SOURCE-LINKED INTELLIGENCE

Prediction-Assisted Pricing and Admission for LLM APIs with Stochastic Token Consumption

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

An LLM application often sells or internally allocates several service products: a small or premium model, a short or long token cap, and possibly multiple posted prices. The operational decision is not merely which model answers a prompt. A price changes purchase probability, a token cap changes both user value and the tail of resource consumption, and accepted requests compete for shared compute and premium-model capacity. Demand and output length are initially uncertain, while an offline model may provide useful but imperfect predictions. We formulate sequential pricing and admission with s

Read original source ↗ Open in workspace

recordType

paper

region

Global