The Way to Monetize Chinese AI Models: Cloud Platforms and Project Contracts Drive Growth

Event Background

Chinese AI model manufacturers are carving out a commercialization path distinctly different from their overseas competitors. According to industry observations, unlike the subscription fees and API call-based models of OpenAI, Anthropic, and others, major Chinese AI providers—including Baidu, Alibaba, Tencent, ByteDance, etc.—generate revenue more through cloud platform services, project contracts, and customized solutions. This difference is rooted in the varying cloud computing infrastructure ecosystems and enterprise procurement practices between China and the US.

Technical Analysis: How Cloud Platforms Enable AI Model Monetization

Cloud Platforms as Distribution Channels for AI Capabilities

In China, AI models are not sold directly as standalone products but rather as service components on cloud platforms. For example, Baidu's ERNIE Bot is integrated into Baidu AI Cloud, allowing enterprise customers to directly invoke AI capabilities through the cloud console without separate license purchases. Under this model, AI models are bundled with cloud resources (compute, storage, networking) and customers pay based on resource consumption.

Project Contract-Driven Customized Deployment

For large enterprises or government clients, Chinese AI vendors typically deliver through project-based contracts. Customers propose specific requirements (e.g., intelligent customer service, content moderation, automated office tasks), and vendors perform customized training and private deployment based on their own models. Revenue comes from a one-time project fee plus ongoing maintenance service fees. This contrasts with the overseas model of charging by request volume through standardized APIs.

Technical Architecture Differences

China's AI monetization model relies on deep integration with underlying cloud infrastructure. Vendors need to build full-stack capabilities spanning from chips (e.g., Huawei Ascend, Cambricon) to platforms (PaaS) to applications (SaaS). Overseas vendors like OpenAI, on the other hand, choose to partner with cloud platforms like Azure while maintaining model-layer independence.

Enterprise Impact Analysis

Cost Impact

CAPEX: When enterprises adopt AI solutions from Chinese vendors, they typically require significant upfront project customization fees and hardware costs for private deployment. However, the cloud platform model can convert this into OPEX, paying monthly resource fees.

OPEX: Ongoing usage costs under the cloud platform model are similar to the overseas API model, but Chinese vendors usually offer more flexible tiered pricing and bundled discounts.

Deployment and Operations Impact

• Deployment Efficiency: The cloud platform integration model enables rapid AI capability deployment without separate license procurement. However, project customization deployment cycles can take months.
• Operations Complexity: Enterprises rely on vendors for model updates, lacking full control. Private deployment increases the burden of local maintenance.

Security and Compliance

China's data privacy regulations (e.g., the Data Security Law, the Personal Information Protection Law) require localization of critical data. Chinese vendors' private deployment solutions more easily meet compliance requirements, while the overseas API model faces regulatory hurdles in China.

Market Competition Analysis### Cloud Vendor Competitive Landscape

• Alibaba Cloud, Tencent Cloud, Baidu AI Cloud, Huawei Cloud: These four major cloud vendors dominate China's AI cloud services market, each leveraging their own proprietary models (Tongyi Qianwen, Hunyuan, Ernie Bot, Pangu) to build differentiated capabilities.
• ByteDance (Volcengine): Leveraging its accumulation in Douyin and recommendation algorithms, it holds advantages in content generation and recommendation scenarios.
• JD Cloud, Kingsoft Cloud: Deeply entrenched in specific industries (e-commerce, gaming).

Competition with Overseas Vendors

Overseas AI models (such as GPT-4, Claude) face data compliance and network access restrictions in the Chinese market, resulting in low actual penetration. Chinese vendors, with localized services, lower prices (due to subsidies and competition), and policy support, hold an absolute advantage in the government and enterprise markets.

Winners and Losers

• Beneficiaries: Vendors with strong cloud infrastructure and model capabilities, such as Alibaba Cloud and Baidu AI Cloud; enterprises providing AI chips and servers (e.g., Huawei, Haiguang Information).
• Those under pressure: Independent AI model vendors lacking cloud platforms (e.g., some startups) struggle to secure large clients through project contracts, and their survival space is squeezed.

Industry Trend Observations

The monetization model of Chinese AI models is moving toward deeper integration of "cloud + AI." Future trends include: 1. Model as a Service (MaaS): More granular API calling patterns are emerging, but still bundled with cloud resources. 2. Vertical Industry Large Models: Customized models for finance, healthcare, manufacturing, etc., are implemented via project contracts, with higher profit margins. 3. Sovereign AI Cloud: Domestically produced computing platforms prioritized for local AI models with government support. 4. Edge AI Integration: AI models sink from the central cloud to edge nodes, generating new edge computing project contracts.

In the long run, the Chinese model may be better suited to enterprise-level digitalization needs, but issues of vendor lock-in and interoperability need to be resolved.

CloudTechDaily Insight

The commercialization path of Chinese AI models clearly reflects the characteristics of its industrial ecosystem: In a market dominated by cloud giants, the model itself is a tool to attract customers to the cloud, not an independent commodity. This model lowers the barrier to AI adoption for enterprises but also transfers most bargaining power and data control to the cloud platforms. For enterprise CTOs and CIOs, choosing a Chinese AI vendor is not just a technical decision but a cloud strategy decision—your AI capabilities will be deeply tied to a specific cloud platform. In the future, as technology decoupling between China and the US intensifies, Chinese enterprises will rely more heavily on the domestic AI cloud ecosystem, while overseas enterprises in the Chinese market will need to collaborate with Chinese cloud vendors to access AI capabilities. The global cloud computing industry needs to pay attention to the formation of this parallel ecosystem, which may shape two independent sets of standards and business models.