OpenRouter has listed Z.ai’s GLM-5.2 as a newly released model with a 1 million-token context window and usage-based pricing, while Z.AI’s own documentation describes the model as a flagship text system for long-horizon reasoning, coding, tool use and structured-output workflows.
OpenRouter has listed Z.ai’s GLM-5.2 as released on June 16, 2026, describing it as a model aimed at long-horizon agent and coding workflows with a 1 million-token context window. The OpenRouter listing also shows pricing of $1.40 per 1 million input tokens and $4.40 per 1 million output tokens.
Z.AI’s developer documentation separately describes GLM-5.2 as a flagship text model designed for long-horizon tasks. According to the Z.AI overview, the model supports a 1 million-token context length and up to 128,000 output tokens, placing it in the category of models intended to handle very large documents, extended conversations and multi-step coding or agent tasks.
Z.AI’s GLM-5.2 overview lists several capabilities relevant to production AI applications. The documentation says the model supports a “thinking mode,” function calling, context caching, structured output and MCP support. Those features suggest the model is being positioned not only for chat-style use, but also for applications that coordinate tools, preserve long context and return responses in predictable formats.
Function calling is typically used to let a language model request external actions through predefined interfaces, while structured output helps applications receive machine-readable responses rather than free-form text. Z.AI’s mention of context caching is also notable for long-context use cases, because caching can reduce repeated processing when an application reuses the same large prompt or document context across multiple requests.
The Z.AI documentation’s stated 128,000-token maximum output length is unusually large relative to many mainstream API models, though developers would still need to consider latency, cost and reliability when using very long completions in real applications.
The official Hugging Face page for zai-org/GLM-5.2 lists the model under an MIT license. The Hugging Face description calls GLM-5.2 Z.ai’s latest flagship model and highlights a “solid 1M context,” flexible coding effort levels and IndexShare architecture improvements.
The MIT license listing is significant for developers and companies evaluating deployment options, because it is generally associated with permissive use. However, implementers should still review the full model card, repository files and any accompanying usage terms before deploying the model commercially or in regulated settings.
Taken together, the OpenRouter listing, Z.AI documentation and Hugging Face model page present GLM-5.2 as a long-context model aimed at agentic workflows, software engineering tasks and document-heavy applications. The 1 million-token context window is the central technical claim across the OpenRouter listing and Z.AI’s own materials.
For developers, a context window of that size can make it easier to place large codebases, research files, policy documents or conversation histories into a single model session. The practical value will depend on model quality across the full context, retrieval strategy, inference cost and how consistently the model follows instructions across long inputs.
OpenRouter’s published pricing gives developers a reference point for hosted access, while the Hugging Face listing indicates that teams may also evaluate the model more directly through Z.ai’s released assets. Z.AI’s documentation adds that GLM-5.2 supports tool-oriented and structured-output features that are often required for enterprise assistants and coding systems.
As with any new model release, independent benchmark results and hands-on testing will be important before drawing conclusions about performance. The available source material establishes the model’s stated context length, output limit, feature set, pricing on OpenRouter and Hugging Face licensing status, but it does not by itself verify how GLM-5.2 performs against competing frontier or open-weight models in real workloads.
The OpenRouter listing also shows pricing of $1.40 per 1 million input tokens and $4.40 per 1 million output tokens.
Z.AI’s developer documentation separately describes GLM 5.2 as a flagship text model designed for long horizon tasks.
What the official documentation says Z.AI’s GLM 5.2 overview lists several capabilities relevant to production AI applications.
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