GLM-5.2

GLM-5.2 is a large language model developed by Zhipu (also associated with the zai-org and THUDM repository identifiers) as part of its GLM-5 family. It sits within the GLM line of general-purpose models that Zhipu has iterated on across several generations, and is exposed by inference providers under several aliases, including glm-5.2, zai-org/GLM-5.2, THUDM/GLM-5.2, and a separately routed glm-5.2-fast / GLM-5.2-Fast variant. Because the same model name is served by more than one provider, capability is consistent while serving characteristics — throughput, latency, and quantization choices — can differ meaningfully between endpoints. The headline technical specification we track for GLM-5.2 is its 1,000,000-token context window, which places it in the small group of models that can accept very large single-request inputs such as full codebases, long document sets, or extended agent trajectories without external chunking. Independent measurements from Artificial Analysis put output generation at roughly 137 tokens per second with a time to first token near 892 ms, which is a mid-to-fast range for a large model and suggests it is practical for interactive use as well as batch workloads. We do not track a verified benchmark suite (reasoning, coding, or multilingual scores) for this specific version, so buyers comparing it against peers should validate quality on their own tasks. In practice, models in this class are used for long-context retrieval and summarization, repository-scale code analysis, and multi-step agent loops where conversation and tool output accumulate quickly. The main decision points for GLM-5.2 are whether the 1M-token window is genuinely needed for the workload, whether the standard or "fast" variant better matches latency requirements, and how per-provider pricing and throughput compare — see the pricing table on this page for the current provider list.