深扒Minimax与智谱：大模型，到底是怎样的生意模式？

Core Viewpoint - The article discusses the financial dynamics and business models of two AI companies, Minimax and Zhipu, which both went public with valuations around $60 billion but are facing significant losses due to high operational costs and investments in model training [5][8]. Group 1: Revenue and Expenditure Dynamics - Both Minimax and Zhipu are characterized as "short and agile" companies with fewer than 1,000 employees, rapidly iterating products and achieving annual revenues approaching $100 million within a few years [9]. - Despite rapid revenue growth, expenditures for both companies are approximately ten times their current income, with Minimax's spending being over five times its revenue in the first nine months of 2025 [11]. - The article raises questions about whether increasing revenue will lead to a narrowing of losses or exacerbate them, indicating a potential scale inefficiency in their business models [14]. Group 2: Role of Computational Power - The article emphasizes the critical role of computational power in the business model of AI companies, noting that training costs are a significant portion of total expenditures, often exceeding 50% [21][24]. - For Minimax, the revenue generated in 2024 is only 65% of the training costs incurred in 2023, while Zhipu's coverage is even lower at 30% by mid-2025 [25][26]. - The companies rely heavily on third-party cloud services for computational power, which contributes to their high operational costs [20]. Group 3: Human Resource Investment - Both companies have a high percentage of R&D personnel, with Minimax's monthly salary per employee reaching up to 160,000 RMB, indicating a focus on talent density rather than sheer headcount [16][18]. - The overall salary expenditure for Minimax is around $10 million annually, which is about 90% of its revenue, reflecting a high investment in skilled labor [18]. Group 4: Business Model Challenges - The article highlights a fundamental contradiction in the business model: while revenue is increasing, it is not sufficient to cover the rising costs of model training and operational expenses, leading to significant losses [30][34]. - The companies are caught in a cycle where they must continuously invest in new models to remain competitive, requiring additional financing that often exceeds their revenue [35]. - The potential for a sustainable business model hinges on the ability to amortize training costs over a longer period, which is currently not feasible due to the rapid pace of model iteration [30][37]. Group 5: Competitive Landscape - The competitive landscape is described as a capital-intensive game, where companies must secure financing to survive, with only a few players likely to emerge as long-term leaders [39][44]. - The article notes that many smaller companies are struggling to compete against larger firms and open-source models, leading to a consolidation in the market [43].