I imagine it'd work the same as merging all the good-tasting foods to get an even tastier one

If you go to Civitai this is pretty how it works in that corner of the image generation world

Everything is using Stable Diffusion as underlying model, then most of the usage is merged of checkpoints

most merge improve a small subset of "feeling" benchmark (too small, too specific, or out of distribution) and tend to show degradation on actual benchmark, with especially punishing result on long chain benchmarks.

also only work on matching architectures (i.e. finetunes/loras of the same model)

that kinda worked in llama 1/2 era, not between different models but between finetunes of the same model. the briefly legendary Mythomax was IIRC a merge of 5+ tunes, some of which were merges themselves.

No, they need the same arch, but you can distill them into a single model. And yes, if you use the API directly Claude will often say it’s an open weight model (likely the ones it was distilled from)

The allegation here is that it's not actually a fine-tune of Qwen, but instead an undisclosed mashup (merge) of someone else's fine-tune of Qwen and the original model. Rio subsequently said that the model was in fact a merge, that they did additional fine-tuning after the merge, and that they accidentally uploaded the base merge instead of the version with additional fine-tuning. But this seems like quite an oversight...

Without evidence, your comment is just bad mouthing.

I have been involved in academia, including in Brazil, and I don't find academia there any more copycat than any other institution, including top tier ones.

This was a municipality working with a government associated IT company.

What does it have to do with Brazilian academia?

No, typically Brazilians go to Paraguay for their education, most of their technology comes from Paraguay too.

That only tells what base architecture they used, but fine tuning does not increase the number of weights, it just adapts the weights to improve better on a fine tuning dataset- something they claimed they had done