AutoGLM is an autonomous task completion agent based on a graphical user interface (GUI) launched by the Zhipu AI team.
It aims to simulate human operation behaviors on mobile phones. By combining advanced machine learning technology and GUI interaction mode, it realizes the leap from traditional large models to autonomous agents.
The following is a detailed introduction to AutoGLM:
Technical details
1. Model architecture:
- AutoGLM adopts the advanced Transformer architecture, which efficiently captures long-distance dependencies in text through the self-attention mechanism.
- The introduction of automatic feature extraction technology reduces manual intervention and improves the generalization ability of the model.
- It integrates multiple optimization algorithms, such as AdamW optimizer and layer normalization technology, to improve the training efficiency and stability of the model.
2. Core technology:
- Decoupling task planning and execution: Task planning and action execution are separated through the natural language intermediate interface, which improves the flexibility and adaptability of the system.
- Self-evolving reinforcement learning framework: Designed specifically for training web agents, it can learn and improve the capabilities of large model agents in web and phone environments from scratch in online network environments.
- GUI interaction mechanism: It combines advanced large language model (LLM) and graphical user interface (GUI) processing technology to provide users with an intuitive and efficient interactive experience.
3. Model parameters and training:
- Zhipu retrained the 32 billion parameter base model GLM-4-Air-0414, adding more code and reasoning data, and optimizing the capabilities of the agent, significantly improving the model’s performance in tool calls, online searches, and code tasks.
- Based on GLM-4-Air-0414, Zhipu launched a new deep thinking model GLM-Z1-Air, which is comparable to DeepSeek-R1 in performance, and has increased its reasoning speed by 8 times, with costs reduced to 1/30.
Application scenarios
AutoGLM has shown extensive application potential in many fields, including but not limited to the following aspects:
1. Social interaction:
- Like, comment, and send messages on WeChat.
- Automatically complete tasks such as writing Moments and reviews.
2. E-commerce shopping:
- Automatically search for products, place orders, and review on Chinese e-commerce platforms such as Taobao and JD.
- Support cross-platform price comparison to help users find the most favorable products.
3. Travel services:
- Buy train tickets on 12306 and book vehicles on Gaode.
- Automatically plan travel routes and provide real-time traffic information.
4. Content creation:
- Create articles and write comments according to user instructions.
- Automatically generate social media posts, advertising copy, and other content.
5. Academic research:
- Implement academic retrieval and code repository construction through the browser plug-in AutoGLM-Web.
- Automatically screen Peking University core journals to improve academic research efficiency.
6. Productivity tool expansion:
- Support functions such as automatic clocking in on video platforms and code warehouse construction.
- Automatically complete complex processes, such as hot pot ingredient procurement.
User feedback and market response
1. User feedback:
- Users highly praised AutoGLM’s in-depth research capabilities and execution capabilities.
- Some users reported that AutoGLM still has shortcomings in complex task execution and cross-platform operations, and needs further optimization.
2. Market response:
- The launch of AutoGLM has attracted widespread attention in the industry and is considered to be a major leap in artificial intelligence from “conversational interaction” to “autonomous operation”.
- Mobile phone manufacturers are optimistic about AutoGLM and believe that the end-side model is the general trend, but are also watching its actual development.
AutoGLM Agent Vs. DeepSeek Agent
AutoGLM Agent vs. DeepSeek Agent In-depth Comparison and Technical Analysis
AutoGLM Agent: Revolution of Full-Process Autonomous Operation and In-Depth Research
Technical Principle
- Core Model: Based on the “Meditation Model” developed by Zhipu AI, it integrates four major capabilities:
- GLM-4: Basic language understanding and generation;
- GLM-Z1: Enhance self-correction and reflection;
- GLM-Z1-Rumination: Realize long-range reasoning and task planning;
- AutoGLM: Give browser operation execution capabilities.
