Nvidia agrees to acquire Hugging Face for $13B
businessinsider.comhttps://www.theinformation.com/articles/nvidia-agrees-buy-op... (paywalled)
https://techcrunch.com/2026/08/24/hugging-face-reportedly-in...
I guess this unfortunately means HuggingFace won't be "the first company to go public with an emoji instead of the three-letter ticker" as the cofounders originally intended:
"When we started the company, a running joke with my co-founders was that we wanted to be the first company to go public with an emoji instead of the three-letter ticker when you go in the NASDAQ."
-- Clem Delangue (https://unsupervisedlearning.substack.com/p/the-future-of-open-vs-closed-source)Nvidia for Hugging Face will be even worse than Microsoft for Github and we now know how low the bar is here.
To be fair Microsoft haven’t done as much integration with their eco system; such as integrating it with Azure DevOps as they could. And long may it continue.
You missed the whole game-ification, enshitification, copilot-ification of github, and open source theft for their AI training episodes
Always like that with Microsoft apologists
Nvidia's been pretty terrible for open source / free software. No need to quote Linus Torvalds here. They want to control what runs on their hardware. They want to you write code against their proprietary drivers and APIs, not directly against the hardware (which these days of course also contains plenty of software, but still).
Don't expect things to go differently this time around. Nvidia wants control over the software stack. Acquiring HF fits in perfectly. The play is long term.
NVIDIA is one of the most open labs.
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.
> NVIDIA is one of the most open labs.
Of course they are. They're commoditizing their complement.
I want to own the hardware, not play around in an nvidia fiefdom full of nvidia rules.
I'll expand on the economics somewhat. My intuition is that you can like a moat left of you in the supply chain, but dislike moats to the right of you. (I'm using left and right as I picture this horizontally drawn. It is usually called vertical integration by economists.) But free competition in your market is worst of all. Free competition right outside your moat is pretty sweet, and that's were parent is commenting on.
Nvidia probably likes that ASML is a monopolist (it's called a monopsony). The price is high and Nvidia can't scale as hard as they want to (more general: capital intensive market). This monopsony makes sure that other chip companies can't rapidly scale up and try to beat Nvidia. That there only ever was one other GPU firm (I'm prehistoric; once there were more) and they bungled it on software, is pretty sweet for Nvidia.
On the side of their customers. It would be best for Nvidia if there is free competition for the outputs generated from there GPUs. This maximizes consumer surplus and thus demand. Maximum demand for tokens, is maximal demand feeded in their monopoly. If there is a monopoly right from you, demand is curtailed, and your value is limited.
And that exactly is why you see interest from token generators for chips. Bridge that moat and gain a larger value surplus. Both NVidia and, say, China actively undercutting the token-supplier value chain is quite interesting to watch. It's like the Opium wars with us as somewhat happy customers.
In this same vein, why isn't ASML raising thousands of billions for building their own (subsidiary) chip foundries, while raising prices and starving the market (a little) for their machines.
> > NVIDIA is one of the most open labs.
> Of course they are. They're commoditizing their complement
Then why don't they sell consumer GPUs with tons of memory. They clearly segment the market into consumer versus server/business.
While nvidia 's drivers are closed source there's enough interest in running LLM's that you are not locked in using nvidia. Strix Halo chips have been around before dgx spark came out and deliver very similar performance.
You do own the hardware. Nvidia GPUs have FOSS driver alternatives (Nouveau, NOVA) and have supported OpenCL on the proprietary drivers since 2009.
If you don't want to use CUDA, they expose the PTX bindings to write your own CUDA alternative too: https://docs.nvidia.com/cuda/parallel-thread-execution/index...
When last looked at it, NVIDIA was not supporting OpenCL beyond 1.0.
Also, when running OpenCL, NVIDIA hardware disables multiple DMA engines, and allows only one memory transfer at a time to prevent OpenCL running as fast as CUDA.
Did NVIDIA finally allow open source drivers to access all parts and features of the card to allow feature parity? Last time I checked they were considering a plan for planning a solution to that.
People love to blame NVidia on OpenCL failure, maybe Intel and AMD should actually deliver something compute researchers want to use?
OpenCL up to 3.0 is ostensibly supported: https://developer.nvidia.com/blog/nvidia-is-now-opencl-3-0-c...
I don't think bits like the GSP firmware will ever be open-sourced, but the opportunity to write better OpenCL drivers has always existed. Some of Nvidia's other proprietary driver backends (eg. GBM, Vulkan) are also decently neglected, but mostly out of disuse rather than malice. I don't think any of these things mean you don't own the hardware.
