<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mistral on XiDao Tech Blog</title><link>https://blog.xidao.online/en/tags/mistral/</link><description>Recent content in Mistral on XiDao Tech Blog</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 XiDao</copyright><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.xidao.online/en/tags/mistral/index.xml" rel="self" type="application/rss+xml"/><item><title>2026 Open Source LLM Landscape: Llama 4, Qwen 3, Mistral &amp; the Rise of Open Models</title><link>https://blog.xidao.online/en/posts/2026-open-source-llm-landscape/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://blog.xidao.online/en/posts/2026-open-source-llm-landscape/</guid><description>&lt;h2 class="relative group"&gt;Introduction: 2026 — The Golden Age of Open Source LLMs
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&lt;p&gt;The development of open source large language models (LLMs) in 2026 has exceeded all expectations. Just two years ago, the industry was still debating whether open source models could catch up to GPT-4. Today, that question has been completely rewritten — &lt;strong&gt;open source models haven&amp;rsquo;t just caught up; in many critical areas, they&amp;rsquo;ve surpassed their closed-source counterparts&lt;/strong&gt;.&lt;/p&gt;</description></item></channel></rss>