- Decision-making Mechanism: Adopt Markov Decision Process (MDP), optimize the operation path through the state-action-reward cycle, and support dynamic task decomposition (such as cross-platform login, multi-step search).
Core advantages
- Autonomous operation: You can control the browser to access closed platforms (such as Xiaohongshu and CNKI), breaking through API restrictions;
- In-depth research: Automatically generate research reports with reference sources, supporting complex tasks such as market trend analysis and academic reviews;
- Completely free: No usage restrictions, greatly reducing enterprise-level research costs.
Typical scenarios
- Business decision: Analyze the market share of new energy vehicles and generate reports including technology route comparison and consumer preference prediction;
- Academic research: Sort out the progress in the field of medical imaging in the past 5 years and integrate clinical application cases of deep learning models;
- Content creation: Plan sustainable fashion marketing activities and output a complete plan with KOL cooperation suggestions.
Limitations
- Overconfidence risk: Inaccurate content may be generated when dealing with problems in unfamiliar fields;
- Environmental dependence: It needs to run on a local browser and cannot directly execute complex operations such as Python scripts.
DeepSeek Agent: Decision engine driven by deep learning and knowledge graph
Technical principle
- Core architecture:
- Multimodal input layer: Synchronous parsing of text, images, and audio (such as extracting information from financial report PDFs and conference call recordings);
- Dynamic knowledge graph: Real-time update of entity relationships based on graph neural network (GNN), supporting trillion-level node queries;
- Adaptive learning: Online incremental learning updates the model daily to capture changes in data distribution (such as energy policy forecasts during the Russian-Ukrainian conflict).
Core advantages
- High cost performance: Open source and commercially available, suitable for customized deployment in finance, medical and other fields;
- Multimodal capabilities: Supports complex data processing such as logical graphs and scientific literature;
- Chinese adaptation: Better than international models in cultural terminology and idiom understanding
Typical scenarios
- Financial risk control: predicting stock price trends by analyzing historical transaction data;
- Medical diagnosis: generating personalized treatment plans by combining medical records and medical literature;
- E-commerce customer service: recommending products based on user browsing records to improve conversion rates.
Limitations
- Data timeliness: knowledge base updates lag and cannot obtain the latest dynamics;
- Complex problem bottleneck: highly professional problems (such as legal judgment prediction) rely on manual review;
- Hardware cost: training requires a large amount of GPU resources and the deployment threshold is high.
Future development trend comparison
| Dimensions | AutoGLM Agent | DeepSeek Agent |
| Technical directions | Strengthen multimodal interaction and expand to IoT device control | Deepen the knowledge graph and improve reasoning ability by combining large models |
| Application scenarios | Smart home (voice command control), industrial inspection | Precision marketing (dynamic budget allocation), supply chain optimization |
| Competitive strategies | Promote the paradigm change of human-computer interaction (such as “driverless” Internet access) | Focus on vertical field customization and challenge international model hegemony |
| Key challenges | Improve fuzzy semantic understanding and avoid execution deviation | Solve data bias and enhance model interpretability |
Selection suggestions
- AutoGLM Agent is preferred: if the requirements include browser operation and cross-platform data integration (such as market research and competitive product analysis);
- DeepSeek Agent is preferred: if you need to handle decision support scenarios such as structured data analysis, financial risk control or medical diagnosis;
- Hybrid deployment: AutoGLM can be used to complete front-end operations in complex processes, and DeepSeek can perform back-end data analysis to maximize efficiency.
Summary of AutoGLM Agent and DeepSeek Agent
AutoGLM Agent and DeepSeek Agent represent two evolutionary paths of AI agent technology: the former reshapes the boundaries of human-computer interaction with autonomous operation + in-depth research, and the latter builds a decision-making brain with knowledge graph + adaptive learning. In the future, the two may merge – AutoGLM enhances semantic understanding, and DeepSeek expands execution capabilities, jointly promoting the evolution of AI from “auxiliary tools” to “intelligent collaborative partners”.
