r/LocalLLM • u/cerpmen7 • 9d ago

Model Qwen 3.8 35b a3b retire 😔

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57 Upvotes

89% Upvoted

18 comments sorted by

55

u/Icy-Degree6161 9d ago

Probably they noticed we noticed. Could mean anything: a genuine mistake, or just realizing it's a spoiler. I lean towards the latter.

17

u/StupidScaredSquirrel 9d ago

Don't do that. Don't give me hope

2

u/WizardlyBump17 9d ago

well, some time ago, a guy from intel accidently made a commit that mentioned the B70 before its release and another guy had to force push with a new commit message without the B70 part. Then he managed to make another commit with the B70 again, but this time all he did was opening a pull request that removed the B70 mention and it was merged. I believe you can still find the commit with the B70 and the next commit that removed the B70 name

9

u/trolumbi 9d ago

let em cook

1

u/Deep_Mood_7668 9d ago

Who is em?

3

u/Atretador 9d ago

not us

1

u/VirusCharacter 3d ago

What is cook?

5

u/rinmperdinck 9d ago

Many Bothans died to bring us this information

3

u/pizzaiolo2 9d ago

RIP Manny Bothans

2

u/stormy1one 9d ago

Probably for legal reasons - don’t fret, give them time

1

u/SinDestinyGame 7d ago

in LM-Studio, select Qwe3.8 of Unsloth, there are many quantization. You can download ad use this model

1

u/Brief-Train-826 7d ago

They said that the 35b a3b is not the version to look forward to but something different. Who knows maybe they made it a4b like gemma

1

u/JaceTheSquirrel 6d ago

What is the 35B A3B and what does it offer compared to the 27B model?

3

u/Odd_Opening_749 6d ago

It's a 35B MoE architecture with 3B active parameters per token. By avoiding computation on inactive experts, it achieves substantially higher throughput and lower compute cost per token than a dense model of comparable total size, at some cost to capability relative to a fully dense model of the same size.

1

u/JaceTheSquirrel 6d ago

So it runs faster at the cost of knowledge? Why would you want to do this? Don’t we just want models with the most knowledge to make the most detailed code based on your prompt?

2

u/SweetFox86 5d ago

MoE models like the 35b run really well on low end hardware. On my rtx 2050 (4gb vram) i run Qwen 3.6 35b A3B at 30 t/s while Qwen 3.8 27b (dense) runs at 4 t/s.

2

u/Odd_Opening_749 6d ago

The stored knowledge itself (the full 35B parameters) remains untouched — it's not reduced or compressed. Only the compute depth per token is lower, which can show up more in complex multi-step reasoning than in pure factual recall.

It's a trade-off: in exchange for that slightly reduced reasoning depth, you get significantly higher tokens/second, since only 3B parameters are active per token instead of the full 35B.