I wish OpenCL was usable today like your implying...
Yeah, OpenCL fandom always blames NVidia instead of Intel and AMD for doing a shitty work.
nothing stopping you from doing that
Are you joking? They just bought HF for $13bill and didn’t break a sweat. They are dominant and spreading.
Can't buy a decent modern Intel gpu to run AI on because of nividias "donation"
But Crescent Island is expected to appear soon
Nvidia has closed drivers, which makes them light years behind AMD in trust.
Also if we were just discussing labs, Ai2 opens ~everything with dramatically less resources than Nvidia.
> NVIDIA is one of the most open labs.
Nvidia’s history with linux shows the opposite. And as a user running models on a linux/AMD stack, this information does not fill me with hope.
"lab" vs "company as a whole"
They might be right w.r.t. openness about LLM at the moment, but w.r.t. general software openness they are definitely the opposite of open.
_why_ have people started to call companies “labs”?!
Because making new AI models is a research activity, so the group within Nvidia (or other companies) that does that activity is called a research lab, or just "lab" for short. I don't think anyone is saying that all of Nvidia is a lab (that's just shorthand I guess).
What amuses me is that “lab” is shorthand for “laboratory” and virtually no computer research happens inside a room people would typically call a lab.
It’s a little like the trend of calling developers “engineers”. There’s no actual engineering in the traditional sense but I’m sure developers think it sounds cool to call themselves that.
Because it sounds cool/sciency.
Just like everything AI is a "model". It's actually not, but it sounds cool/sciency.
"The proprietary shovel seller has some excellent tutorials on how to dig gold. Nobody else has such good step by step guides. Therefore them buying a shovel-agnostic tutorials and techniques method (that has a lot of info on using other shovels effectively) is justified."
They are sharing stuff that makes you consume their stuff. Their position with big ai companies is always vulnerable (asics/direct tsmc relations)
> They are sharing stuff that makes you consume their stuff
No shit Sherlock. Name one company that shared their code to make you NOT to consume their stuff?
Well if you find that obvious (I also do) then why do you not find their motives in acquiring HF onvious or that this move would be bad for the ecosystem as a whole? Cause it's all kinda the same thing.
Their (not especially great, compared to Chinese ones) models being open weight doesn't even come close to outweigh the effect of CUDA & Co being proprietary and closed.
> NVIDIA is one of the most open labs.
Dude, where's the src for GPU drivers and the firmware blobs?
Sorry, you can't say it is one of the most open labs without qualifying a proper response to the question above.
"Labs" here specifically means "AI/LLM model lab", which that part of Nvidia is unquestionably one of the most open.
Nvidia is also one of the most closed hardware developers around. Two things can be true.
Then this whole comment thread was a diversion though, as it was specifically about the hardware parts and not model training.
NVIDIA is a lot more than a “lab”.
Not really just to counter Anthropic
I'm with Torvalds here, fuck you Nvidia.
lol “Everything you said is correct but you’re wrong because I’m thinking about something other than what you were talking about”
CUDA is proprietary for a pretty understandable reason. There's no good way for Nvidia to standardize it.
They supported OpenCL when Khronos floated the idea of a GPGPU standard to manufacturers, but OEMs didn't want to design scalable hardware or sponsor the software.
>No need to quote Linus Torvalds here
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...
He definitely sounds more pragmatic than before, which is, in a sense, more positive.
> This is actually one of the benefits brought by AI; it has made Nvidia a good participant in the Linux kernel space. [...] Now, when Linux is so important for AI clouds, Nvidia suddenly cares very much about Linux.
Nvidia releases some of the most open open weights models, Nemotron 3, which have the full training code open, and most but not all of the training datasets.
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.
The worry is not that Nvidia isn’t open about their models.
The worry is that Nvidia is trying to control the way you run those models. Trying to bake CUDA assumptions into model design, and pushing the software ecosystem to be as Nvidia first as they can.
What would be the worst three?
My pick:
1. Oracle
2. A16Z
3. GameStop
Arguably, this move will help AI open source market more. Nvidia has an incentive to make AI open source competitive with closed source. If OpenAI or Anthropic gains in market share, they will eventually gain power over hardware vendors as well, which Nvidia does not want.
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.
Dude, the source of an LLM is the training data and the training algorithm. Those are not open, so stop calling it open source.
Open weights correspond to "binary available" for software. Nobody would call that "open source".
(Even ignoring the licensing which "open source" normally entails.)