Future Development Direction
Technology Upgrade:
- Continue to strengthen the performance of the base model, improve semantic understanding ability and task execution efficiency.
- Explore the application potential in more fields, such as smart home, smart office, smart transportation, etc.
Application Scenario Expansion:
- Realize in-depth application in more fields, such as finance, medical care, education, etc.
- Improve data processing efficiency through automated modeling, and help accurate prediction and analysis.
Human-computer interaction mode innovation:
- Promote innovation and transformation of human-computer interaction mode and become a leader in the field of human-computer interaction.
- Explore more natural and efficient interaction methods to improve user experience.
In summary, AutoGLM, as an autonomous task completion agent based on a graphical user interface, has shown wide application potential in multiple fields.
By combining advanced machine learning technology and GUI interaction mode, AutoGLM has achieved a leap from traditional large models to autonomous agents.
In the future, with the continuous upgrading of technology and the continuous expansion of application scenarios, AutoGLM is expected to play an important role in more fields and promote the intelligent development of human-computer interaction technology.
Zhipu Qingyan: ChatGLM & AutoGLM, AI Assistant for Work and Study
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FAQs
The following are frequently asked questions and answers about AutoGLM agents:
AutoGLM is an intelligent agent. AutoGLM is the latest agent product released by Zhipu AI. It has deep research and operation capabilities and can realize the function of “thinking while doing”. It captures environmental information in real time through cameras and sensors, dynamically adjusts task priorities, and can automatically optimize sorting paths and replenishment operations in scenarios such as warehousing and logistics.
In addition, AutoGLM can also autonomously plan operation paths and recognize graphical user interfaces (GUIs) based on the user’s natural language instructions, and perform various tasks such as social interaction, e-commerce shopping, travel services, and content creation.
The technical architecture of AutoGLM is based on the new deep thinking model GLM-Z1-Air launched by GLM-4-Air-0414, which demonstrates strong mathematical reasoning ability and fast reasoning speed. Its technical principles include decoupling task planning and execution, self-evolution reinforcement learning framework, etc., which enable AI to truly understand and operate graphical user interfaces and realize autonomous operation.
AutoGLM agent is an intelligent agent product released by Zhipu that integrates deep research capabilities and operational capabilities. It is called AutoGLM Rumination. The product was officially released at the Zhongguancun Forum. It is based on Zhipu’s GLM-Z1-Rumination Rumination model and can perform deep research and actual operations while performing complex tasks.
The biggest feature of AutoGLM Rumination is that it can think and do at the same time, similar to how humans can think and do operations when dealing with complex problems. It can open and browse web pages, complete tasks such as data retrieval, analysis, and report generation, and has deep research and actual operation capabilities, which has pushed AI Agent into a new stage of “thinking and doing”.
In terms of technical implementation, AutoGLM Rumination improves error recovery and performance by decoupling the planning and execution behaviors of the basic intelligent agent and adopting a self-evolving online course reinforcement learning framework. It performs well in web page operation and device control, such as achieving a 55.2% success rate on VAB-WebArena-Lite and a 96.2% success rate in the OpenTable evaluation task.
The release of AutoGLM marks an important progress in China’s autonomous intelligent agent technology, demonstrating the potential of AI Agent to evolve from a simple thinker to an intelligent executor that can deliver results.
AutoGLM uses RPA (Robotic Process Automation) technology to simulate human operations based on Android’s barrier-free services, without relying on manufacturer interfaces, and supports autonomous execution of application operations in the Android system.
Covering 8 high-frequency scenarios such as social (WeChat, Weibo), e-commerce (Taobao, JD.com), and travel (12306, Gaode), it can complete complex tasks such as friend circle interaction, product price comparison, and hotel reservation.
Make sure Python 3.8+ is installed, use a virtual environment (such as venv), run pip install -r requirements.txt to install dependent libraries, and if the installation of a specific library fails, install it manually and refer to the official documentation.
