Inference Auctions: new paper proposes bidding for faster LLM serving without sacrificing latency
_onionesque · x · 2026-10-25
A new arXiv paper by Keegan Harris, Siddharth Prasad, Michael I. Jordan et al. tackles how to allocate priority when inference demand exceeds compute capacity. Instead of coarse fixed-price tiers, the proposed auction lets users bid for faster service, allocating priority economically efficiently without hurting latency, with fast algorithms for truthful-bidding prices and an autobidding agent that adjusts bids under a budget. Experiments show increased system welfare while preserving SGLang's cache utilization and latency advantages.
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