Core Viewpoint - The article discusses the challenges faced by AI companies in balancing subscription pricing and operational costs, highlighting a potential "prisoner's dilemma" where companies struggle between offering unlimited subscriptions and usage-based pricing, leading to unsustainable business models [3][45][46]. Group 1 - DeepSeek's emergence in the AI space was marked by its impressive training cost of over $5 million, which contributed to its popularity [1]. - The training costs for AI models have decreased significantly, with Deep Cogito reportedly achieving a competitive model for under $3.5 million [2]. - Despite the decreasing training costs, operational costs, particularly for inference, are rising sharply, creating a dilemma for AI companies [3][15]. Group 2 - Companies are adopting low-cost subscription models, such as $20 per month, to attract users, banking on future cost reductions in model training [7][12]. - The expectation that model costs will decrease by tenfold does not alleviate the pressure on subscription services, as operational costs continue to rise [5][13]. - The reality is that even with cheaper models, profit margins are declining, as evidenced by the experiences of companies like Windsurf and Claude Code [14][15]. Group 3 - Users are increasingly demanding the latest and most powerful models, leading to a rapid shift in demand towards new releases, regardless of previous models' cost reductions [17][21]. - The pricing history of leading models shows that while initial costs may drop, the demand for the latest technology keeps prices stable [20][22]. - The consumption of tokens has increased dramatically, with the number of tokens used per task doubling every six months, leading to unexpected cost increases [28][29]. Group 4 - Companies like Anthropic have attempted to address cost pressures by implementing strategies such as increasing subscription prices and optimizing model usage based on load [38][40]. - Despite these efforts, the consumption of tokens continues to rise exponentially, making it difficult to maintain sustainable pricing models [41][44]. - The article suggests that a fixed subscription model is no longer viable in the current landscape, as companies face a fundamental shift in pricing dynamics [44][60]. Group 5 - The article outlines three potential strategies for AI companies to navigate the cost pressures: adopting usage-based pricing from the start, targeting high-margin enterprise clients, and vertically integrating to capture value across the tech stack [51][52][57]. - Companies that continue to rely on fixed-rate subscription models are likely to face significant challenges and potential failure [60][62]. - The expectation that future model costs will decrease significantly may not align with the increasing user expectations for performance and capabilities [61][64].