Author | Liu Baodan
Editor | Huang Yu
DeepSeek has become an industry benchmark, and in this AI competition, mainstream model companies are trying to surpass DeepSeek. The domestic AI unicorn Zhipu has also provided its own answer.
On March 31, Zhipu officially launched AutoGLM Reflection at the Zhongguancun Forum. This new intelligent agent not only possesses deep research capabilities but also enables practical operations, truly pushing AI Agents into the &#34;thinking while doing&#34; stage.
As the world's first Agent that integrates deep research and practical operation capabilities, the release of AutoGLM Reflection marks an important advancement in Zhipu's autonomous intelligent agent technology and a further upgrade of device control agents.
Behind AutoGLM Reflection, Zhipu has launched the Agentic GLM series matrix, including the GLM-4 base model, GLM-Z1 inference model, GLM-Z1-Rumination Reflection model, and AutoGLM model, especially the inference model GLM-Z1-Air, which has inference performance comparable to DeepSeek R1, but costs only 1/30 of R1.
It has been over two years since ChatGPT gained widespread attention, and AI large models have shifted from technological iteration to practical application, the latter becoming the core indicator for assessing the competitiveness of model vendors. Currently, Zhipu has partnered with leading companies such as Samsung and has become a partner in cities like Beijing and Shanghai. Additionally, Zhipu has also initiated an overseas expansion strategy.
Zhipu CEO Zhang Peng told Wall Street Journal that the company's commercial revenue growth will exceed 100% in 2024, with even greater growth opportunities in 2025.
In this AI large model competition, Zhipu is beginning to explore its own growth path.
<h2>AutoGLM Reflection: Thinking While Doing</h2>
Four months ago, Zhipu used AutoGLM to implement a group red envelope feature, marking the first red envelope issued by AI, representing the transition of AI large models from dialogue to operation. Four months later, Zhipu has laid out its inference capabilities onto Agents.
Unlike the last time when red envelopes were sent, this time Zhipu has started to make money with Agents.
Fourteen days ago, Zhipu secretly conducted a test, registering a Xiaohongshu account focused on lifestyle science popularization. Then, it used AutoGLM Reflection to generate notes, such as how to choose a coffee pot and how to compare cosmetic ingredients.
During a live demonstration, Zhang Peng stated that the task of investigating the three most popular anti-aging ingredients in cosmetics for 2025, comparing their effects, usage, advantages, and disadvantages, and finally conducting rigorous comparative analysis is not simple at all.
Zhipu revealed the account's achievements on-site: in two weeks, it gained 5,000 followers and received multiple business order invitations. Yesterday, Zhipu issued its first business order, earning 500 yuan
AutoGLM Chensi is the first Agent that integrates deep research capabilities and web operation capabilities, reflecting Zhiyu's latest understanding of AI Agents, which is to enable machines not only to think but also to take proactive actions, achieving the goal of &#34;thinking while doing.&#34;
This is also where AutoGLM Chensi differs from OpenAI's DeepResearch, as Chensi pushes AI Agents to evolve from mere thinkers to intelligent executors capable of delivering results.
Zhang Peng stated that Chensi has broken through real-time online search, dynamic tool invocation, deep analysis, and self-verification, achieving true long-range reasoning and task execution.
For example, asking Chensi to write a report on &#34;How the success of Nezha 2's box office will change the Chinese film industry.&#34; According to Zhang Peng, Chensi is very good at tackling such open-ended questions that require the model to explore on its own, ultimately generating a report of nearly 10,000 words.
This time, Zhiyu has released the preview version of AutoGLM Chensi, which primarily supports research scenarios. Zhang Peng revealed that in the next two weeks, they will further expand the execution capabilities of more Agents.
In addition, AutoGLM Chensi has been launched and is currently available on the Zhiyu Qingyan PC client.
<h2>Fully Self-Developed Backend Model</h2>
Behind the AutoGLM Chensi model is Zhiyu's independently developed full-stack large model technology.
Overall, Chensi integrates the general capabilities of GLM-4, the reflective capabilities of GLM-Z1, the rumination capabilities of GLM-Z1-Rumination, and the automatic execution capabilities of AutoGLM.
