GLM-5.2 Ships With Open Weights, a Million-Token Context, and Dual Reasoning Modes

The GLM team has released GLM-5.2 and published the weights at launch, according to a post from the Russian-language channel AI ML Big Data. The release continues a pattern in which Chinese open-weight labs make frontier-adjacent models available to anyone who can host them.

The main claims are a notable improvement on coding and agentic tasks compared with the previous generation, and a context window expanded to one million tokens, which the post says lets the model hold large amounts of material and run long multi-step workflows. The release comes in two reasoning configurations, including a higher-effort GLM-5.2 max mode for harder problems.

These figures come from the launch announcement, not from independent evaluation. The improvement is described in general terms rather than tied to a named benchmark with a baseline score, and a one-million-token context window is a claim about capacity, not a measure of how well the model actually uses information at the far end of that window. Practitioners should treat the long-context number as a maximum to be tested rather than a delivered capability, and wait for third-party runs on SWE-bench, agent harnesses, and long-context retrieval before drawing comparisons with closed models.