<?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>Inference-Speed on danilchenko.dev</title><link>https://www.danilchenko.dev/tags/inference-speed/</link><description>Recent content in Inference-Speed on danilchenko.dev</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 31 Mar 2026 06:00:00 +0000</lastBuildDate><atom:link href="https://www.danilchenko.dev/tags/inference-speed/index.xml" rel="self" type="application/rss+xml"/><item><title>Diffusion Language Models Explained — How Mercury Generates 1,000 Tokens Per Second</title><link>https://www.danilchenko.dev/posts/2026-03-31-diffusion-language-models-mercury-1000-tokens-per-second/</link><pubDate>Tue, 31 Mar 2026 06:00:00 +0000</pubDate><guid>https://www.danilchenko.dev/posts/2026-03-31-diffusion-language-models-mercury-1000-tokens-per-second/</guid><description>Mercury uses diffusion instead of autoregressive decoding to generate all tokens in parallel, hitting 1,000+ tokens/sec. We break down how it works.</description></item></channel></rss>