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Qwen3.8-Max: A New Bar for Coding and Cowork

qwen.ai

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Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#291

Post by websap »

badsectoracula wrote: post #222
websap wrote: post #216

Earlier quoted context omitted.

[flagged]

A local model needs 0 investment and 0 commitment, takes literal minutes to get started (especially if you have someone who is into that stuff showing you the ropes) and if you end up disliking the experience of using AI you can just `rm -fr` it and forget the whole thing existed.

Needs 0 investment and 0 committment?

- You at least need a capable machine, so that's not 0 monetary investment. - You need to spend at least an hour decicding between ollama, llamacp, mlx, etc. - You need to find the correct quantized version of the model that works for you based on the architecture. - You need to figure out the correct context window size to get reasonable performance. - You need to setup a harness that works against your model - You might need to setup additional websearch tools, image tools, etc since harnesses like pi don't come with the model. Ofc you can't use codex and claude code, because those aren't opensource and you are anti-AI.

Or, you could sign up for Opencode for $10 and just be productive.

I'm particularly calling out the hypocrisy of the original comment. Being Anti-AI, and then spending hours on setting up a less than frontier AI model.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#292

Post by k__ »

ucha wrote: post #264
Zenst wrote: post #255

Whilst these coding models improve, they seem to cater for multiple languages, and for many, a trimmed-down LLM that supports just one language would be fantastic. This would be smaller, more able to run on the hardware people have at home, realistically (even on the CPU). Having one LLM that knows assembler, java, bain, C etc is neat, but when you only work and use one language at a time, it would be kinda neat to h…

That's not how LLMs work. If you're talking about number of parameters, you wouldn't be able to reduce the size much by "removing" support for other languages.

Yeah, I'd assume it's possible to extract all languages as steering vectors from a model and then substract the ones you don't need from its weights.

However, that would just change the weights values and not their dimensions.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#293

Post by breakingcups »

stanac wrote: post #243
markasoftware wrote: post #197

Earlier quoted context omitted.

Moonshot is printing money on k3. It likely costs the same to serve as qwen3.8. The license requires all major inference providers to sign an extra (secret) licensing agreement with moonshot that almost certainly requires them to agree to this price and pay royalties to moonshot. Watch as the k3 price plummets over the next 1-2 weeks.

If k3 is open-weight (and it's available on hugging face [1]), how could they force providers to sing an extra (secret) licensing agreement? Edit to answer my own question: License file [2] states: > If the Licensee or any of its affiliates operates a Model as a Service business, and the aggregate revenue of the Licensee and its affiliates exceeds 20 million US dollars (or the equivalent in other currencies) in total…

Can weights be copyrightable?

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#294

Post by gspr »

akmarinov wrote: post #156
CamperBob2 wrote: post #107

Earlier quoted context omitted.

Level 1: Anyone using unauthorized model weights in their business is prohibited from doing business with the government... Level 2: ... or with anyone who does. Level 3: Anyone caught with unauthorized model weights is subject to the same prosecution they could expect if they had been caught with CSAM.

Cool - how are they going to detect/police that?

It's not out of the realm of possibility to do AI audits. I'm not saying it's a good idea or likely, but certainly something they could do.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#295

Post by roosgit »

tesnorindian wrote: post #242

AWS Bedrock still lacks the support for the latest open weights models like GLM 5.2, DSV4 Flash 0731, Kimi K3 etc. Even they only support Qwen 3 which is a very old model. Any specific reasons they are reluctant to support open weights models?

I was wondering the same thing. Maybe it’s a licensing issue. Or the models are too big and there isn’t enough demand. But size is not a solid argument because they also don’t support Qwen3.6 27B and 35B-A3B, especially since they just added Gemma 31B and 26B-A4B.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#296

Post by dahrkael »

websap wrote: post #291
badsectoracula wrote: post #222

Earlier quoted context omitted.

A local model needs 0 investment and 0 commitment, takes literal minutes to get started (especially if you have someone who is into that stuff showing you the ropes) and if you end up disliking the experience of using AI you can just `rm -fr` it and forget the whole thing existed.

Needs 0 investment and 0 committment? - You at least need a capable machine, so that's not 0 monetary investment. - You need to spend at least an hour decicding between ollama, llamacp, mlx, etc. - You need to find the correct quantized version of the model that works for you based on the architecture. - You need to figure out the correct context window size to get reasonable performance. - You need to setup a harnes…

install LM Studio, download the automatically selected quant based on your hardware, start a conversation with the automatic context size. 10 minutes at best and zero effort

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#297

Post by OtomotO »

websap wrote: post #291
badsectoracula wrote: post #222

Earlier quoted context omitted.

A local model needs 0 investment and 0 commitment, takes literal minutes to get started (especially if you have someone who is into that stuff showing you the ropes) and if you end up disliking the experience of using AI you can just `rm -fr` it and forget the whole thing existed.

Needs 0 investment and 0 committment? - You at least need a capable machine, so that's not 0 monetary investment. - You need to spend at least an hour decicding between ollama, llamacp, mlx, etc. - You need to find the correct quantized version of the model that works for you based on the architecture. - You need to figure out the correct context window size to get reasonable performance. - You need to setup a harnes…

> You at least need a capable machine, so that's not 0 monetary investment

It is 0 monetary investment if I already have said machine lying around doing nothing.

Which is exactly the story OP talked about.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#298

Post by zild3d »

Zenst wrote: post #255

Whilst these coding models improve, they seem to cater for multiple languages, and for many, a trimmed-down LLM that supports just one language would be fantastic. This would be smaller, more able to run on the hardware people have at home, realistically (even on the CPU). Having one LLM that knows assembler, java, bain, C etc is neat, but when you only work and use one language at a time, it would be kinda neat to h…

I think you'd want to remove e.g. knowledge of harry potter universe and ancient egypt. Training on a bunch of high quality java code bases is still likely to improve your python model.
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