Menu Pricing of Large Language Models

Dirk Bergemann, Alessandro Bonatti and Alex Smolin

No 25-1670, TSE Working Papers from Toulouse School of Economics (TSE)

Abstract: We develop a framework for the optimal pricing and product design of LLMs in which a provider sells menus of token budgets to users who differ in their valuations across a continuum of tasks. Under a homogeneous production technology, we show that users’ high-dimensional type profiles are summarized by a scalar index, reducing the seller’s problem to one-dimensional screening. The optimal mechanism takes the form of committed-spend contracts: buyers pay for a budget that they allocate across token classes priced at marginal cost. We extend the analysis to environments with multiple differentiated models and to competition between a proprietary leader and an open-source fringe, showing that competitive pressure reshapes both the intensive and extensive margins of compute provision. Each element of our theory (token-budget menus, maximum- and minimum-spend plans, multi-model versioning, and linear API pricing) has a direct counterpart in the observed pricing practices of providers such as Anthropic, OpenAI, and GitHub.

Keywords: Large Language Models; Optimal Pricing; Menu Pricing; Fine-Tuning (search for similar items in EconPapers)
JEL-codes: D47 D82 D83 (search for similar items in EconPapers)
Date: 2025-10, Revised 2026-03
New Economics Papers: this item is included in nep-com, nep-des and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Menu Pricing of Large Language Models (2026)
Working Paper: Menu Pricing of Large Language Models (2026)
Working Paper: Menu Pricing of Large Language Models (2025)
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Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:130997

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