---
id: 20260403-T0-03
title: "ParetoBandit：动态调整LLM路由策略，节省530倍成本"
title_en: "ParetoBandit: Budget-Paced Adaptive Routing for LLM Serving"
url: https://ai.daily.yangsir.net/daily/20260403-T0-03
issue_date: 2026-04-03
publish_date: 2026-04-02T04:00:00.000Z
category: research
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2604.00136
---

# ParetoBandit：动态调整LLM路由策略，节省530倍成本

ParetoBandit算法优化多模型LLM服务路由，动态平衡成本与质量。该系统根据实时定价波动、模型质量变化和新模型上线，自适应调整路由策略，覆盖530倍成本范围。测试显示，在保持95%准确率的前提下，平均节省40%计算成本。适用于云服务商和企业AI平台，可有效控制大模型部署开销。

## English Version

**ParetoBandit: Budget-Paced Adaptive Routing for LLM Serving**

ParetoBandit optimizes multi-model LLM serving by dynamically balancing cost and quality. The system adapts routing in real-time to handle pricing changes, quality regressions, and new model launches across a 530x cost range. Tests show 40% cost reduction while maintaining 95% accuracy, making it ideal for cloud providers and enterprise AI platforms.

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**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2604.00136)

**详情页**：https://ai.daily.yangsir.net/daily/20260403-T0-03

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