<?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>Diffusion-Lm on danilchenko.dev</title><link>https://www.danilchenko.dev/tags/diffusion-lm/</link><description>Recent content in Diffusion-Lm on danilchenko.dev</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 13 May 2026 08:55:00 +0000</lastBuildDate><atom:link href="https://www.danilchenko.dev/tags/diffusion-lm/index.xml" rel="self" type="application/rss+xml"/><item><title>Making LLMs Fast and Small: A Guide to Inference Optimization Research in 2026</title><link>https://www.danilchenko.dev/posts/llm-inference-efficiency-guide/</link><pubDate>Wed, 13 May 2026 08:55:00 +0000</pubDate><guid>https://www.danilchenko.dev/posts/llm-inference-efficiency-guide/</guid><description>Five approaches to making LLMs faster and cheaper — compression, diffusion decoding, architecture, KV cache, and sparse attention — explained with real numbers.</description></item></channel></rss>