English(EN) Prediction-Assisted Pricing and Admission for LLM APIs with Stochastic Token Consumption

新算法优化LLM API定价和准入控制

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

研究人员开发了一种名为预测裁剪UCB（PCUCB）的新算法，用于优化大型语言模型（LLM）API的定价和准入控制。该算法解决了随机令牌消耗和不同服务产品（如不同模型层级和令牌上限）的挑战。PCUCB将离线预测与在线学习相结合，动态设置价格并管理资源分配，旨在平衡收入生成与高效计算使用。 AI

影响引入了一种管理LLM API资源和定价的新方法，有望提高服务提供商的效率和盈利能力。

排序理由关于LLM API管理新算法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Patrick Wong · 2026-09-02 04:00

基于预测辅助的LLM API定价与准入：随机Token消耗模型

arXiv:2609.00710v1 Announce Type: cross Abstract: 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 …