories—including source code, tests, and configuration files—into its working memory. By eliminating the need for frequent summarization, the model maintains higher coherence during complex, multi-file refactoring or debugging tasks.

Thinking-Effort Levels

GLM-5.2 introduces two distinct "thinking-effort" modes: High and Max. These settings allow developers to calibrate the model's reasoning depth based on task complexity. Z.ai recommends the "Max" effort setting for multi-step coding operations. In tools like Claude Code, this is integrated via the /effort command, where settings such as xhigh, max, and ultracode are now mapped to the model's Max effort level.

Implementation and Compatibility

Despite the lack of public benchmark scores at launch, Z.ai has prioritized immediate integration with existing developer tooling. The model is compatible with eight agentic coding platforms, including Claude Code, Cline, OpenCode, and OpenClaw. Developers can implement the model by updating their ~/.claude/settings.json or by configuring environment variables to point to the Z.ai API endpoint. The model is available to all users on the GLM Coding Plan, ranging from Lite to Team tiers.