Nvidia agrees to acquire Hugging Face for $13B

Historically NYSE (and AMEX; thought of in this specific context as CTA) had a lock on 1-3 character symbols. NASDAQ (via UTP) had a lock on 4-6 character symbols.

For a long time you could tell where something was listed purely by looking at the length of the symbol it traded under.

This all changed in the late 2000s or so, so no longer useful information.

I honestly would leave the industry if one of the exchanges tried to bend the industry to allow an emoji in a symbol. The communication protocols essentially lock this at 8 character alpha. It would be a huge pain in the ass, for everyone, to change this just because some exchange wants to appeal to a potential listing.

"The company was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf in New York City, originally as a company that developed a chatbot app targeted at teenagers. ..." Wikipedia

Besides that: which EU and sovereignty doesn't really rhyme, given data protection, energy costs, AI restrictions and no vital start up scene at all.

Mistral is heavily state funded via Banks that are predominantly owned by the French state, so I don't get it.

Also name one global success that doesn't came from US? China? Well, second place maybe, but second in any sense.

Nevertheless, kudos to huggingface. Not only to the founders, but to the ecosystem and I guess it got harder by the day to finance all the hosting and only hope for the future, that Nvidia will help HF to thrive, at least not put burdens on them.

GitHub is still alive, and hope that HF will benefit from more AI power.

Nvidia doesn't have any disadvantages in my playbook, because hardware wise, there is no one to beat them in any regard and Apple will always stay nichy.

So well played - hopefully.

It could be worse or even a shut down otherwise, who knows. So for me it sounds cool and I am glad that EU isn't involved in any regard.

As the AI Act demands full disclosure under really easy to match requirements into your inner workings, this is quite the opposite of freely sharing information.

HF was.. a hub to download models and some of the worst source code in the space that contributed to huge amounts bugs that did a lot of downstream damage. Go ahead and read their blog by their CTO on how they don’t believe in DRY and then implemented DRY in the worst way imaginable with unnecessary code generation.

Their BLOOM model was a joke and dead on arrival.

But yea these guys are definitely going to be the frontier of EU AI.

Hyperscalers and hardware manufacturers will absorb the overgrowth and hopefully (for them, sucks for us) settle at the top of the software value chain. The only way to make all the money poured into compute for the last 4 years pay for itself at any level is selling people and corporations on very inefficient software for the next couple of decades.

Not too different from what "the cloud" did to this market from 2015 or so...

Nvidia has a strong interest in open source AI being a strong contender to proprietary models. They don't want a single AI company to win, as that company would then have enormous leverage over Nvidia, and could perhaps even erode the Cuda moat with their own chip spending.

They want the AI market to be hypercompetitive, with AI companies focusing on competing amongst themselves instead of with Nvidia on one side, and many self-hosters / small inference providers buying Nvidia GPUs for large open models on the other.

It's in Nvidia's business interest to be a good steward of Huggingface, while being a good steward of Github is at best incidental to the interests of Microsoft.

They even share many of their pre-training and even post-training datasets for Nemotron on HuggingFace; for example: https://huggingface.co/datasets/nvidia/Nemotron-Post-Trainin...

Which other lab shares this?

Yes, there is no question NVIDIA wants to lock you into CUDA and their hardware. But also, they’ve consistently demonstrated the most openness when it comes to model training, datasets, and research; even before the LLM era (e.g. StyleGAN).

There’s also modelscope.cn (china’s huggingface) which is worth checking out. I would not be surprised if one day, we have to use China VPNs to download open weight models.

Evidently we should, because Linus has been more positive about Nvidia in the last 2 years [0]. I've been using the open driver for years now, for both gaming and CUDA.

[0] https://binarymusings.org/posts/talks/linus-on-ai-linux-in-k...

Their strategy for AI is pretty clear and they bank on on-premises OSS models for the busines, with their really cool open-source software: https://www.youtube.com/watch?v=tmcn1-jFLWY

This is a really good watch and is a glimpse into what the actual future shapes up to be considering the current situation in where the OSS Chinese models successfully compete with proprietary US ones.

Nvidia is a big company. They are good about some things and bad about others.

I think they really do like open weights because they make some of the best hardware for training, and the more open weights models there are, the more people are training and fine-tuning them, mostly on Nvidia hardware.

I feel like Nvidia is one of the better choices for buying Huggingface. Not perfect, but definitely far from the worst.

