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

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

#331

Post by XCSme »

overfeed wrote: post #185
hippycruncher22 wrote: post #129

Earlier quoted context omitted.

Yes let’s get rid of employees so no one is employed but somehow they can afford to buy my stuff

It's the natural outcome of next-quarter short-termism. The board and C-suite will be fine (monetarily).

I am surprised that they keep going with it, seeing how fast it improves and basically soon running themselves too out of business.

What's even their end goal? Open source models make sense, if profit is not the target, but for OpenAI and the rest, once they achieve "AGI", don't they basically become useless?

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

#332

Post by sheepscreek »

I was super excited to read this but lost the plot when I go to

> Qwen3.8-Max was asked to create the oh-my-cli project from scratch and, over a 10+ day long-horizon autonomous coding run

10+ days of building what exactly? Is that a shell prompt customization toolkit? Or a coding harness??

Neither - well, sort of the second. The poorly named thing is a self evolving coding harness, the self evolving part makes it a big deal.

I wish they had picked a different example.

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

#333

Post by msdz »

whage wrote: post #322
ucha wrote: post #264

Earlier quoted context omitted.

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.

Can you please explain why?

Not who you responded to, but I’ll give it a try.

Imagine our LLM as this one-dimensional matrix (instead of unfathomably many, many more dimensions):

0.728201017

-1.9293839303

2.93020202929

5.82290101728

-0.2844920917

…

And then, all of these values are multiplied by some scaling factor, essentially vectors pointing in some direction (in our case, only on a one-dimensional line instead of in some higher-dimensional space).

Now imagine it’s possible to “remove” the portion of the weights’ directions that’s responsible for some undesired property like history knowledge, or another programming language:

0.428201017

-1.6293839303

2.63020202929

5.52290101728

-0.5844920917

…

(For demonstration and faster-to-type-out purposes, I’ve changed each vector by deducting a constant amount of 0.3, which doesn’t make much sense. In reality, it’d modify probably all digits in some direction.)

Now we can see: the number of rows has stayed the same, but the value has changed. This means the required storage (or computational) space remains the same.

Please do correct me if this simplified too much or I had a mistake in my understanding.

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

#334

Post by satvikpendem »

me551ah wrote: post #257

This makes me wonder if AI companies even have a MOAT in the first place. All requests to an LLM are idempotent, for every API call you need to send it the entire conversation history so that it can process it. LLMs do not learn or remember anything, which makes it super easy for users to switch LLMs on the fly. Most popular AI frameworks, make this a one-liner change these days. And that makes me wonder if the trill…

Google figured this out with their paper from 2023, We have no moat and neither does OpenAI. The moat now is the harness and being able to recursively self improve from RLHF, a great example is how Grok used to be pretty bad but since SpaceX bought Cursor, they used that data to train Grok 4.5 which is now very competent at coding and even exceeds frontier models in certain benchmarks.

https://www.semianalysis.com/p/google-we-have-no-moat-and-ne...

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

#335

Post by satvikpendem »

zild3d wrote: post #298
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.

Actually, it's shown that even general knowledge helps coding models because their input is natural language itself so they need to understand it well enough to even turn into code.

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

#336

Post by TonyStr »

sznio wrote: post #206
tommica wrote: post #104

Earlier quoted context omitted.

What on earth hardwares do you guys have to be able to run 100gb models locally?! That's crazy! I'm here struggling to even get 27b models to run in somewhat usable way

quantized + offload I have an RX 6700 XT with 12gb vram and 64gb system ram. running dense models like 27b is difficult, but i can run IQ4/IQ5 qwen 122b-a10b or 35b-a3b at ~20tok/s

IQ4 qwen 122b-a10b would mean 61GB total size and 5GB active, so about 5GB of the model loaded into GPURAM plus any generated context, and 61GB of weights loaded into system RAM? I don't know if that math is correct, but does that run well? Wouldn't that only leave 3GB of system RAM?

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

#337

Post by satvikpendem »

deaux wrote: post #201
akmarinov wrote: post #155

Earlier quoted context omitted.

I mean it’s not competitive at all?

It has been more competitive than any other LLMs by non-US/CN companies. Including Korean and Japanese models in case you want to bring those up.

A distant third is not saying much.

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

#339

Post by mdp2021 »

gilgoomesh wrote: post #133
Fordec wrote: post #119

Earlier quoted context omitted.

Even if the US does ban it, Europe due to its lack of European competitors, has no current similar protectionist incentives. Even if there is regulatory capture in the US, the rest of the world isn't going to follow suit until the current market leaders outright are replaced with other competitors that Europe would want to favor. The genie is out of the bottle in the West already.

> lack of European competitors There's Mistral. Although they've been surprisingly quiet for the last 6 months.

> There's Mistral

https://trackingai.org

Mistral: eq.IQ ~70

Kimi, Claude, Grok, Gpt, Gemini: eq.IQ ~130+

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

#340

Post by gizmodo59 »

satvikpendem wrote: post #334
me551ah wrote: post #257

This makes me wonder if AI companies even have a MOAT in the first place. All requests to an LLM are idempotent, for every API call you need to send it the entire conversation history so that it can process it. LLMs do not learn or remember anything, which makes it super easy for users to switch LLMs on the fly. Most popular AI frameworks, make this a one-liner change these days. And that makes me wonder if the trill…

Google figured this out with their paper from 2023, We have no moat and neither does OpenAI . The moat now is the harness and being able to recursively self improve from RLHF, a great example is how Grok used to be pretty bad but since SpaceX bought Cursor, they used that data to train Grok 4.5 which is now very competent at coding and even exceeds frontier models in certain benchmarks. https://www.semianalysis.com/p…

Moat is not the harness. Harness itself is temporary until the models get better and slowly the code in harness will go down.

Note that the biggest GPU providers in the world are the hyper scalers and even they couldn’t allocate more if you pay for it. Because the rich companies and well funded ones are gobbling them up to the point where if tomorrow a 5T model that smokes every other model in the world is released you just can’t afford inference.

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