📄 中文摘要
缓存是一种将频繁访问的数据存储在临时高速存储中的技术，能够减少服务器在处理相同请求时的计算负载和延迟。在大语言模型（LLM）API调用中，成本是根据“令牌”来计算的，包括客户端请求时的“输入令牌”和模型返回的“输出令牌”。由于每个令牌都需要付费，当用户反复请求相同查询时，成本会非常高。因此，实施缓存可以有效降低重复请求的费用，提升系统性能。
缓存如何在大语言模型应用中发挥作用？
出处: How caching helps in LLM Application?
发布: 2026年2月12日
📄 English Summary
How caching helps in LLM Application?
Caching is a technique that stores frequently accessed data in temporary, high-speed storage, reducing the computational load on servers for repeated requests and minimizing latency. In the context of Large Language Model (LLM) API calls, costs are measured based on 'tokens,' which include 'input tokens' used during client requests and 'output tokens' received from the model. Since each token incurs a cost, repeated user queries can become very expensive. Implementing caching effectively reduces the costs associated with repeated requests and enhances system performance.