<?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>Llama.cpp 速度 on Negi AI Lab</title><link>https://ai.negi-lab.com/tags/llama.cpp-%E9%80%9F%E5%BA%A6/</link><description>Recent content in Llama.cpp 速度 on Negi AI Lab</description><image><title>Negi AI Lab</title><url>https://ai.negi-lab.com/images/og-default.png</url><link>https://ai.negi-lab.com/images/og-default.png</link></image><generator>Hugo -- 0.154.5</generator><language>ja</language><lastBuildDate>Sun, 16 Aug 2026 06:30:31 +0900</lastBuildDate><atom:link href="https://ai.negi-lab.com/tags/llama.cpp-%E9%80%9F%E5%BA%A6/index.xml" rel="self" type="application/rss+xml"/><item><title>ローカルLLMで開発効率化！Shell特化1.5Bモデルを使い倒すためのPCスペック比較と選び方</title><link>https://ai.negi-lab.com/posts/local-llm-15b-shell-command-hardware-guide/</link><pubDate>Sun, 16 Aug 2026 00:00:00 +0900</pubDate><guid>https://ai.negi-lab.com/posts/local-llm-15b-shell-command-hardware-guide/</guid><description>結論: シェル操作や単純なコード生成なら1.5B規模の軽量モデルがノートPCのCPUで1秒以内に動き、開発効率は劇的に上がる。。判断軸: 快適さを求めるな...</description></item></channel></rss>