Check system memory and GPU memory, use data batching to reduce model complexity, or use distributed training/cloud resources to expand computing power.
Use quantization technology to optimize the model, use efficient reasoning engines such as TensorRT or ONNX Runtime, combine batch processing technology, or deploy to high-performance hardware such as GPU/TPU.
Make sure to use a supported Android phone, update to the latest version of Chrome browser, and correctly install Zhipu Qingyan desktop client and plug-in to avoid anti-jump restrictions affecting functions.
It does not support modifying or opening new conversations during tasks, otherwise the task process will be terminated. You need to plan complete instructions in advance, or continue to communicate through historical conversation records.
Currently, only text reports can be generated, which can be manually copied as MD format or plain text. Automatically generating charts or saving as PDF is not supported, and secondary processing is required with other tools.
You need to log in to relevant websites (such as Zhihu and Xiaohongshu) in advance. If you are not logged in, AutoGLM will wait for the user to manually confirm or automatically adjust the search strategy and turn to other sources to obtain information.
Currently, the browser needs to be kept online throughout the process. Background operation or task modification is not supported. Zhipu plans to launch a “virtual machine” version to enhance actual landing capabilities.
In the AndroidLab evaluation, the success rate reached 36.2%, surpassing GPT-4o; in the WebArena-Lite evaluation, the first attempt success rate was 55.2%, and the second attempt was 59.1%.
It has the combination of in-depth research capabilities and actual operations, supports GUI interaction, can break through platform information barriers, reach closed content ecosystems such as Xiaohongshu and Zhihu, and provide better information.
Step 1: Install Zhipu Qingyan PC client
Official website download https://autoglm-research.zhipuai.cn
Step 2: Install the latest version of Chrome browser
Windows:
ChromeSetup
Mac:
GoogleChrome-MAC
Step 3: Install Zhipu Qingyan browser plug-in (AutoGLM-Web)
[The browser plug-in will be installed for you when the PC installation package is installed. You can open the browser-extension page-check whether the Qingyan plug-in is installed. If the installation is complete, click Enable]
If the Qingyan plug-in is not installed during PC installation, you can go to the AutoGLM-Web official website to install the plug-in
Step 4: Restart the browser, open Zhipu Qingyan PC client, enter the AutoGLM meditation intelligent body, and raise questions.
When you install the Zhipu Qingyan PC client, the Qingyan plug-in will be automatically installed in Chrome;
2.1 Plug-in installation
If the installation fails, you can go to the Google Store to install it, or use the compressed package to install it.
(1) Google Store chromewebstore.google.com
(2) Search for “Zhipu Qingyan” in the Chrome/Edge App Store, or click the store link above to enter the plug-in details page, click “Add to Chrome”/”Get”, and select “Add extension”.
2.2 Installation package
(1) Download link➡️autoglm.aminer.cn
(2) Download the zip compressed package and decompress it to obtain the txt instruction document, crx installation package and zip compressed package
1) AutoGLM Shensi only supports crx installation package installation! ! !
2) zip: You can drag the folder after decompressing the zip package into the extension page
3) In the Chrome or Edge browser, enter the extension page and turn on the developer mode
4)‼ ️Note: Installation via the installation package will not automatically update
5) Drag the downloaded Qingyan plugin Crx installation package into the extension page (do not click to load the unzipped program)
6) Note: If you want to update, please remove the old version of the plugin first
7) When you see the pop-up box, click Add Extension and the installation is successful!
If you are a macOS user and have previously installed the Qingyan plugin, we recommend the following:
1. Uninstall the plugin
2. Open the terminal and enter the following commands in sequence:cd ~/Library/Application\ Support/chatglmrm -r config.json
3. Install the dmg package and open it
4. Open the browser and manually start the plugin, then close the browser
5. Test
After installing the Zhipu Qingyan browser plugin for the first time, you need to open the extension page in Google Chrome and confirm that the plugin is enabled.
