<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Moe on Best of AI</title><link>https://bestofai.io/tags/moe/</link><description>Recent content in Moe on Best of AI</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sat, 05 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://bestofai.io/tags/moe/index.xml" rel="self" type="application/rss+xml"/><item><title>Qwen3.8-Flash-Next</title><link>https://bestofai.io/models/qwen3-8-flash-next/</link><pubDate>Sat, 05 Sep 2026 00:00:00 +0000</pubDate><guid>https://bestofai.io/models/qwen3-8-flash-next/</guid><description>&lt;p&gt;Alibaba open-sourced Qwen3.8-Flash-Next on August 26, 2026, giving developers an early look at the Qwen4 architecture ahead of the full model family. It&amp;rsquo;s a multimodal mixture-of-experts model with a 125 billion parameter backbone but only 6 billion active per token, alongside a 51 billion parameter n-gram embedding table and a 4 billion parameter multi-token prediction module. Context runs natively to 262,144 tokens and extends to a million. Alibaba says it outperforms the older Qwen3.7-Plus, especially on coding and office tasks, while costing roughly one-ninth as much to train and about a twelfth as much to run. Both a standard and an FP8 checkpoint were released at launch.&lt;/p&gt;</description></item></channel></rss>