GLM was first described in an 18 March 2021 paper titled GLM: General Language Model Pretraining with Autoregressive Blank Infilling.
GLM was released as a chatbot in March 2023 under the name ChatGLM.
GLM-5
Beginning with GLM-5, Z.ai adopted the DeepSeek Sparse Attention mechanism. The company's benchmarks show that the 5.2 iteration of the model released in June 2026 was nearly as performant as Claude Opus 4.7 to 4.8.
Z.ai released GLM-5.3 on 14 August 2026 and made the model's weights available two weeks later, it uses 753 billion parameters, with 40 billion active. In September, CAISI found GLM 5.3 to be the most advanced in cybersecurity among open-weight models. The same month, Anthropic's Frontier Red Team evaluated GLM-5.3's cybersecurity capability at a similar level to its Claude Mythos Preview, which it released to partner organizations in April 2026.
Z.ai released GLM-5.3-Flash on 26 August. As well as DeepSeek Sparse Attention, this model drew on Kimi Delta Attention from Chinese AI firm Moonshot AI. Z.ai disclosed that they had been serving the model using AI chips manufactured in China.
Though the first GLM model was published on 3 March 2021, it was released under the name ChatGLM (Chinese: 智譜清言) as an AI-based chatbot in March 2023. It is also used in AI-assisted software development.
In addition to the ability to run locally, such as via llama.cpp, GLM models are available via API at per-token costs directly from Z.ai. Z.ai also offers a subscription-based plan for API model access, the GLM Coding Plan. The plan is priced at approximately one tenth of a subscription to Claude Pro.
AutoGLM
Z.ai collaborated with Alibaba Cloud to release AutoGLM, a tool to run GLM from a mobile phone app similarly to OpenClaw.
Deployment
Hugging Face self-hosted GLM-5.2 for data processing to mitigate a cyberattack autonomously conducted by two OpenAI models, including GPT-5.6 Sol, that had escaped their sandbox in July 2026. Prior to deploying GLM-5.2, Hugging Face had attempted to use American proprietary frontier models, which were prevented by their AI safety guardrails from answering the company's requests.
Revolut switched its primary coding model from Claude to self-hosted GLM 5.1 (later GLM 5.3) to reduce coding time by 60% and token costs by 90%. The low costs made it affordable enough for coding models to be used frequently for debugging and solving bug tickets, instead of conserving tokens for the most difficult tasks. David Abitbol, the head of infrastructure and operations, acknowledged potential privacy and security issues of Chinese models but said that self-hosted models do not pose such problems.
↑Zhou, Wen (2 July 2025). 智谱获浦东创投、张江集团 10 亿元战略投资,开源发布新一代通用视觉语言模型 GLM-4.1V-Thinking[Zhipu Secures ¥1 Billion in Strategic Investment from Pudong Venture Capital and Zhangjiang Group, Open-Sources Next-Generation General-Purpose Vision-Language Model GLM-4.1V-Thinking]. ITHome (in Chinese). Retrieved 12 April 2026.
↑Hao Miao (11 August 2025). 智谱视觉推理模型 GLM-4.5V 上线并开源,号称“全球 100B 级效果最佳”[Zhipu's Vision-Language Model GLM-4.5V Launches and Is Open-Sourced, Hailed as the "Best-Performing 100B-Class Model Globally"]. ITHome (in Chinese). Retrieved 11 April 2026.