As a AMD GPU user, I feel as if trying to mandate CUDA only or some other way to increase NVIDIA lock in like that would be met with people leaving the platform or at lest simply working on the non NVIDIA formats away from hugging face. Though requiring a lot of space it's quite easy to spin up a competitor at least for hosting weights. And if they try some legal shenanigans then many countries outside the US will still be happy to host I am sure why not China?
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.
Hf’s python / transformers is a hot mess. It conflates so many different ideas into huge monoliths that it’s barely usable for anything other than the small snippets listed for trying out models.
They need to take a machete to all the cross coupling they’ve metastasized.
I think this is part of an open-source play. I'm not arguing your other points, I think they're true.
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.
Nvidia has hardly open sourced the nvcc compiler, yet no-one here is complaining about why it is closed source.
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.
I assume it's because nvidia is a hardware company that produces world class hardware, and it's a compiler to target that.
Whereas mojo is a general purpose language, and we're absolutely spoiled for choice on modern languages with open source compilers.
I'm not saying it's fair or right, I still think mojo is neat, but isn't exactly comparing apples to apples.
We can stop with these weak excuses since AMD and Intel have done more for open source than Nvidia has, including their GPU drivers for Linux.
Nvidia on the other hand has not and the best they have done is a bunch of closed-source blobs which they do more closed source releases than the rest.
Mojo is open source and targets all GPU architectures for their compiler regardless of the vendor and nvcc targets their own (and both that and CUDA are closed source).
So this is directly an apples to apples comparison.
I'll give credit to Intel, they've always been open source friendly and I prefer to buy them because I'm not a gamer, so don't need the best.
AMD is another story. Their binary closed source blobs were even worse than nvidias for many years. So much so people used terrible performance open source tries just to avoid the headache. That they finally slopped together an open source version after they'd lost the GPU race isn't exactly noble. But as an open source supporter in general, I commend the effort still.
> as a force to have open weight models run better on Nvidia against the rest.
this is the crux - if nvidia makes it so that open weights end up running better on nvidia hardware than competitor's, then it's going to prevent hardware innovation and competitiveness in the entire sector.
It's like as tho General Motors buys out oil refinery to make gas for all, but the gas somehow runs smoother in GM cars.
If you don't own the customer relationship, you don't own the profit. See App store, FB.
NVidia is delivering commodity hardware to the hyperscalers, and would eventually get commodity margins (when hyperscalers make their models work on their own hardware).
Amazing article on relevant economics of squeezing vendors - actually about antitrust ad-models but:
https://www.thediff.co/archive/ad-supported-platforms-are-a-...The answer is that [advertising based] companies are an ideal test case for an increasingly common business meta-model, where companies try to create a consumer surplus at one end in order to maximize their negotiating leverage for capturing the producer surplus everywhere else in their supply chain.Perhaps not relevant to huggingface, sorry.
It's a clever move if that's what they're doing. They're restricted in China, and are likely to face stiff competition from Chinese chipmakers in the coming years. Acquiring the largest repository of trainable models and ensuring they run better on Nvidia hardware is probably one of the few moves they have for keeping ahead of the competition. I mean, it would be terrible for the consumer, but it does make me think that NVDA is a decent investment.
Why would they have to acquire hf in order to optimize their stack for those models?
Couldnt they just take those models anyway?
> no-one cares anymore.
possibly because it took qualcomm buying them to make that happen.
Just say you don't know.
Mojo was partially open source before Qualcomm bought them, and they were going to do open source it anyway.
Was NVCC or CUDA ever open source since the lifetime of its development?
> they were going to do open source it anyway.
uh huh.
> Was NVCC or CUDA ever open source since the lifetime of its development?
you ever ask Nvidia why? i did.
As opposed to whom else? Do you think any of the other labs or acccelerators are clamoring for open source hardware?
I for one welcome our new robot overlords.
I think it's a plausible play that keeps the AI boom in session for a year or two longer.
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.
Did you just quote an LLM as a citation? That's not how citations work.
"That's not how citations work." (Dude on the interwebz, 2026)
But more seriously, this is my first time seeing that as well, and I'm not sure I like it. Citing an LLM is a little like citing Wikipedia to me, you cite the primary source the LLM is quoting directly, not the secondary source.
Far worse from my perspective is that it's not a fixed citation that it's not falsifiable. It's just a mutable, generalized source, which is stochastic in nature.
It may as well say "(Socrates, probably)"
A Wikipedia link can be nice when you get several different sources provided.