After restarting the browser, you can use AutoGLM normally.
Note: It is recommended to install the Zhipu Qingyan client in the default path. Changing the path may cause execution failure.
Case 1: You are currently using meditation mode in the main Chat interface of Zhipu Qingyan, and have not entered the AutoGLM meditation intelligent body embedded on the left side of Zhipu Qingyan.
Case 2: Each user’s browser version and scenario are different. It may be that the browser cannot be awakened due to various engineering reasons, resulting in meditation trying to call the Qingyan browser plug-in but failing to execute. We are accelerating improvements and compatibility.
Currently, AutoGLM meditation is only supported on the Zhipu Qingyan browser PC client, and other terminals are temporarily unavailable.
Xiaohongshu, Zhihu, CNKI and other websites require full account login to access and perform search operations. Therefore, before searching, meditation will prompt you to log in to your account in the lower left corner of the conversation and count down 180s. If you are still not logged in after 180s, it will automatically abandon the search of the website and start the next round of search.
Related privacy agreements: Qingyan Plugin User Agreement Qingyan Plugin User Agreement; Zhipu Qingyan Privacy Policy; Zhipu Qingyan User Agreement
Yes.
You can manually minimize the browser window where meditation is performing tasks and reopen a window for normal use.
The window for the current round of tasks has been completed and can be manually closed.
If your network signal is weak, the answer may be interrupted. It is recommended that you switch to a more stable network or use a mobile hotspot to try again.
Currently, AutoGLM has a large number of visits, and the server is being repaired and expanded. Therefore, some users will receive a “server abnormality” reminder when using it. It is recommended that you try again later.
The screen splitting in the official website case is a manual drag operation, not an automatic screen splitting.
You can freely drag the size of the two browser pages to achieve the split screen effect.
Currently, AutoGLM only supports Chrome browser, and it will be further expanded in the future.
Zhipu Qingyan browser plug-in (AutoGLM-Web) supports Chrome, 360, and Edge.
Meditation mode: the dialogue mode of Zhipu Qingyan’s main Chat interface
After turning on this mode, Qingyan can respond to open and complex questions, search while reasoning, browse dozens or even hundreds of web pages, summarize a long and clear report, and provide all reference sources, so that the content output by AI can be checked.
AutoGLM meditation: AI agent embedded on the left side of Zhipu Qingyan
It can automatically operate and browse web pages like humans, view high-quality information sources such as CNKI and Xiaohongshu that are not open to the public API, and has multimodal understanding capabilities, and can better understand web page information, making the research more comprehensive.
AutoGLM related papers:
https://arxiv.org/abs/2411.02337
https://arxiv.org/pdf/2410.24024
AutoGLM Github:
https://github.com/THUDM/Android-Lab
AutoGLM technical explanation:
https://mp.weixin.qq.com/s/NXHum04VO6gtjz0n_8f87A
https://mp.weixin.qq.com/s/wQUOYA8b5IzJJfQeg5e7dg
https://xiao9905.github.io/AutoGLM/
AutoGLM meditation model system:
AutoGLM meditation: Generate in-depth research reports + operate browsers
autoglm-research.zhipuai.cn
An autonomous agent (AI Agent) that can explore open questions and perform operations based on the results. It is based on the SOTA reasoning model Z1 training and incorporates the hands-on operation function of AutoGLM. It can respond to open-ended deep questions, think about the answer steps independently, search the web page for multiple rounds, call the user’s browser, perform deep information retrieval tasks on the real browser, generate tens of thousands of words of deep reports, and can further perform operations such as purchasing goods based on the survey results.
