---
title: "Qwen Introduces Qwen3.8-Flash-Next: Multimodal MoE Model Previewing Qwen4 Architecture"
source: "Simon Willison 博客（Atom）"
source_tier: "t2"
url: "https://simonwillison.net/2026/Aug/26/qwen38-flash-next/"
permalink: "https://feed.astralor.com/items/itm_63366f5f9044fc451f21041b"
published: "2026-08-26T23:52:58.000Z"
score: 74
channel: "ai"
tags: ["MoE","Qwen","Qwen3.8-Flash-Next","Open-source Model"]
---

# Qwen Introduces Qwen3.8-Flash-Next: Multimodal MoE Model Previewing Qwen4 Architecture

## AI commentary

> This isn't just a model announcement—it's the first practical run-down of Qwen3.8-Flash-Next with specific quantized builds worth trying. For anyone tracking next-gen architecture, this blog is more useful than the official press release.

## At a glance

Qwen has released Qwen3.8-Flash-Next, an open multimodal MoE model with 125B total parameters but only 6B active, offering a significant performance boost and serving as an early preview of the Qwen4 architecture. Simon Willison tested it on a DGX Spark using Unsloth quantized versions, trying the 72.5GB UD-IQ1_S and the 78.9GB UD-Q2_K_XL, particularly recommending the high reasoning effort configuration of UD-Q2_K_XL. Continuing Qwen's open-source path, this model is worth watching.

## Key points

- Qwen3.8-Flash-Next is an open multimodal MoE model with 125B total parameters and only 6B active. 
- It serves as an early preview of the Qwen4 architecture with notable performance gains. 
- Simon Willison tested Unsloth quantized versions on a DGX Spark, recommending the UD-Q2_K_XL high reasoning effort config.

## Full text

Qwen3.8-Flash-Next Another open weights model from Qwen. This one is "a multimodal MoE model that also serves as an early preview of the architecture used in Qwen4". It's pretty big: 125B tokens, but only 6B active which means it gets a pretty big performance boost. I've been trying it out on a DGX Spark using these Unsloth quantized models. I'm still exploring the model - so far I've tried the 72.5GB UD-IQ1_S one (producing these pelicans) and the 78.9GB UD-Q2_K_XL (producing these). My favorite so far was this xhigh reasoning effort one from UD-Q2_K_XL: Via Hacker News Tags: ai, generative-ai, llms, qwen, pelican-riding-a-bicycle, ai-in-china, nvidia-spark

---

Verify against the original before citing; curated by Astral Feed: https://feed.astralor.com/items/itm_63366f5f9044fc451f21041b