Key Features

Flagship GLM model focused on long-horizon coding and engineering tasks.
Provides a solid 1M-token context according to Z.ai materials.
Supports flexible thinking-effort levels to balance quality and latency.
Uses IndexShare to reduce sparse-attention per-token FLOPs at long context.
Improves multi-token prediction for speculative decoding acceptance length.
Targets repo-scale implementation, automated research, and performance optimization.
Released with public model resources and API availability.
Benchmarked as a leading open-source model for long-horizon coding tasks.

The model improves coding with flexible thinking-effort levels and introduces architecture changes such as IndexShare for sparse attention efficiency. Z.ai also describes improved multi-token prediction for speculative decoding, with benchmark gains on long-horizon coding and engineering tasks.


GLM-5.2 is useful for developers building coding agents, repository-scale refactoring tools, automated research workflows, and long-context assistants. The model is available through Z.ai surfaces and public model resources, while teams should verify deployment terms and hardware needs before self-hosting.

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