Oh no, someone is profiting off of their work without proper attribution!?!?

This is an open weights model based on other open weights models.

The dispute is that they released it with claims about having done some post training that improved the outputs. It was discovered that the model was not post trained like they claimed.

The HF page now says it’s a merge of models, which wasn’t there before. They’re trying to claim they accidentally uploaded the wrong model to HF and that they’ll upload the real one soon.

Basically, they thought they could splice two open weights models together and claim their team had accomplished some amazing post training, but they weren’t smart enough to realize that other researchers would discover that there wasn’t any post training.

Thanks for the factual clarification. This is so important when everyone already has their trigger finger on politics. Not meaning that politics are irrelevant here, see sister comment by jobim.

But it's impossible to form a nuanced opinion when political association has a higher priority than the facts; which, again, don't look flattering for the implementers.

This is a pure scam on tax payer money. But what else would be expected?

Great, now we're defending embezzlement and fraud with public funds on HN, because we really really hate big business.

A child caught doing something bad will cry "but my friends also did it!", is that the level of reasoning hackers want to be at?

That seems like a bad faith read to me. Nobody is defending it, just pointing out the irony / hypocrisy. Two things can be bad, and they can be related.

What part of that said "defense?"

They can both be bad.

Attribution isn't the relevant part. Lying about your lab's capabilities is.

That's also something all the AI companies have been doing.

But the whole game is lying and stealing isn't it?

That's attribution to Qwen team.

There (is/was) no attribution to Nex team (they've released a model based on Qwen 3.5 397B as well).

As per OP link Nex claims that what Rio team released (so far) is just linear interpolation of weights between Nex and OG Qwen model. With no attribution to Nex and zero signs of Rio doing any training of their own.

Are you talking about the credit that was just updated an hour ago? lol

leopards ate my face

"Their work"? First you had the original content creators that did 99.99% of the work. Then you had the US companies bundle it up into a frontier LLM. Then "they" did the "work" of using the US model as a foundation for their own. So in the sense of doing 0.00001% of the actual work that went into their product, sure.

I'd say it's more like someone forking a Linux distro, adding a few themes and fonts, and then complaining when someone else forks their distro and adds another theme.

That joke really went over your head, huh...

That’s the joke.

That was the joke of the parent comment.

It is only a problem if you claim it to be an independently developed OS with no attribution to base

Oof this is delete your post level I think. Sorry bud, I been there.

The municipality of Rio de Janeiro (via its IT company IplanRIO) released Rio-3.5-Open-397B, presented as a homegrown Qwen3.5 fine-tune that beats comparable open models on benchmarks. The linked issue argues it's actually a weighted merge of ~60% Nex-N2 Pro + ~40% Qwen3.5-397B-A17B - Nex-N2 having been released about a week earlier.

I didn't know model merging like that was possible. (Obviously possible from a pure software standpoint but I'm surprised it's effective)

So the problem isn’t in the missing attribution to Qwen, but with the fact that they didn’t mention Nex-N2 Pro right?

The problem is that they claimed to have made a big achievement with their home grown post training, and they expected to receive a lot of praise for it.

Then researchers looked at the weights and there is no post training at all.

They are now attributing both models they merged, but their excuse for the lack of post training is to claim they accidentally uploaded the wrong files.

I'm honestly surprised that they even had the inclination to attempt creating a model. I guess it's bullish that a municipal IT department had the guts to try this?

“Well, Steve (Jobs), I think it’s more like we both had this rich neighbor named Xerox, and I broke into his house to steal the TV set, but I found out that you had already stolen it.”

-- Bill Gates

lmao i really hope this is a real quote cuz it’s a banger

The model's webpage at https://huggingface.co/prefeitura-rio/Rio-3.5-Open-397B says it's a merge now. It previously didn't contain this paragraph:

>The model is built via a merge of https://huggingface.co/nex-agi/Nex-N2-Pro and https://huggingface.co/Qwen/Qwen3.5-397B-A17B, proceeded by On-Policy Distillation from a stronger model. We detected an incorrect upload in the previous version, where the base merged version was upload instead of the final distilled model. We are sorry for the confusion and apologize profusely.

Incidentally are people using Github issues as blogs now?

One funny thing about incompetence is that they don't have the competence to know that their incompetence is straightforward to verify by a competent person.

You just described every single vibe coder...

I wouldn’t describe what happened here as incompetence. As a “carioca”, I am pleasantly surprised to know that the government’s IT department is involved in AI work — even without the budget to create its own models from scratch.

This seems kind of insane though, every time I go to Rio I think of the potential of AI/technology to solve some problems and leave it even more paradisiacal... But working on their own model? Wtf? There are a million applications of existing ones there that should be followed up on instead.

Why would they care? They get their salaries and pensions and bonuses, and the tax payer is footing the bill.

Not surprised

This is fascinating that it worked though. Can we just merge all the open weight models and get something better?

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

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)

Didn’t the last thread about this have someone from the lab or an enthusiast in Rio saying exactly that?

Its a fine tune of Qwen

Not a conspiracy

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 is very easy to prove [1][2]. Brazil has that reputation in the broarder academic world, and it's for a reason.

[1] https://www.sciencedirect.com/science/article/abs/pii/S17511...

[2] https://www.scielo.br/j/aabc/a/xNytDrrrHdyK4XPcHBRJZmd/?lang...

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

What does it have to do with Brazilian academia?

that's just a lie lol, stop spreading misinformation

What? Never heard of this

That sounds like nonsense, they don't even speak the same language in Brasil and Paraguay …

Wasn’t it already obvious given the awfully familiar parameter numbers?