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I hope really badly that we'll get a new 35B A3B or similar MoE model!

I also miss the Qwen 3 Coder Next, which was 80B A3B, there are quite a few use cases where a non-dense model <100B would be the sweet spot (when you have the VRAM but not the TDP or compute power). Heck, I'd gladly take A5B or A8B or even A10B as a sort of middle ground.

Also alternate link for viewing the images without signing in: https://xcancel.com/Alibaba_Qwen/status/2088280182356611304

I'm hoping too that they'll put out some MoE variants.

Qwen3.5:122b:a10b can run about twice as fast as this 27b dense model.

Edit: Like its predecessors, 3.8 seems really inclined to overthinking, and on a 27b dense model that's kind of painful. I think I'm going to stick with gemma4:26b-a3b as my go-to because it runs about 4x as fast and tends to only need a fraction of the tokens in its 'thinking' stage to get the same or similar answer.

Did you try the claude reasoning traces finetune for qwen3.6? I find that it works muuch better. I assume the same 3.8 finetune will be released at some pointas well.

Edit: link - https://huggingface.co/rico03/Qwen3.6-27B-Claude-Opus-Reason...

Me too. 35B A3B runs really fast on my MacBook Pro (M4 Max) and is suitable for real-time tasks like dictation post-processing. The dense model is not.
Same here! Qwen3.6-35B-A3B is the only local model I've found that runs reasonably on my iGPU. Looks like me and and my noisily-wheezing laptop will be sitting out this upgrade.
Mind sharing your laptops specs? Just interested to see what is needed to locally run Qwen3.6-35B-A3B
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yeah, that's the A3B part; going up to A5B would probably also feel comfortable.

on the 395+ AI MAX w/128GB, the A10B qwen 3.5 can do a lot of long running work if you don't need to baby sit it. deer-flow works well like that.

> I'd gladly take A5B or A8B or even A10B as a sort of middle ground.

Whats up with focusing on the active param count? Do yall fiddle with the weights or something?

Total param count decides how much vram you need to run it. Active param count decides how fast it runs. My 10 year old GPU can load quantized 35B or 27B, but it can’t process 27B parameters per token faster than 2-4tok/s, while it can do A3B at >40tok/s
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You can run these on CPUs at a somewhat reasonable speed.
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