It’s the formatting and formality that bother me. Say “I looked it up with Gemini,” don’t give me some weak attempt at “proper citation” to legitimize the bare minimum effort you put in.
Why waste keystrokes when less do trick?
Even worse is that Gemini's knowledge cutoff is still Jan '25.
2026 equivalent of “my Mama told me”
Better to site the primary source, its like googling something and then siting google as your source.
> There's only $50b in datacenter buildout nationally (Source: Gemini, 2026).
Your reference lacks authority, veracity, and reproducibility.
It came to me in a dream.
They’re buying a brand, some employees, and some momentum — not any of their software. HF probably does have propriety goodies to make it all run efficiently, but certainly not a billion dollars worth, much less 13!
No company is going to be acquired for their software alone with multi-billion valuations ever again. It should be clear by now that code alone is not where the value is anymore, if it ever was.
We are so used to these numbers being thrown around in the AI era that something one needs a reminder that this is 13 billion, not million. Insane exit by HF.
80x its yearly revenue. Clearly they aren't buying HF for margins.
In fact, has HF ever wished to make money? They probably pay AWS more infra cost than they earn. The exit was planned all along.
Was looking for this comment, the tech world has gotten completely insane with ”valuations”. I would love to hear why it was 13 and not 5. It would still be completely insane at 5 billion, but someone though they should add another 8…
Yeah, the price is weird as fuck.
Well congrats to Clem and the team. I remember when huggingface was doing things like coreference resolution models on spacy.
I hope nvidia does right by the community.
Edit to add: $13B should cover the S3 egress fees for a couple months :D
They need to switch to egrees free cloudflare R2!
I wonder if Cloudflare would find a cause to exclude them because I can't imagine the transfer amounts this would generate.
The $13b doesn't go to hugging face's bank acct to pay for anything like S3 egress fees... It go to hugging face's owners' Bank accounts for them to do anything else. New cohorts of billionaires and centi millionaires getting minted.
> billionaires and centi millionaires
I think you mean hecto-millionaires.
Totally, and as long as they don't turn on the AWS NAT Gateway, they'll be just fine.
Obviously, NVIDIA is trying to own the AI development chain.
Owning HF -- the discovery and distribution channel -- is one thing, but I think the biggest threat vector is the privileged access to HF platform data, that includes HW survey info and model download pattern. This can be a borderline anti-trust case.
If the acquisitions of late tell us anything at all, it's that Nvidia wants to be a vertical AI company, not a hardware or gaming company.
Also they bought the company which develops the open source slurm scheduler which is the primary and defacto standard HPC scheduler on the market. Bit of a concern to say the least
Pets.com, here we go!
Just a little bit longer and this whole "AI" insanity might finally be over! :)
Remember just 6 months ago that "Ggml.ai joins Hugging Face to ensure the long-term progress of Local AI" (https://news.ycombinator.com/item?id=47088037)
(Ggml.ai is llama.cpp.)
Curious if the “I consider HuggingFace more "Open AI" than OpenAI” sentiment in that top comment will still apply with NVIDIA as the boss now...
Nvidia is promoting "unmetered intelligence". Jensen wants everyone to have a spark dgx with an nvidia chip in their home.
Maybe but they make their real money in data centers. Certainly, they want to have fingers on every trend. Owning something the Government wants to control gives you more access to trade repression of open models for more Government favors and money.
NVidia has reasonable incentives to keep things open indefinitely, it wants people to use it's GPUs
Issue is that llama.cpp is the best way to run models on hardware that isn't nvidias.
Except when they have less than 16 gb of ram?
Nvidia is halving the production of its higher end GPUs, doubling prices and heavily segmenting the market. They don't give a single shit about individuals. One wafer that makes 10 5090s that might sell at 3000 each, or one wafer that it already sold 6 months ago for 200k to one of the incestuous AI companies it works with?
It'd be really nice if I could use my egpu 4090 on my macbook pro..
The more interesting is HF turned down a $500M Nvidia investment late last year at a $7B valuation, after passing on a $235M round in 2023 at $4.5B — going from "we don't want a dominant investor" to a $13B full acquisition in under a year is quite the reversal.
Well, if they didn't want a dominant investor, they didn't get one, they got acquired.
Sounds like it was just too much money for the stakeholders to refuse
Yea, my bet is that there is quite a long list of money bags sitting behind the leadership team that will weigh in if the offer is juicy enough.
Oh yeah, so surprising to refuse $500M that go in the pockets of your company that is now owned in large part by the investor, but then accept $13B that go directly in your own pockets.
