【文章标题】:Qwen3.8-Flash-Next

【文章正文】: 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”. 【文章正文】: Qwen3.8-Flash-Next

通义千问推出的又一开源权重模型。该模型是“一个多模态混合专家模型,同时也作为Qwen4所用架构的早期预览”。

It’s pretty big: 125B tokens, but only 6B active which means it gets a significant performance boost. 它的规模相当庞大:1250亿token,但激活参数仅为60亿,这意味着其性能获得了显著提升。

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

). 我一直在DGX Spark上使用

这些Unsloth量化模型

进行测试。我仍在探索该模型——到目前为止,我尝试了72.5GB的UD-IQ1_S版本(生成了

这些鹈鹕

)和78.9GB的UD-Q2_K_XL版本(生成了

这些

)。

My favorite so far was this xhigh reasoning effort one from UD-Q2_K_XL: 到目前为止我最喜欢的是UD-Q2_K_XL版本中这个超高推理强度的输出:

Via

Hacker News

Tags:

ai

,

generative-ai

,

llms

,

qwen

,

pelican-riding-a-bicycle

,

ai-in-china

,

nvidia-spark 来源:

Hacker News

标签:

ai

,

generative-ai

,

llms

,

qwen

,

pelican-riding-a-bicycle

,

ai-in-china

,

nvidia-spark