<?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>VRAM 容量 目安 on Negi AI Lab</title><link>https://ai.negi-lab.com/tags/vram-%E5%AE%B9%E9%87%8F-%E7%9B%AE%E5%AE%89/</link><description>Recent content in VRAM 容量 目安 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>Wed, 10 Jun 2026 04:14:48 +0900</lastBuildDate><atom:link href="https://ai.negi-lab.com/tags/vram-%E5%AE%B9%E9%87%8F-%E7%9B%AE%E5%AE%89/index.xml" rel="self" type="application/rss+xml"/><item><title>ローカルLLM環境の選び方と比較：OllamaからvLLMまで、失敗しないPC・GPU構成ガイド</title><link>https://ai.negi-lab.com/posts/local-llm-hardware-guide-ollama-vllm/</link><pubDate>Wed, 10 Jun 2026 00:00:00 +0900</pubDate><guid>https://ai.negi-lab.com/posts/local-llm-hardware-guide-ollama-vllm/</guid><description>ローカルLLM入門なら「Ollama + RTX 4060 Ti 16GB」がコストと手軽さの最適解。業務・API提供なら「vLLM + RTX 4090...</description></item></channel></rss>