Demand for LLMs: Descriptive Evidence on Substitution, Market Expansion, and Multihoming
This provides descriptive evidence on market dynamics for LLM providers, helping them strategize on demand and pricing, though it is incremental as it documents existing trends without proposing new methods.
The paper analyzes demand patterns for Large Language Models using marketplace data, finding rapid initial adoption, varying substitution versus market expansion effects from new releases, and widespread multihoming among apps.
This paper documents three stylized facts about the demand for Large Language Models (LLMs) using data from OpenRouter, a prominent LLM marketplace. First, new models experience rapid initial adoption that stabilizes within weeks. Second, model releases differ substantially in whether they primarily attract new users or substitute demand from competing models. Third, multihoming, using multiple models simultaneously, is common among apps. These findings suggest significant horizontal and vertical differentiation in the LLM market, implying opportunities for providers to maintain demand and pricing power despite rapid technological advances.