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Qwen 3.8

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Re: Qwen 3.8

#301

Post by vitalyan8184 »

zer0gravity wrote: post #93
nsbk wrote: post #19

Bring it on! Hoping that they release smaller sizes of Qwen3.8. I use the 35B MoE and 27B dense models locally and most of the time I don’t need to reach out to Claude. Extremely useful specially when requests include sensitive and/or personal data

This seems more of a battle for frontier AI supremacy. I'm afraid that small capable models have been left in the dust. Big labs don't really want to hand over the golden eggs goose to the end user. Possibly the hardware vendors(e.g. Nvidia) may want to play in that area as well, to pull money from all parties.

nvidia and amd don't give a flying fuck about end users right now while they can milk triple digit markups from infinite money VCs via data center GPUs.

Re: Qwen 3.8

#303

Post by andy99 »

apitman wrote: post #279
pixelpoet wrote: post #276

Earlier quoted context omitted.

Yes, yes, yes! I'm absolutely ready and waiting with dual Strix Halo machines here and really want something approaching Opus at home. Speed is secondary concern for now, that would absolutely change the world. Qwen 3.6 27b 8b quant 16b kv cache is already pretty good on the Strix.

What kind of tokens per second do you get on that setup?

I get about 12 tok/s with 27B 8 bit, 50 with 35B A3B 8 bit, and 12 with 3.5 122B A10B 4 bit. The latter is about 80 GB iirc. it feels like the best balance between using as much memory as I can and still having a smaller expert model for inference to give decent speed, but I haven’t actually rigorously compared the performance of the three models.

Edit: that’s for one machine, would be interested to know if the upstream commenter with two has them networked to run bigger models? If I had two I might be inclined to have them running in parallel, the obvious limitation I’ve found with a single machine is that I can’t parallelize any tasks and I think I’d get more use out of the extra speed vs a bigger model (there’s nothing I’m too excited about in the say 200B range that having 256GB memory would unlock). But am very curious what others do

Re: Qwen 3.8

#304

Post by mycall »

gardnr wrote: post #6
adrian_b wrote: post #4

I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to bett…

It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.

> it also happens to be really good for humanity.

AI being good for humanity is still an open question, but for closed vs. open models/weights, yeah it is preferred. I foresee it won't be much longer before everyone will be slicing/distilling/tuning their models once the architecture improves.

Re: Qwen 3.8

#305

Post by blfr »

notnullorvoid wrote: post #300

Always nice to see more open-weights in the heavy model class. I can only hope this trend continues, causing OpenAI and Anthropic to crash and burn.

As much as I dislike 'em, this sounds mean spirited. And Alibaba admits in this very tweet that Fable is next level (it is).

Re: Qwen 3.8

#306

Post by bwfan123 »

XCSme wrote: post #90
vitorgrs wrote: post #68

Deepseek 4 "final" version is imminent as well. Will probably be at Opus 4.8 level, and I find it pretty big deal because of Deepseek price...

DeepSeek V4 pricing is insane, 10x-30x cheaper to use than most other models, and it usually is good enough for most tasks.

> it usually is good enough for most tasks

The model is fantastic. And costs almost nothing. The only problem I see is that they will train on your data.

There are zero-data-retention providers of DeepSeek models, of which I have used openrouter (with zdr guardrails), and fireworks. But these are 3x to 5x more expensive than directly using DeepSeek, possibly due to poor caching. Thats the price to pay for zdr.

Re: Qwen 3.8

#307

Post by oceanplexian »

gardnr wrote: post #6
adrian_b wrote: post #4

I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to bett…

It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.

> It's hard to say what their motivation is.

Not for anyone who reads history.

Back in the late 18th century, England was the world's top economy, in big part due to its textile industry. England had an export ban on the technology, but textile worker named Samuel Slater brought blueprints over (Supposedly in response to a bounty posted in a newspaper by the US government!). The technology diffused rapidly because the legal environment made competition easy, and ironically the US had better sources of energy (superior water-power sites).

Arguably, China is doing the same thing in the 21st century.

Re: Qwen 3.8

#309

Post by nojito »

gardnr wrote: post #6
adrian_b wrote: post #4

I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to bett…

It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.

> most effective way to debase American frontier labs

You're not going to debase the frontier labs through distillation.

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