Glass Slipper

"In this work, we leverage the OpenRouter platform, which is an AI inference provider across a wide variety of LLMs, to analyze over 100 trillion tokens of real-world LLM interactions across tasks, geographies, and time.

"In our empirical study, we observe substantial adoption of open-weight models, the outsized popularity of creative roleplay (beyond just the productivity tasks many assume dominate) and coding assistance categories, plus the rise of agentic inference. 

"Furthermore, our retention analysis identifies foundational cohorts: early users whose engagement persists far longer than later cohorts. 

"We term this phenomenon the Cinderella Glass Slipper effect. 

"These findings underscore that the way developers and end-users engage with LLMs in the wild is complex and multifaceted. 

"We discuss implications for model builders, AI developers, and infrastructure providers, and outline how a data-driven understanding of usage can inform better design and deployment of LLM systems."



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