Nvidia wants people and companies to go choose a free open model, run that model on Nvidia hardware. And because Nvidia can't fully control what hardware an AI model can run, Apple Silicon and AMD hardware users will benefit as well.

The only thing I can see them being able to get away with is increasingly bending the hugging face python API and any other features of that sort they develop to NVIDIA only. I personally don't use that and don't see a reason to and I am not sure how many people do use the hugging face python library.

They're trying to mix up the competitive landscape(that doesn't impact their bottom line, and I don't think opensource is eating their lunch), so I don't think this is fake, at least that's my initial take.

My impression I've developed in the years of working there is that Nvidia's relationship with opensource is... not intentional. They kinda suck at it because they genuinely don't know how to do it more than they want to make money out of it.

Here's an anecdotal "success story" which is also an illustration to how things might not work out well otherwise.

So, I was on the team that deals with server infrastructure. One day we get a new "feature" which was supposed to allow Slurm (the workload manager, a kind of software used to run "jobs", including eg. model training) to be deployed with distributed MySQL as a backend. The feature is all obviously written by a single developer with an enormous amount of "help" from AI. I was tasked with testing it.

Trying to figure out what it does... I realized that the "distributed" part of the feature was to be achieved by integrating with Oracle's MySQL by means of using MySQLShell (another proprietary Oracle's product). Until that point, by default, we integrated with MariaDB. Not only was it using Oracle's proprietary tool, the tool, actually, didn't support the "distributed" part of the "solution". It was pitched as the "first step on the way there".

So, I was able to push back on it, mentioning Galera, arguing that the "solution" doesn't solve the problem and will require from customers to change databases (even if they are mostly compatible... they never quite 100% compatible). And the misfeature was rolled back.

I made an effort to investigate how did we even get there, and turned out that whoever authored the "solution" had an experience of working with Oracle products, but never really tried the open-source ones. So, he didn't do a research. He just used what he knew.

Unfortunately, this is a rare win, where the evidence of disadvantages of using proprietary solution was huge and enough to turn the tide. But often it doesn't face any resistance because nobody is even aware of the problem.

Modular on the other hand creates the Mojo compiler gets criticised for not open sourcing it immediately and now once they do, no-one cares anymore.

Huggingface was not just a target for open source, but as a force to have open weight models run better on Nvidia against the rest.

> They want

[citation needed]

Or at least, $13b to stay at the head of the race (or keep the race running) must be worth it to someone's desk.

There's only $50b in datacenter buildout nationally (Source: Gemini, 2026).

So it is a bit of a puzzling choice for what amounts to a pile of software, in my opinion. but I don't know shit.

Reversal would be "valued at 7B then valued at nothing", this is more like "nah, we want more" then "nah, we want more" then "yes, that's what we want :)".

This is the article you are referring to is this but your facts are wrong: https://techcrunch.com/2026/08/24/hugging-face-reportedly-in...

I'm not a fan of big-tech acquisition results either, but one benefit can be that a product continues to exist when it would otherwise become insolvent.

> We make money via compute credits + Enterprise Hub + HF Pro subs [...]

I guess this plus custom inference deployments, external inference providers, partnerships with the big cloud AWS, Azure, etc.

[1] https://x.com/reach_vb/status/1928050126498713706

Or perhaps they will start throttling downloads for free users.

I don't know what they business case is, it might be to shut them down: I suspect good free models on local hardware is a threat to Nvidia's investments in OpenAI/Anthropic.

I think the federal antitrust regulators are asleep.

Edit: antitrust regulators' job has just begun -- we'll see how this deal gets adjudicated by the FTC (if at all).

The era of VC-funded home-delivery recipe boxes is still my favourite.

Has always been this way. Big companies always seek to buy fast growing startups and unfortunately the founders of these startups mostly take the money.

Dgx Spark and Strix Halo have very close specs and deliver similar performance. If nvidia makes their stack be more efficient with for example 50% more tockens on similar hardware specs agaist competitors, they don't need HF.

My take is that Chinese Labs, though slightly behind on the frontier (due to compute constraints) are on a trajectory to surpass Western labs (this is me speculating, reasons are better ecosystem creation on China's part and potentially better/more data environment). Qwen-3.5-122b was the king in it's category and noone came up with something better, even though many tried like poolside with laguna. Similar with 35b and 27b param models. I think poolside and HF acquisitions show us that nvidia really wants to have competitive models on the prosumer (~100-150b param size) and likely at the 300-500b as well. Together with a hardware to run them that's a good market to be in. And as the recently rumored Xiaomi AI cube shows us (together with gorgon/medusa halo and mac studios), this is a market segment that will have competition.

