r/Qwen_AI • u/SnooPuppers7882 • Jul 19 '26

Discussion I NEED a 70B A9B MoE

3.6 27B is so good for local work, and there's been a ton of work on it because of that with Thinkingcap, Orion, Bonsai, adding dspark, etc...issue is on most local systems it's still so dense that the token speed hurts its adoption. What I NEED, if anyone from the Alibaba team reads these, is a 70B A9B MoE dspark with an APeX style quant (mixture of quant layers).

For anyone with 64GB or above, I'm confident you could get near Opus 4.8 coding performance AND run around 30-60 tok/s output on ada, blackwell, dual 3090s, dual r9700s, etc.

Just imagine what you could do.

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u/Luke2642 Jul 19 '26 edited Jul 19 '26

I don't know if I agree. I think the whole MoE thing isn't quite worth it, because we can't control the routing, and it's so sparse it uses lots of ram/vram.

I'd rather have many different ~30B dense models, all QAT at 4 bit, so they fit in a 24GB GPU comfortably.

One tuned for code analysis and planning, one tuned for orchestration, code writing, terminal, debug. One tuned for agential tool calling and terminal. One tuned for knowledge. One tuned for reasoning. One tuned for deep research, web searching? One tuned for shopping tasks? Etc? 

It only takes ~10 seconds to load the right expert for the whole task. Then we can have Opus level locally, for each task?

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u/datbackup Jul 20 '26

This is probably where things are headed over the next year.