<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Gpu on thelastguardian.me</title><link>https://thelastguardian.me/tags/gpu/</link><description>Recent content in Gpu on thelastguardian.me</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Sat, 16 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://thelastguardian.me/tags/gpu/index.xml" rel="self" type="application/rss+xml"/><item><title>I Got an AMD R9700 (32GB) for Local Inference</title><link>https://thelastguardian.me/posts/2026-05-16-an-amd-r9700-for-local-inference/</link><pubDate>Sat, 16 May 2026 00:00:00 +0000</pubDate><guid>https://thelastguardian.me/posts/2026-05-16-an-amd-r9700-for-local-inference/</guid><description>&lt;p&gt;If a local model was going to be part of the assistant, I wanted to understand the machine under it. So I bought a AI-oriented GPU.&lt;/p&gt;
&lt;p&gt;I wanted to learn the internals of LLMs and inference, and I can&amp;rsquo;t afford the multi-million-dollar racks of datacenter GPUs the hyperscalers run. A local model is a temporary stand-in for that learning: not smart enough to replace a frontier model, not some AGI/ASI waking up in my utility room, but decent enough to test chatting flows and scripts and watch how serving behaves.&lt;/p&gt;</description></item></channel></rss>