Qwen Introduces Qwen3.8-Flash-Next: Multimodal MoE Model Previewing Qwen4 Architecture
Score
74提供了新模型的核心架构信息和实测量化体验，对比常见新闻稿有增量细节。
来自资深开发者的第一手试用记录，客观且包含实用偏好建议。
给出了具体的量化版本和运行平台，对想本地部署的开发者有直接参考价值。
模型刚发布即被试用报道，时效性极佳。
Simon Willison是知名的技术博主和开发者，信源可信度较高。
Base 82.5 × T2 Source weight ×0.9 = 74
Curation line 70Selected
Why selected
The post is a hands-on evaluation by veteran developer Simon Willison, highlighting new model traits and quantized runtime experience with unique personal insights.
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.」
Quick overview
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.
- 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
Showing the source text; the full translation is being generated.
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
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