Models are already largely hardware agnostic. It would be pretty hard to put that cat back in the bag.

I could imagine them building value-added services on top of HF to advantage Nvidia products (i.e. "run this model on NVIDIA cloud" with one-click), but in this moment it's hard to imagine how they could actively disadvantage models built to run on other platforms.

good old torrents

That said, I share all your concerns. The days of a permissive hands-off HF may be numbered

Commoditize your complement.

Now the Open-Models crowd will try to move to some other place. But fragmentation will weaken the position. Yes, there is Civic, there are purely Chinese websites ... for those who speaks Mandarin. Which only reinforces the point.

BTW Instagram raised $50 million at the valuation of $500M, just 4 days before the Facebook acquisition. %100 return of investment in 4 days, I think that's insane.

The amounts are incomprehensible at this point. I don't think anyone can conceive of 13 billion dollars accurately, including the people brokering this deal, they're just thinking of bargaining chips and weighing them in comparison to how many they have.

True about Intel and ECC, but AMD now does similar things, even with their consumer CPUs and chipsets.

These three companies now make very sure that consumer products can never canibalize those juicy data center profits - so they make sure to limit what the consumer segment can do.

VCs could not see any other reason to raise more money and Huggingface was not growing as fast as they thought to justify the valuation or the next fundraise.

So they might as well get Nvidia to save them from the VCs pressurizing them.

In this case, Nvidia wants the easiest route from:

find model -> adapt model -> optimise model -> run model

to terminate inside the Nvidia stack. This is a boon for DGX cloud.

> Here have some of my monopoly money I can print and come join us at Nvidia!

1) Local inference means more general GPUs and less ASIC hardware. Only big companies can push ASIC because of the software required, meanwhile nVidia owns cuda which is the standard.

2) Local is less resource-efficient per chip (chips remaining idle much more, meaning more chips required).

3) End-customers have less bargaining power compared to hyper-scalers. Although this might change if customer hardware start behaving more like phones (SoC with everything packed in), but even then the SoC makers will likely still have less bargaining power than hyper-scalers. But then nVidia could potentially make the whole SoC too.

So overall local-inference users = higher profit margins for nvidia. They much rather have every business on the globe buy one nvidia rack (or every laptop have a beefy GPU) than have 5-10 hyperscalers buy a few hundred thousand.

works fine for now

whats nvidia gonna do except make it worse?

usually buyouts go something like this:

1 buy company

2 fire various people

3 enshittify

hugging face even said they didnt want to accept a 500 million dollar investment from nvidia, because they didnt want nvidia to run the ship.

instead they sell it... guess who'll run the ship?

https://techcrunch.com/2026/08/24/hugging-face-reportedly-in...

His other comments on Nvidia often contain expletives.

And now you've recreated most of HF

Because you can't host arbitrarily large files on github, it's basically become a defacto "publish your project here" thing.

For a CN domestic equivalent take a look at Modelscope.

Having Nvidia behind HF will now probably have a bunch of litigious entities salivating to sue them for not only allowing, but also distributing uncensored AI models that will then be used for deepfakes, porn, spam, scam, hacking, etc.

Sure that could have also been done to HF before, but I'm thinking Nvidia is a much juicier target.

Should also now be much easier for the government to just eventually force NVidia to restrict access to Chinese open models seeing as it will now become an American company that needs to obey to American law and we all know how American AI companies are lobbying for exactly that.

The problem for them is that the leading provider of training and inference is actually AWS...

That's the anthropics and openais of the world.

Nvidia is making tons of money by selling GPUs at a very high profit margin. They will do anything to remain dominant

  > Nvidia Agrees to Buy Open Source Model Repository Hugging Face For $12.9 Billion

No doubt you have the nucleus of a substantive comment here, but that's not enough. If you only post the shallowest top stratum of what you're thinking, other people do the same, and then we get "Laws are for poor people" and endless descending repetition. The whole point of this site is to try for something other than that.

https://news.ycombinator.com/newsguidelines.html

p.s. Also, please don't be snarky on HN. That's also in the guidelines.

It's comparable to the biggest bank buying the biggest ratings agency.

Not just on this HF acquisition, but on the whole ecosystem monopoly.