<?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>Kimi-K3.1-Pro on Negi AI Lab</title><link>https://ai.negi-lab.com/tags/kimi-k3.1-pro/</link><description>Recent content in Kimi-K3.1-Pro 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, 08 Nov 2026 04:01:20 +0900</lastBuildDate><atom:link href="https://ai.negi-lab.com/tags/kimi-k3.1-pro/index.xml" rel="self" type="application/rss+xml"/><item><title>Kimi-K3.1-Proオープン化！ローカルLLMで動かすVRAM容量とRTX/Mac選び方比較ガイド</title><link>https://ai.negi-lab.com/posts/kimi-k3-1-pro-open-weights-hardware-guide/</link><pubDate>Sun, 08 Nov 2026 00:00:00 +0900</pubDate><guid>https://ai.negi-lab.com/posts/kimi-k3-1-pro-open-weights-hardware-guide/</guid><description>DeepSeek-R1に匹敵する「最強の推論モデル」がオープンウェイト化され、ローカル環境で自律的な思考が可能になった。仕事で実用するにはVRAM 48G...</description></item></channel></rss>