I don't think they passed on the 4.5 billion. They still raised it in 2023 with investors like Alphabet etc. They turned Nvidia *earlier this year* for the $7 billion valuation deal. It makes sense if they were angling for an acquisition.
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...
Seems the opposite of a reversal to me.
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 :)".
I have never seen an acquisition be good for the users. I struggle to believe this one will be different
I'm sure it'll be fine. As long as you have the latest 90-class card you'll probably continue have nearly full functionality from the HF libraries. (Upgrade to enterprise gear for full functionality)
Is huggingface profitable?
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.
The fit is theoretically good (nvidia is model agnostic) but I can see then pushing the ecosystem increasingly towards cuda and some custom nvidia software packages for inference etc etc
Apple buying Workflow (became Shortcuts). Its users have a better, faster tool and got it soon after acquisition. And it has many more users now.
Was Workflow available on every platform running on every hardware provider?
I’m not sure your point, sorry.
That specific example might be relevant to the case "I don't see any acquisition being good for the users", but not for the specific case of the HuggingFace buyout. Workflow was already operating within the bounds of the closed Apple ecosystem. Huggingface is providing models not only for Nvidia chips but for their competitors hardware (Apple Silicon, AMD GPUs, ...).
I think that it was already iOS only, so making it free was just flipping a flag etc. I'm not sure how that helps his point tho.
Acquisition of GitHub let to increased downtimes, but also to unlimited private repos for the free tier.
The unlimited private repos for free tier would have happened anyways. You have to remember that this was around the time people were jumping ship from GitHub exactly because they didn't offer private repos for free. It was something many wanted, and they were actively seeking out other places that would give it to them.
Overall GitHub still got significantly worse since the acquisition. Downtime was essentially zero before.
Usage was 5% of what it is now before.
It was unreliable post acq. and before the slop-tsunami, the latter has just multiplied the underlying issue of their ipv4 only half assed azure migration.
... Which gitlab already had before github. And still does.
Truer words were never spoken. This is painfully true.
Yeah I'm afraid they will only keep cuda support for their software. Good thing it's all Open source
It feels really weird to see this when I keep seeing the CEO and CTO of HuggingFace push for local inference to win.
Why? If anything it makes complete sense:
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.
The hyperscalers were stable customers buying far more expensive equipment and NVidia has also made a bank selling a lot of auxillary hardware like Mellanox to AI datacenters.
But the spending spree is probably coming to an end with the looming IPO's and NVidia is probably trying to hedge their bets by making themselves the sure bet once big-AI stops monopolizing RAM and everyone races to get their local setups.
Nvidia is also pushing for local inference IMHO. They want open models and competition in the model layer, not two big labs controlling all of it.
NVIDIA buying HF feels like defensive move. They don't want open models become hardware agnostic. I bet we see more 'optimized for CUDA' push in one year.
Do they really need HF for that?
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.
That could be a factor, but the optimistic interpretation would be that they want to support the open ecosystem because it sells more chips.
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.
What is the business model of hugging face? My understanding was they were basically just a file hosting platform.
Here is an employee of HF at a time answering how do they make money, supposedly [1]
> 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.
Didn’t we just witness it? Become a critical ecosystem player then get acquired based on the value of that position.
I’m asking more to work out what is the basis of this valuation. Why would Nvidia spend $13B for what seems to be a services that gives things away for free.
Talking about profit is so passé in the new economic paradigm. The rules have changed— it’s about how much a company is worth. Get with the times.
–Some guys in every bubble I’ve witnessed.
I think Russ Hanneman calls it a "pure play" type of company. He put radio on the internet, so he would know.
I dunno. You can argue over whether they're overpaying, but it's not like Huggingface is Clinkle. They hit $150 million in ARR this year, they have tons of runway, and according to reports, have just started to even burn the money they raised a few years ago.
I get that it's fun to be glib about the stupidity of tech elites and investors in general, but Huggingface have been pretty open about their financials and are, in my opinion as a practitioner in the field, one of the most responsible orgs in our space. They've been a pillar of open source ML for years now and have made a very positive impact on our ecosystem.
Nvidia is getting a real business generating revenue, and the center of the universe for open models. Both seem like pretty valuable attributes, from Nvidia's perspective.
150 million a year? Why, at that rate NVidia will make their money back in just 86 years.
Solid point. I'm sure Nvidia went into this deal expecting completely flat growth and no other benefits to their core business. Sorta like how Meta never increased Instagram's revenue from $0 and is still waiting for it to pay off that billion dollar acquisition price.
