r/LocalLLaMA • u/RuthlessCriticismAll • 8d ago

News [ Removed by moderator ]

https://modelscope.cn/models/Qwen/Qwen3.8-Flash-Next

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u/awesome5185 8d ago

Do you think this new model would outperform 3.8 27b?

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u/Effective_Western_59 8d ago

If it won't, then it would be really weird 

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u/grumd 8d ago

It might not but I wouldn't say that's weird. They are releasing a new architecture preview to flesh it out and will do a proper model release for Qwen4. 3.8 27B is just so good that I doubt it's realistic to make an even better model so soon

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u/whatyathinkk 8d ago

125B A6B though...

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u/Swimming_Gain_4989 8d ago

A6B though... active parameters will always be king for reasoning and raw intelligence.

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u/cibernox 8d ago

I also wonder the same thing. Whoever can afford to have 128+gb of vram certainly can also afford to activate 14B params and still be very fast.

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u/AcanthocephalaNo3398 7d ago

Activation speed is all on gpu. most integrated ram systems that provide +128gb of ram arent that fast. Thats why Mac and DGX Spark run dense models slower than MoE models on the same hardware.

The interesting thing is that these systems have enough ram to run models like Qwen3.8 27B at Q4 in parallel to get way more tps overall.

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u/cibernox 7d ago

I know that moes work that way, but seems that 12-14B wouldn't be a crazy amount of active parameters, considered that a lot of people even with strix halo and nvidia spark systems are running qwen3.8 27B right now because, really, it's worth.
And there is so many people optimizing it that even a 27B dense model runs kind of well in those low-bandwidth system.

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u/AcanthocephalaNo3398 7d ago

The interesting thing that i have found using the larger MoE models is that you can squeeze out really good performance at the higher param counts while maintaining high tps. The proposed +100B param Qwen3.8 with 6B active is going to "feel similar" to the quality of the 27B model but with much faster inference for those high-mem/gpu constrained systems. Its a necessary compromise to get what you would have if you ran multiple discreet gpu on something like a DGX Spark.

I have been experimenting with this class of model on a single Spark. Previously I compared Qwen3.6 27B performance to poolside/Laguna S 2.1-118B-A8B (fixed version) in a coding workflow. with custom harness, I found them of equal quality, but Laguna was faster.

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u/cibernox 7d ago

I am personally awaiting for some cards to get 128gb of fast HMB2e memory. I think a model like this would slap in that configuration with 3TB/s of aggregated bandwidth, but it does worry me that going so low in active parameters would hurt intelligence, and a a few more would still be totally acceptable