The Emerging Market for Intelligence: Pricing, Supply, and Demand for LLMs

We document six facts about the structure and dynamics of the LLM market using API usage data from OpenRouter and Microsoft Azure. First, we show rapid growth in the number of models, creators, and inference providers, driven by open-source entrants. Second, we show price declines and persistent price heterogeneity across and within intelligence tiers, with open-source models being 90% cheaper than comparable closed-source models of the same intelligence. Third, we document market dynamism, with frequent turnover among leading models and creators. Fourth, we present evidence of horizontal and vertical differentiation, with no single model dominating across use cases, and demand for intelligence varying widely across applications. Fifth, we estimate preliminary short-run price elasticities just above one, suggesting limited scope for Jevons-Paradox effects. Finally, we show that although the share of firms that use multiple models increased over time, most firms concentrate their use on a single model, consistent with experimentation rather than persistent reliance on multiple models.