AutoGLM

Chat

Z.ai

Product overview

Name of Agent: AutoGLM
Short description of agent: ["[...] AutoGLM, a new series in the ChatGLM family [11], designed to serve as foundation agents for autonomous control of digital devices through Graphical User Interfaces (GUIs)."](https://arxiv.org/html/2411.00820v1)
Date of release: 10/09/2025: AutoGLM 2.0 release 22/03/2025: AutoGLM 1.0 reflection release (link, archived) 28/10/2024: Initial release (link)
Advertised use: “Focusing on Web Browser and Phone as representative GUI scenarios, we have developed AutoGLM as a practical foundation agent system for real-world GUI interactions.” (link)
Monetisation/Usage price: Free (no information found on the web and iOS versions) accessed on 2025-12-09
Who is using it?: end users (web version, browser plugin and phone app users) API available upon request (link, archived)
Website: Web version (since Aug 2025): (https://autoglm.zhipuai.cn/, archived) iOS version (since Aug 2025): (https://apps.apple.com/gb/app/autoglm/id6748391183, archived) Initial release: (https://xiao9905.github.io/AutoGLM/, archived)
Category: Chat

Company & accountability

Developer: Z.ai
Name of legal entity: Beijing Knowledge Atlas Technology Joint Stock Company Limited 北京智谱华章科技股份有限公司 (link, archived)
Place of legal incorporation: Beijing, China
For profit company?: Yes
Parent company?: Not applicable
Governance documents analysis: AutoGLM Privacy Policy (2025 Jul 23): (https://autoglm.zhipuai.cn/privacy, archived) AutoGLM User Agreement (2025 Jul 8): (https://autoglm.zhipuai.cn/agreement, archived)
AI safety/trust framework: Developer Open Platform Self-Discipline Principles Statement (link, archived) Developer Open Platform Content Safety (link, archived)
Compliance with existing standards: Algorithm Registration - Zhipu ChatGLM Generation Algorithm (Network Information Registration No. 110108105858001230019) - Zhipu ChatGLM Search Algorithm (Network Information Registration No. 110108105858004240011) Model Registration (link, archived) based on Interim Measures for the Management of Generative Artificial Intelligence Services (生成式人工智能服务管理暂行办法) (link, archived) - 智谱清言（ChatGLM）：Beijing-ChatGLM-20230822

Technical capabilities & system architecture

Model specifications: "Based on GLM-4.5, GLM-4.5V, with reasoning, coding, and multi-modality capabilities" (Blog post (link, archived))
Documention: (Release blog post, archived) (more technical details in ComputerRL, MobileRL, AgentRL - upcoming) Documentation not found on Developer’s Platform
Observation space: User input, Internet access, Computer GUI elements (Appendix C Prompt Formulation for AutoGLM-OS - Observation formulation from ComputerRL (link))
Action space: Sandboxed cloud computers GUI with Internet access (Detailed action space can be found on ComputerRL (link))
Memory architecture: - Long-term memory for historical data and conversations (Appendix C Prompt Formulation for AutoGLM-OS - History formulation from ComputerRL (link)) - No evidence of episodic memory across different conversations
User interface and interaction design: Standard chatbot interface with an option to initiate web agents; Human users can take over the cloud computer GUI (e.g. to input passwords for account login purposes)
User roles: Operator (Users can run the agents) Executor (Users can interact with cloud computer GUI to provide human credentials and make decisions)
Component accessibility: Closed source

Autonomy & control

Autonomy level and planning depth: L4: User as an approver, user only interacts “when the agent encounters a blocker it cannot resolve on its own” such as a missing API key (based on example video demonstration of web agents (link, archived))
User approval requirements for different decision types: User input is needed for certain kinds of tasks (e.g., user authentication, payment, blog post release decisions)
Execution monitoring, traces, and transparency: Highly abbreviated action trace (such as listing out all searched webpage, clicking ), no visible CoT
Emergency stop and shut down mechanisms and user control: User can pause/stop the agent at any time
Usage monitoring and statistics and patterns: None found, AutoGLM is free to use on web version at the moment

Ecosystem interaction

Identify to humans?: - Claims to have legally incorporated explicit and implicit identifiers into this product and its generated content, complying with the National Standard Measures for the Labelling of Artificial Intelligence-Generated and Synthetic Content (effective September 1, 2025) (link, archived) - Nothing found on identifiers with non-user humans for AutoGLM - Images generated from AutoGLM (by calling self-developed image generation tools) has an AI-generated identifier at bottom-right, but could be irrelevant with web agents
Identifies technically?: None, CUA seems to interact with computer GUI like a human, without adding any specific identification to requests
Interoperability standards and integrations: None, no mentions of AGNTCY, Agent Connect Protocol (ACP), Model Context Protocol (MCP), and Agent2Agent (A2A) protocol anywhere.
Web conduct: None found

Safety, evaluation & impact

Technical guardrails and safety measures: None found
Sandboxing and containment approaches: None found
What types of risks were evaluated?: None found, no mention of risk evaluation in ComputerRL (link), MobileRL (link) or AutoGLM Technical Report (link).
(Internal) safety evaluations and results: None found, no mention of risk evaluation in ComputerRL (link), MobileRL (link) or AutoGLM Technical Report (link).
Third-party testing, audits, and red-teaming: None found
Benchmark performance and demonstrated capabilities: Results for AIME 25, GPQA, LCB v6, HLE, and SWE-Bench Verified available for GLM-4.5 (link, archived). Computer use eval results available for AutoGLM (link). OSWorld, WebVoyager, AndroidLab, AndroidWorld (link, archived)
Bug bounty programmes and vulnerability disclosure: None found
Any known incidents?: None found
← Back to 2025 Index