[anana_]

It's rather surprising that a solo dev can squeeze more performance out of a model with rather humble resources vs a frontier lab. I'm skeptical of claims that such a fine-tuned model is "better" -- maybe on certain benchmarks, but overall?

FYI the latest iteration of that finetune is here: https://huggingface.co/Jackrong/Qwopus3.5-27B-v3

[1dom]

I feel that's a little bit misleading.

That link doesn't have much affiliation with Qwen or anyone who produces/trained the Qwen models. That doesn't mean it's not good or safe, but it seems quite subjective to suggest it's the latest latest or greatest Qwen iteration.

I can see huggingface turning into the same poisoned watering-hole as NPM if people fall into the same habits of dropping links and context like that.

[anana_]

I'm not saying it's the latest Qwen iteration - that would be Qwen3.6.

I'm saying it's the latest iteration of the finetuned model mentioned in the parent comment.

I'm also not suggesting that it's "the latest and greatest" anything. In fact, I think it's rather clear that I'm suggesting the opposite? As in - how can a small fine tune produce better results than a frontier lab's work?

[1dom]

Sorry, I somehow didn't see the comment above yours, but it makes a lot more sense now.

The sentiment still applies the parent comment of yours though.

[NitpickLawyer]

> can squeeze more performance out of a model with rather humble resources vs a frontier lab.

That's the idea behind distillation. They are finetuning it on traces produced by opus. This is poor man's distillation (and the least efficient) and it still works unreasonably well for what it costs.