Core Viewpoint - The belief that AI model costs will continue to decrease is challenged, as the most advanced models maintain stable costs despite older models becoming cheaper [5][10][19]. Group 1: Cost Dynamics - AI entrepreneurs assume that as model costs decrease, their revenue situation will improve, allowing their businesses to continue [2][3]. - a16z claims that the cost of large language models (LLMs) is decreasing at a rate of 10 times per year, but this is primarily true for outdated models [4][5]. - The actual costs of the best models remain relatively unchanged, leading to a potential misalignment in business strategies for AI startups [19][40]. Group 2: Market Demand and Model Performance - Market demand consistently favors the best-performing models, which keeps their costs stable [19][21]. - When new models are released, consumer interest shifts almost entirely to these advanced models, regardless of the cost of older versions [12][16]. - The expectation for high-quality outputs drives users to prefer the latest models, further complicating the cost-reduction narrative [21]. Group 3: Token Consumption and Business Models - The consumption of tokens has increased dramatically, with tasks requiring significantly more tokens than before, leading to higher operational costs [23][29]. - The shift from simple interactions to complex tasks has resulted in a substantial rise in token usage, which is not accounted for in traditional subscription models [24][37]. - Companies adopting fixed-rate subscription models face challenges as token consumption outpaces revenue generation, leading to financial strain [33][40]. Group 4: Pricing Strategies and Market Competition - Many AI companies recognize the need for usage-based pricing but hesitate to implement it due to competitive pressures from fixed-rate models [41][42]. - The industry is caught in a "prisoner's dilemma," where companies opt for growth over sustainable pricing, risking long-term viability [44][45]. - Successful consumer subscription services typically rely on fixed-rate models, making it difficult for usage-based pricing to gain traction [47]. Group 5: Future Directions and Strategies - Companies are exploring various strategies to avoid the pitfalls of high token consumption, including vertical integration and creating high switching costs for customers [52][51]. - The emergence of "neocloud" providers may offer a path forward, focusing on sustainable business models that can adapt to changing cost structures [59]. - The industry must rethink its approach to pricing and service delivery to remain competitive and financially viable in the evolving landscape [56][58].