📄 中文摘要
提示缓存技术在大语言模型（LLMs）中对于优化调用成本和延迟具有重要意义。通过缓存用户的输入提示，系统能够在后续请求中快速响应，从而显著减少计算资源的消耗和响应时间。这种方法不仅提高了系统的效率，还降低了用户的等待时间，提升了整体用户体验。随着大语言模型应用的广泛普及，提示缓存的实现和优化显得尤为重要，尤其是在处理重复性任务和高并发请求时。有效的提示缓存策略能够帮助开发者更好地管理资源，提升应用的可扩展性和响应速度。
为何关注大语言模型中的提示缓存？
出处: Why Care About Prompt Caching in LLMs?
发布: 2026年3月13日
📄 English Summary
Why Care About Prompt Caching in LLMs?
Prompt caching is a crucial technique in large language models (LLMs) that optimizes the cost and latency of API calls. By caching user input prompts, the system can quickly respond to subsequent requests, significantly reducing computational resource consumption and response time. This approach not only enhances system efficiency but also minimizes user wait times, improving the overall user experience. As the adoption of LLMs continues to grow, the implementation and optimization of prompt caching become increasingly important, particularly in handling repetitive tasks and high-concurrency requests. Effective prompt caching strategies enable developers to better manage resources and enhance application scalability and responsiveness.