<?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>MLX on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/mlx/</link><description>Recent content in MLX on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Sun, 28 Jun 2026 11:00:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/mlx/index.xml" rel="self" type="application/rss+xml"/><item><title>MLX：Apple Silicon 上的大模型推理框架</title><link>https://guijiagi.com/posts/mlx-apple-silicon-inference/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/mlx-apple-silicon-inference/</guid><description>深度解析 Apple MLX 框架在 2026 年的大模型推理能力，涵盖性能优化、模型适配与实际部署实践</description></item></channel></rss>