Zhiyu retrained a base model, GLM-4-Air-0414, with 32 billion parameters, incorporating more code-related and reasoning-related data during the pre-training phase, and optimizing for agent capabilities during the alignment phase, significantly enhancing the model's abilities in tool invocation, online search, and other agent tasks.
At the conference, Zhang Peng stated that GLM-4-Air-0414, with its 32 billion parameters, is comparable to larger parameter mainstream models both domestically and internationally, making the model particularly effective in adapting to agent tasks. &#34;This is because agent tasks often involve multiple rounds of complex interactions, and the 32 billion parameters allow GLM-4-Air-0414 to quickly execute complex tasks, providing a solid foundation for the large-scale application of AI agents.&#34;
Based on GLM-4-Air-0414, Zhiyu has launched a new deep thinking model, GLM-Z1-Air, which can compete with DeepSeek-R1 (671B, activated 37B) in performance.
In terms of inference speed, GLM-Z1-Air has improved by 8 times compared to R1, with costs reduced to 1/30, achieving a dual breakthrough in high performance and high cost-effectiveness. Additionally, GLM-Z1-Air can run on consumer-grade graphics cards
Based on GLM-Z1, Zhipu has enhanced the model's long-range reasoning ability through extended reinforcement learning training, resulting in the development of the rumination model GLM-Z1-Rumination.
Zhang Peng stated that this model breaks through the limitations of traditional AI, which solely relies on internal knowledge reasoning, by innovatively combining real-time online search, dynamic tool invocation, deep analysis, and self-verification, forming a complete autonomous research process.
GLM-Z1-Rumination can actively understand user needs, continuously optimize reasoning, and repeatedly verify and correct hypotheses in complex tasks, making research results more reliable and practical. Compared to traditional reasoning models, Zhipu expects the rumination model to lead AI assistants into a stage of &#34;high IQ&#34; to &#34;high IQ + high autonomy.&#34;
The core of the Agent is reasoning planning and hands-on ability. If the rumination model is the brain of AutoGLM rumination, then AutoGLM is the hands and feet of AutoGLM rumination.
Zhipu released AutoGLM last October, which is the world's first large model intelligent agent capable of executing over 50 steps of action on a mobile phone. The capabilities behind the AutoGLM rumination version have also evolved significantly since the last release.
Zhang Peng mentioned that there is a Scaling Law in the pre-training and post-training of large models, and Agents also exhibit a similar Scaling Law. &#34;Based on the Agent Scaling Law, we further discovered the emergence of capabilities in Agents.&#34;
For example, during training, AutoGLM rumination had never been taught to access the Giant Tide Information Network. However, when given the instruction &#34;Help me collect yesterday's research reports on embodied intelligence,&#34; AutoGLM rumination was able to devise a plan to solve the problem by accessing the Giant Tide Information Network and successfully operated the website.
Zhang Peng stated that AutoGLM's hands-on ability is currently at the state of the art (Sota) in the industry, with comprehensive leading capabilities in using tools, including browsers, mobile phones, and computers. In the area of GUI intelligent agents, CogAgent has achieved Sota results on multiple rankings for GUI Agents.
The series of achievements mentioned above is inseparable from Zhipu's forward-looking layout for Agents.
From the earliest launch of Zhipu Qingyan with FunctionCall capabilities in October 2023, to the launch of GLMs supporting intelligent agent orchestration in January 2024, to the release of AutoGLM in October 2024, and today’s launch of AutoGLM rumination, Zhipu has been leading the exploration of Agents.
After six years of technological accumulation, Zhipu has finally begun to demonstrate more competitiveness in this AI competition.
<h2>Open Source Does Not Mean Free</h2>
Like AI companies such as DeepSeek and Alibaba, Zhipu also adheres to an open-source strategy. Zhang Peng stated that the aforementioned model will be open-sourced on April 14 and will be gradually launched on the MaaS platform within the next two weeks
Alibaba's open-source business logic is aimed at selling cloud computing services. For model manufacturers, open-source means making core technologies public, which poses certain challenges for commercialization.
