---
title: "Alibaba’s Qwen Team Releases Qwen3.8-Flash-Next: A 125B Multimodal MoE With 6B Active Parameters Previewing the Qwen4 Architecture"
type: signal
url: https://frontiernewswire.com/s/alibabas-qwen-team-releases-qwen3-8-flash-next-a-125b-multimodal-moe-v06e64728
published: 2026-08-26T15:20:00.000Z
byline: "Source: Mark Tech Post"
---

# Alibaba’s Qwen Team Releases Qwen3.8-Flash-Next: A 125B Multimodal MoE With 6B Active Parameters Previewing the Qwen4 Architecture

Source: Mark Tech Post · Published 2026-08-26 · Canonical: https://frontiernewswire.com/s/alibabas-qwen-team-releases-qwen3-8-flash-next-a-125b-multimodal-moe-v06e64728

We look at Qwen3.8-Flash-Next, Alibaba's open-weight multimodal Mixture-of-Experts model and an early preview of the Qwen4 architecture. We break down where the 180B parameters actually sit: a 125B backbone, a 51B N-gram embedding table, and a 4B multi-token prediction module, with only 6B active per token. We walk through the four architectural changes — the Gated DeltaNet and Qwen Sparse Attention hybrid, Gated Residual, N-gram Embedding, and the Muon optimizer. We also cover the benchmark results, the reported 1/9 training cost against Qwen3.7-Plus, and what self-hosting a 172.78 GiB FP8 checkpoint really demands. The post Alibaba’s Qwen Team Releases Qwen3.8-Flash-Next: A 125B Multimodal MoE With 6B Active Parameters Previewing the Qwen4 Architecture appeared first on MarkTechPost .

In this story: [Qwen 4](https://frontiernewswire.com/models/qwen-4), [Qwen3.8-Flash-Next](https://frontiernewswire.com/models/qwen3-8-flash-next)

## Sources

- [Read the original at Mark Tech Post](https://www.marktechpost.com/2026/08/26/alibabas-qwen-team-releases-qwen3-8-flash-next-a-125b-multimodal-moe-with-6b-active-parameters-previewing-the-qwen4-architecture/)

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