Analysis of the Technology Commercialization Path for Potential Collaboration Between Zhipu AI and Merck

Based on the information I have collected, I found that there is no publicly confirmed official announcement regarding the specific news report of Zhipu AI and Merck reaching a 3-billion collaboration. However, I can provide a detailed analysis of the technology commercialization path for this potential collaboration based on Zhipu AI’s technical strength, the current state of the AI drug discovery market, and the business characteristics of both parties.

As China’s largest independent general large model developer, Zhipu AI’s 2024 revenue reached 312.4 million yuan, with a compound annual growth rate (CAGR) of 130%, ranking first among independent general large model developers in China [1]. The company’s core technologies include the GLM series models, which have core capabilities such as text generation, code understanding, and multimodal interaction, and their performance in multiple benchmark tests is comparable to or even exceeds that of internationally leading models [2]. Its business model is mainly based on localized deployment for B-end and G-end institutional customers (accounting for 84.5% of revenue), while also developing cloud API call services (accounting for 15.5% of revenue) [3]. The gross profit margin has remained above 50%, reaching 56.3% in 2024, showing good profitability [4].

As a global pharmaceutical giant, Merck has actively布局 AI drug discovery in recent years. In September 2023, Merck reached a multi-year collaboration with Exscientia to discover new small molecule drug candidates using AI-driven precise drug design capabilities [5]. In November 2024, Merck collaborated with Valo Health, a U.S. AI biotech company, to use its AI technology platform to identify and validate new disease targets and quickly generate preclinical compounds [6]. The global AI drug discovery market is expected to exceed 6.3 billion U.S. dollars by 2029, with a continuously rising compound annual growth rate [7]. AI technology can shorten the drug development cycle from the traditional 10 years to 3-5 years, and significantly reduce the R&D cost of a single drug from more than 1 billion U.S. dollars [8].

If Zhipu AI and Merck reach a 3-billion-level strategic collaboration, the technology commercialization path can be evaluated from the following dimensions:

Zhipu AI is technologically leading in the field of general large models. Its GLM-4 series performs excellently in code generation and reasoning capabilities, and has the technical foundation to expand into the pharmaceutical vertical. Merck has rich drug discovery data, clinical trial experience, and global commercial channels. The collaboration between the two parties can achieve deep integration of ‘general AI capabilities + professional pharmaceutical knowledge’.

The size of China’s large language model market is expected to increase to 101.1 billion yuan by 2030, with a CAGR of 63.5% from 2024 to 2030 [9]. As a high-value vertical scenario, AI drug discovery has high customer unit price and strong demand rigidity. Referring to the 66% gross profit margin of Zhipu AI’s current government and enterprise customer localized deployment [10], the gross profit margin of pharmaceutical field collaboration may be higher.

Zhipu AI’s main current challenge is how to maintain the basic盘 of localized deployment revenue while increasing the proportion of standardized cloud services [11]. Collaboration in the pharmaceutical field requires deep customization and long-term operation and maintenance, which may加重 the ‘heavy asset’ model. However, from a positive perspective, pharmaceutical customers have high stickiness and expected renewal rates.

The core barriers to pharmaceutical AI collaboration lie in data assets and industry know-how. If Zhipu AI can obtain more high-quality pharmaceutical data through collaboration, it will help build competitive barriers in the vertical field. At the same time, collaborating with a global giant like Merck can also enhance Zhipu’s brand influence and international competitiveness.

• Technology Implementation Risk
  : The application of general large models in professional pharmaceutical scenarios requires a lot of industry knowledge adaptation, and there are certain technical thresholds
• Customer Concentration Risk
  : Referring to Zhipu AI’s current top five customers accounting for 40% of revenue [12], if the amount of a single collaboration is too large, it may bring dependency risks
• Geopolitical Risk
  : Against the background of Sino-US technological competition, international collaboration may face policy uncertainty

• It is recommended that Zhipu AI focus on obtaining authorization and usage rights for pharmaceutical data in the collaboration
• Gradually build professional model capabilities in the pharmaceutical field, rather than simply calling general models
• Explore a composite business model of ‘technology authorization + milestone payments + sales sharing’
• Pay attention to compliance requirements to ensure the compliance of cross-border data and intellectual property rights

If the potential collaboration between Zhipu AI and Merck can be reached, it will be a landmark case of deep binding between Chinese AI enterprises and international pharmaceutical giants. From the perspective of the technology commercialization path, this collaboration has good complementarity and market prospects, but also faces challenges in implementation and business model optimization. It is recommended to continue to pay attention to the progress of both parties in specific collaboration forms, data rights allocation, and commercialization implementation.

---

[1] Wall Street News - Fire Analysis of Zhipu AI Prospectus: Annual Revenue of 300 Million with 130% Growth Rate
[2] OFweek - About to Win the Crown of ‘First Large Model Stock’, How Does Zhipu AI Solve the Commercialization Puzzle?
[3] 21st Century Business Herald - Detailed Explanation of Zhipu Prospectus, What is the Quality of the ‘First Large Model Stock’?
[4] Wall Street News - Analysis of Key Financial Indicators of Zhipu AI
[5] Fortune Business Insights - Artificial Intelligence (AI) in Drug Discovery Market Report
[6] Sina Finance - Rapid Development of AI Drug Discovery Makes Building a Trusted Data Space Imperative
[7] Korn Ferry Management Consulting - Global AI Drug Discovery Market Size Forecast
[8] Chengdu Yibang Pharmaceutical Technology Co., Ltd. - Cost Saving Analysis of AI Technology in Drug Screening
[9] Frost & Sullivan - China Large Language Model Market Size Forecast
[10] Zhipu AI Prospectus - Gross Profit Margin and Revenue Structure Data
[11] Sina Finance - Detailed Explanation of Zhipu Prospectus Business Model Analysis
[12] Zhipu AI Prospectus - Customer Concentration and Revenue Structure