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Model details

GLM-5

GLM-5 is part of the Z.ai flagship family of large language models, sitting as a predecessor to later releases such as GLM-5.2 and GLM-5.3, which Z.ai describes as substantial advances over the earlier generation. Z.ai (zai-org) publishes and hosts artifacts for the family, with an official repository on GitHub at github.com/zai-org/GLM-5 and model pages on Hugging Face under the zai-org organization, making the series accessible to researchers and developers who want to follow its evolution. As the original member of this generation, GLM-5 established the lineage that later variants would build on, including the move toward stronger coding ability and long-horizon task handling.

Practically, GLM-5 is best understood as the foundation of a research and product line aimed at agentic coding and complex task workflows rather than as a standalone endpoint with published benchmarks. The family trajectory points clearly toward long-context reasoning and tool-augmented agent use: successor releases emphasize sustained quality across long, messy coding trajectories and improved performance on coding and agent benchmarks. For practitioners, GLM-5 represents the earlier entry point into this series, while users needing the strongest long-horizon and coding performance are pointed by Z.ai toward the more recent variants in the same family.

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Alibaba Token Plan (China)
Model key
glm-5
Release date
Feb 12, 2026
Last updated
Feb 12, 2026
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Output modalities
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Limits

Output tokens
16,384 tokens
Context window
202,752 tokens

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GLM-5 is the flagship open-weights large language model from Zhipu AI (operating internationally as Z.ai, Hugging Face org zai-org), launched February 11, 2026, "targeting complex systems engineering and long-horizon agentic tasks." Compared with GLM-4.5, GLM-5 scales to 744B total parameters with 40B active and raises Technically, GLM-5 integrates DeepSeek Sparse Attention (DSA) to reduce deployment cost while preserving long-context capacity, and the arXiv technical report "GLM-5: from Vibe Coding to Agentic Engineering" (arXiv:2602.15763, submitted 17 Feb 2026) describes an asynchronous RL infrastructure that decouples generation

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