# Alibaba's Qwen Team Previews Its Qwen4 Architecture With a 6-Billion-Active-Parameter Open Model

Qwen3.8-Flash-Next pairs a 125-billion-parameter mixture-of-experts core with 51 billion parameters of N-gram lookup memory and was trained for a ninth of the cost of its predecessor.

- Published: 2026-08-27T06:20:08.967Z
- Canonical: https://polylog.news/ai/2026-08-27/alibaba-s-qwen-team-previews-its-qwen4-architecture-with-a-6
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [Polylog editors](https://polylog.news), [Qwen](https://qwen.ai/blog?id=qwen3.8-flash-next), [MarkTechPost](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/)

Alibaba's Qwen team released Qwen3.8-Flash-Next, an open-weight multimodal mixture-of-experts (MoE) model that the team describes as an early preview of the architecture intended for Qwen4. The checkpoint totals about 180 billion parameters…

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