AutoGLM: Operate Android Phones
agent.aminer.cn
A large model interactive intelligent agent that can execute actions can plan the task instructions issued by the user, thereby simulating the operation of people on the mobile phone and completing a series of complex tasks. It can replace people to read web pages, shop, order takeout, book hotels, comment and like Moments, send WeChat, and even complete cyclic tasks across APPs. At the same time, it can continuously interact with users during task execution, and make independent judgments and self-correction. In theory, AutoGLM can complete anything that humans do on electronic devices.
Zhipu Qingyan Browser Plug-in (AutoGLM-Web):
new-front.chatglm.cn/webagent/landing/index.html
A browser plug-in based on intelligent agent technology. It integrates common functions such as general dialogue, page summary, intelligent writing, and supports advanced functions such as advanced site search and code interpretation. After accessing AutoGLM capabilities, it can also understand user intentions and automatically complete complex tasks.
GLM—PC: Operating Computer
cogagent.aminer.cn/home
The AI computer agent launched by Zhipu AI based on CogAgent is driven by the self-developed GLM series of large models, especially for multi-step decision-making, tool calls, desktop environments and automatic operation tasks of mobile devices.
In-depth research
AutoGLM can autonomously break down open-ended questions, search while reasoning, browse dozens or even hundreds of web pages, and finally output a long report with a clear framework and detailed content. At the same time, it is also good at finding unpopular and non-intuitive information, and outputs it with clear references and summaries of the thinking process, which is convenient for users to check and verify information.
Smooth execution
As a deep reasoning agent that can execute actions, AutoGLM can take corresponding actions based on the text results after completing the research report, such as booking the corresponding tickets, or purchasing the most cost-effective products, etc.
Scientific research: history, biology, computer, good at writing relevant courseware and literature review
Life strategy: travel strategy (with ticket purchase execution), party planning (with product purchase)
Business analysis: industry analysis, competitive product analysis
Cosmeceutical recommendation: analyze ingredients, recommend beauty products (with product purchase)
When you are currently searching for web pages, you need to log in to your personal account.
Your information is only used on the user side, and AutoGLM meditation will not record any of your private information.
Related privacy agreements: Qingyan plug-in user agreement Qingyan plug-in user agreement; Zhipu Qingyan privacy policy; Zhipu Qingyan user agreement
Not supported for the time being.
Currently, AutoGLM only supports Android phones. Specifically, it needs to meet the Android system version requirements (usually a newer version) and enable accessibility service permissions.
You need to download the Zhipu Qingyan desktop client, which will automatically configure the Chrome browser plug-in during installation. Make sure that Chrome is the latest version. After installation, run the client and select the AutoGLM module to use it.
If you need to log in to platforms such as Zhihu and Xiaohongshu when performing tasks, you need to log in manually in advance. AutoGLM itself does not require a separate account registration, but some functions may rely on user account information.
It supports 8 high-frequency scene operations such as likes and comments on WeChat Moments, Taobao product search and ordering, and Meituan takeaway ordering, which can simulate human clicks, slides, inputs and other behaviors.
Make sure the phone microphone permission is turned on to avoid environmental noise interference. If the problem persists, try restarting the app or updating to the latest version.
Close other background applications to free up memory and ensure smooth operation of the mobile phone system. If the problem occurs frequently, try to clear the AutoGLM cache or reinstall the application.
Modification or interruption during task execution is not supported, otherwise the current task will be terminated. You need to plan the complete instructions in advance, or continue the unfinished task through the history record.
AutoGLM strictly respects user privacy and only obtains page information related to the task initiated by the user, and will not actively collect personal privacy. Sensitive operations (such as payment) will be confirmed to the user.
You can search for “Accessibility Service” in the phone settings and find the AutoGLM related options for switch management. Re-authorization is required every time you close the application and re-enable it.
Close unnecessary background applications, clean up the mobile phone cache regularly, and ensure sufficient system resources. If the task is complex, you can try to split the instructions and execute them step by step.
You can submit feedback through the Zhipu AI official website or related community forums, providing detailed operation steps, problem descriptions, mobile phone model, system version and other information to help the team optimize the product.