Or like GitHub, which was generating something like 200 million in ARR and had never hit profitability when Microsoft bought it for $7.5 billion back in 2018. I'm sure it has come as nothing but a happy surprise to Microsoft that GitHub generated $1 billion in 2023. They had initially penciled it in for 38 years til ROI.
Can someone help me out - who pays for things on HF? Are they charging the model providers?
It's not too dissimilar from GitHub, but geared towards ML. They have a 9/mo pro plan for individual users for upgraded storage/usage, and an enterprise version of Hub that larger orgs can pay for. I think the enterprise has some contract minimum + 50/mo per seat. https://huggingface.co/pro
They also have inference endpoints with metered prices, and their spaces product (though i'd imagine this is a smaller portion of revenue).
This gets mentioned a lot, but the most valuable companies, by orders of magnitude, have the most profit, by orders of magnitude.
Risk management.
Nvidia has a market cap of $5T USD today, and a decent chunk of that is due to LLM speculation.
Does Nvidia want their stock price to be at risk of being tanked by a download service being in the news? No, they want to make sure the party keeps going and is under their direct supervision, and part of that is making sure Hugging Face isn't bought by a competitor or runs out of money.
If their stock moves up more than third of percent due to this they have won... The math at these valuations get somewhat extreme. But there is some logic in it.
> Why would Nvidia spend $13B for what seems to be a services that gives things away for free.
To stop that! Literally. To stop those services being free.
Why would Nvidia destroy the first place we all look for models to load on our Nvidia hardware?
for 6 months?
I don't understand who this is targeted at. You can download the models, clone the datasets free. Who is paying them and why?
This is like saying GitHub or Google just gives away everything for free
Not really. GitHub has a strong platform of paying customers and a solid product that’s hard to replicate.
Google is obvious.
Hugging Face is a file download mirror with a couple of side features dangling off.
They hit 150 million in annual recurring revenue this year.
Pretty nice dangling side features apparently.
That still leaves the company valued at 86 years of revenue
Yeah, great point. Nvidia could potentially be overpaying. Not sure how that equates to Huggingface being "a file download mirror with a couple of side features dangling off".
Just wait until you hear that Facebook bought Instagram for $1 billion in 2012, when it was generating no revenue.
While it's probably easier to say this in retrospect, they were eliminating a direct competitor to their core business. Something so advantageous it should have been blocked by regulators.
I can't see this as being as good of a purchase, especially when it's 13x the price of what was seen as an absurdly large amount back then.
You are very good at bringing up irrelevant numbers and missing the forest for the trees
You are right, we are in a post numbers and reality economy.
Absolutely none of this makes sense and the thing that amazes me is how long it has continued. Future historians will just laugh at how stupid and obvious the crash was.
Whether you realize it or not Hugging Face's monetization is just as obvious as GitHub's
They make it easy to run models. The models have to run on hardware somewhere.
Possibly, but they were profitable already.
This. They are buying a brick in the xkcd #2347 diagram
They have various paid services that relate to AI—paid inference hosting; paid accounts aimed at AI development with GPU rentals [credits plus paid overages, I believe], more private storage and public storage than free accounts; and many of the community a and some other benefits on individual/team/enterprise tiers; additional paid storage above the base quotas for the paid account tiers; on demand rentals of HF managed containers on GCP and AWS, and some other things.
If GLM-5.3 was truly trained and ran on Chinese chips, we'll have to ask what the business model of Nvidia itself is soon :)
Isn't this pretty much the model for any tech company? Rush to get MVP released, stoke the hype, cash in on FOMO.
I guess we may have to start paying to download models.
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 see the opposite — NVIDIA is aiming to commoditize the model layer and push open models that are tuned to run on NVIDIA hardware.
So much this. It's like Apple buying Shazam or any other software company, they do it to bring value to their hardware platform.
NVidia has been expending energy helping improve local models and inference platforms for them targeting NVidia GPUs; good free models that users can run locally rewards Nvidia’s investment in product lines for local inference (DGX, RTX PCs, etc), as well as—given their continued dominance in the space—the premium over competitors of their consumer and workstation GPUs.
Maybe everyone will migrate to Hugging Bay for downloading models via torrent?
File hosting isn’t that hard to replicate though. Even if they start charging people will just set up torrents for the files or lists of mirrors.
Unless I’m missing something, this feels like Nvidia having more money than they know what to do with.
