<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>KVCache on SiBlog</title><link>https://sinimite.work/en/tags/kvcache/</link><description>Recent content in KVCache on SiBlog</description><image><title>SiBlog</title><url>https://sinimite.work/images/og-default.svg?v=20260525-210321</url><link>https://sinimite.work/images/og-default.svg?v=20260525-210321</link></image><generator>Hugo -- 0.156.0</generator><language>en-US</language><lastBuildDate>Thu, 05 Mar 2026 11:09:00 +0900</lastBuildDate><atom:link href="https://sinimite.work/en/tags/kvcache/rss.xml" rel="self" type="application/rss+xml"/><item><title>What Is an LLM API KV Cache?</title><link>https://sinimite.work/en/posts/llm-api-kv-cache/</link><pubDate>Thu, 05 Mar 2026 11:09:00 +0900</pubDate><guid>https://sinimite.work/en/posts/llm-api-kv-cache/</guid><description>KV Cache is a key concept connecting Transformer theory with LLM engineering and deployment. Understanding it completes the path from how a model computes to how it runs.</description></item></channel></rss>