<?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>Self-Hosted on disobey.dev</title><link>https://disobey.dev/tags/self-hosted/</link><description>Recent content in Self-Hosted on disobey.dev</description><generator>Hugo -- 0.152.2</generator><language>en-us</language><lastBuildDate>Wed, 03 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://disobey.dev/tags/self-hosted/index.xml" rel="self" type="application/rss+xml"/><item><title>262K context on 16GB VRAM because why not</title><link>https://disobey.dev/posts/gemma-4-26b-262k-context-16gb-vram/</link><pubDate>Wed, 03 Jun 2026 00:00:00 +0000</pubDate><guid>https://disobey.dev/posts/gemma-4-26b-262k-context-16gb-vram/</guid><description>&lt;p&gt;I&amp;rsquo;ve been running local LLMs for a while now and the eternal struggle is always the same: you want more context, more model, more speed — and you have none of the VRAM to support any of it. So when Gemma 4 dropped with 262K context window I obviously had to try fitting the whole thing on my RTX A5000. 16GB. Turns out you can. And its actually usable.&lt;/p&gt;
&lt;p&gt;~658 tok/s prompt eval. ~35 tok/s decode. Full 262K context window. f16 KV cache, no compression tricks.&lt;/p&gt;</description></item></channel></rss>