Maybe they're trying to see how big the market actually is before considering shutting it down, maybe or getting lawyers and politicians to try and outlaw or restrict open models if they see a big enough opportunity.
it's literally the GitHub for AI
Github was acquired for $7B. It's hard for me to see how HF is worth almost double Github.
GitHub was acquired for 10B in 2026 dollars. And software on HF requires quite a bit more hardware expenditure to run.
It hugs your face
ondemand cloud? b2b?
The open weights AI ecosystem is way too concentrated with HF. That said, it was clear they were going to either get bought or aggressively monetized at some point, Nvidia seems like it could be one of the more aligned acquirers.
I do worry about any sort of crowding out or downplaying non Nvidia-relevant quants, and about changing rules to crack down on models or datasets that for one reason or another “don’t align with their corporate values” - uncensored etc. Someone mentioned Microsoft and GitHub, they appear to me anyway to have been very hands off, I hope it’s the same model.
There are always torrents, which would seem to be a fine way to distribute models.
We also have modelscope.cn, I'm sure that one won't get acquired
It's already part of Alibaba, which has its own incentives. So does kaggle with Google. Civitai is neutral but it is mostly nsfw even though they don't show it outright. Torrenting is the Best way
Potentially horrible for monopoly reasons, but if other big acquisitions in the AI era teach us anything, developers are about to get a whole lot of free and discounted trial credits.
That’s at least a plus. I will happily burn through as much VC money as they will give me to tinker with my projects.
Yes. Great for devs, for a while. Awful for overall competition and industry's health.
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).
> I think the federal antitrust regulators are asleep.
Have been for a long time. All of the big techs should have been broken up long ago.
You can torrent and seed these models via torrenting. They are not piracy so there's no problem hosting them besides maybe not having enough bandwidth
Interesting ideas, maybe the real open alternative will indeed be torrents.
... You wouldn't steal a car ... you wouldn't steal a bag ... piracy is a crime. (Girl cancels the download and walks away from the PC. Remember? :-))
That is what will happen to torrents. Followed by VPNs. China, Russia and Iran had paved the way already.
Can't you see the puzzle coming toghether?
Current US government is pay to play. As in buy my cryptocurrency and you get a pardon or case dismissal, no backroom deal required. Payment directly. Blatant corruption sucks.
If the House or Senate turn that might actually stop or slow down. The market falling by 30% when the AI bubble eventually pops would also trigger it.
Except for during Biden, they've been asleep for almost 50 years.
Now that you mention sleeping. I imagine one could do cool sleeping startups that clone something but exist only on paper. The sleeper startup is only launched the moment some ham fisted mega corp aquires the original and all the customers are looking for a way to abandon ship.
Won't work. Businesses need a proven track record before they can buy. With no established history of successes, this plan is already dead on arrival.
Lina Khan @ the FTC was the best thing about the Biden administration, for me.
I think failing to take advantage of the charisma of both Lina Khan and Janet Yellen, and not making them public-facing economics gurus like Alan Greenspan or Larry Summers historically were, was a huge tactical mistake by Biden.
Fair, but the biggest mistake by far was failing to take charge of the immigration debate. The second biggest was his press secretary's insistence on announcing that everything was fine in the economy over and over as a distant second. Third was not resigning when it became clear that he couldn't really keep up with the job, or at least not trying to run for a second term. Virtually nothing else matters by comparison.
Fear over economic damage due to immigration is perhaps the last remaining unifying force among the American political right wing. Biden actually did a lot of good things as president -- arguably a lot more good than he did in his time as senator. But his administration was too eager to just run the federal government as a quiet meritocracy and avoid dealing with any of the hot political issues of the day. He and his administration fucked up so bad that now not only is most of that good undone, but we are in a dire existential situation, facing generational-scale damage that might be unfixable.
It's one thing that they genuinely fumbled the handling of the huge immigration/refugee waves spanning the entire continent and it took them well over a year to start coordinating a response (which they never really did apart from eventually just closing the border) -- it's another that they kept trying to insist everything was fine, there was no problem, there's nothing to see here. People were freaking out about it all over the country, and of course they were being heavily propagandized, but that's not the point. A strong and proactive White House would have made all the propaganda look stupid. Instead, it looked like the truth.
It's absolutely mind-boggling to look back on just how weak the president had to have been from 2020-2024, to somehow let the party of Jan 6 and the disastrous handling of the Covid-19 pandemic regain enough control of the political narrative to make Trump seem like anything other than a narcissistic mobster.
