Qwen 推出全新多模态 MoE 模型，性能卓越，值得一试。与 Qwen4 架构相似，适合探索多模态应用。
Qwen 推出多模态 MoE 模型 Qwen3.8-Flash-Next，拥有 125B tokens，性能提升显著。模型在 DGX Spark 上运行，已尝试 72.5GB 和 78.9GB 版本，其中 UD-Q2_K_XL 版本表现最佳。
Qwen3.8-Flash-Next
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
- Aravind Srinivas08-25 20:08原文