Zhang Peng also candidly acknowledged that open-source will have some impact on the commercialization market. However, he emphasized that open-source does not equate to being completely free. The subsequent investment of technical personnel, maintenance costs, and how to localize and implement DeepSeek, among other factors, incur significant costs, necessitating the need for professional teams to solve problems.
Currently, there are various intelligent agent products on the market. As a model manufacturer that began research on intelligent agents early on, Zhiyu understands market demands well. Zhang Peng stressed, &#34;We must provide services for the models; it's not enough to just throw the product at enterprises. If enterprises can't make it work, it's pointless. They spend money and will come back to tell you it's not usable.&#34;
At present, Zhiyu is vigorously promoting overall AI technology services, including providing tools and platforms, case studies and solutions, and better experiences, enabling more people to effectively utilize purchased or open-source models.
According to Wall Street Insights, Zhiyu has partnered with collaborators in finance, education, healthcare, government, and enterprise services to jointly advance the application of AgenticLLM. In February of this year, Zhiyu officially announced a collaboration with Samsung based on Agentic LLM, bringing the Agent experience to Samsung's latest Galaxy S25 series smartphones. Additionally, Zhiyu has successively reached cooperation agreements with cities such as Beijing, Hangzhou, Shanghai, Chengdu, and Zhuhai.
Zhiyu is also actively expanding overseas. On the same day, led by Zhiyu, a &#34;Self-Sufficient Large Model International Co-Building Alliance&#34; was officially established, initiated by ten countries from ASEAN and along the &#34;Belt and Road&#34; route, to help &#34;Belt and Road&#34; countries establish autonomous AI and build controllable national-level AI infrastructure.
Regarding commercialization, Zhiyu achieved an overall growth rate of over 100% last year, with many leading industries already making inroads, resulting in a certain scale effect. For this year's expectations, Zhang Peng stated that after another round of popularization, the market will see more than tenfold growth, presenting greater opportunities.
&#34;The entire model and commercial path will undergo some changes, and we will make adjustments. However, we will maintain a consistent and stable pace and effectiveness in commercialization, continuously improving the results of commercialization,&#34; Zhang Peng stated.
When discussing the company's current strategic focus, Zhang Peng told Wall Street Insights that Zhiyu positions itself as a technology-driven company, with another leg being the commercialization path. These two legs are not contradictory or competing for resources; they are in a dynamic adjustment process.
Zhang Peng further stated, &#34;The advancement and evolution of technology have reached a point where it must be deeply integrated into industries and applications to absorb nutrients and feed back into technology research and development. This is why we have vigorously promoted industrialization and commercialization since last year, which will involve some resource investment. However, from the overall perspective of core tasks and resource allocation, we still invest more resources in technology research and development and innovation.&#34;
The race towards AGI is still in its early stages. For Zhipu, although it has already explored the L3-Agentic LLM stage, the road ahead is still fraught with challenges. To achieve greater innovation on a global scale, it must go all out.
Risk Warning and Disclaimer
The market has risks, and investment requires caution. This article does not constitute personal investment advice and does not take into account the specific investment goals, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article align with their specific circumstances. Investing based on this is at one's own risk

SSNGY

Zhipu released AutoGLM Shen Si at the Zhongguancun Forum, which is the world's first intelligent agent that integrates deep research and practical operational capabilities, marking a new stage for AI Agents to "think while doing." Zhipu launched the Agentic GLM series, including models such as GLM-4 and GLM-Z1, particularly the GLM-Z1-Air, which has inference performance comparable to DeepSeek R1, but is priced at only 1/30 of it. Zhipu is collaborating with companies like Samsung and has initiated an overseas strategy, expecting commercial revenue growth to exceed 100% in 2024

- On March 31, Zhiyu officially launched AutoGLM, an AI agent that combines deep research and operational capabilities, marking a significant advancement in AI technology.  
- The AutoGLM model series includes various models, with GLM-Z1-Air offering performance comparable to DeepSeek R1 at a fraction of the cost, highlighting Zhiyu's competitive edge in the AI market.  
- Zhiyu aims for over 100% revenue growth in 2024 and is expanding its international presence, emphasizing the importance of practical applications and partnerships in driving AI innovation.

Applying reasoning to self-developed Agents, Zhipu has started to take the lead