Yellen was objectively the dumbest Treasury Secretary ever. When everyone and their dog realized inflation was getting out of control, she thought it was transitory. She literally gets an F- as an economist.
And some former Roomba employees may have thoughts about Kahn.
Kahn was right about Roomba. Amazon was going to torpedo all the superior competition on the Amazon platform where almost all robot vacuums are sold in the US, plus as the e-commerce monopoly, Amazon was going to instantly have access to an army of cameras inside people’s homes to analyze personal information related to purchase preferences.
IMO allowing Roomba to hit chapter 11 was still a better option for the consumer than handing them to Amazon. They’re still in business as an independent competitor on the market, consolidation was successfully avoided.
Yellen, I don’t have much of an opinion on, but she absolutely wasn’t alone in that opinion (the nuance of that opinion being inflated by this hyperbole), and the treasury is a lot less involved than the federal reserve in doing anything about inflation, anyway.
This is a tangent to my first comment parent to this one, but also more related to the actual article at hand: whether it's Amazon buying Roomba or Nvidia buying Hugging Face, I have a somewhat radical (or is it?) opinion that large companies like Nvidia, Amazon, Apple, Microsoft, Coca-Cola, etc, should not actually be allowed to acquire companies. At all. under any circumstances, even if competition is healthy.
These companies are generally large enough that they do not need the competitive aid of buying an existing company and starting with that sort of structural advantage.
E.g., did Nvidia not have enough money in their bank to start a company to compete with Hugging Face? This is a company that reportedly has ~200-300 employees with investment rounds totaling $400 million. Nvidia made $31.9 billion in net income last quarter.
I look at a company like Xiaomi which just developed its automotive division in-house without resorting to buying car companies. I think our traditional business and finance mindset has an overreliance on acquisitions.
Roomba was not competitive in the market, no amount of Amazon market manipulation would have changed that. Best case scenario, Amazon would have invested in making it competitive. Worst case, their engineers would have been absorbed into Amazon's warehouse robotics projects.
Is either of those worse than what actually happened: the company is now a zombie brand for a Chinese company?
Of course Amazon would have changed that. You would go on Amazon and search for "robot vacuum" and Amazon would put iRobot at the top of the results. Review manipulation on the platform would be trivial.
Amazon could email/push notification/text customers asking for reviews of iRobot vacuums but then not do the same for competing vacuums, skewing their reviews higher (asking for reviews boosts ratings by gathering opinions from happy customers who usually don't bother writing a review). Competing brands potentially don't even have your contact information to ask for a review.
Go on Amazon right now and search for "usb cable." There's a giant banner at the top that recommends the Amazon Basics brand, three across horizontally, which on my desktop monitor takes up nearly 50% of the screen real estate. Then below it are the Anker cables that you're more likely to be looking for.
They would have almost certainly been manipulating pricing on them as well. For example, they could take the strategy of lowering the price of the vacuums to break even or sell as a loss leader, but use them as a data-gathering robot in your house to help Amazon sell more of everything else. They could make their Alexa smart home platform preferential to iRobot or lock out competing models.
Robot vacuums are a consumer goods category that is heavily skewed toward Amazon.com as the place of purchase compared to other retailers.
I think "zombie brand owned by a Chinese company" is actually preferable, yes. They still operate and sell vacuums competing with the other robot vacuums on the market, and they aren't in service as household data collection bots for a monopoly e-commerce platform.
I don't think the ownership of the company being foreign or domestic is very relevant to the FTC's goal of preserving positive trade conditions. Would we think the iRobot situation was a bad outcome if iRobot was purchased by a foreign company we view more positively like Miele? We only think of it negatively due to anti-Chinese bias. iRobot being Chinese-owned is almost certainly the best possible outcome for preserving the amount of competition in the market.
iRobot is now 100% owned by Shenzhen Picea Robotics of China. (https://www.sec.gov/Archives/edgar/data/1159167/000115916726...)
Yes, that's a very good company to be the owner of iRobot, because they are just a robot factory and not a near-monopoly e-commerce retailer.
They are essentially on equal footing with other robotic vacuum manufacturers. iRobot didn't go out of business or get absorbed into a larger company lowering competition in the marketplace.
It's also not the FTC's job to ensure that companies, especially ones with zero/trivial national security or domestic labor force value, remain under domestic ownership. Amazon itself is not really a "domestic" company, it's publicly traded. Anyone from any non-sanctioned country can buy shares of Amazon.
> zero/trivial national security
Huh?
Robots with vision + sounds sensors and connected to the internet in professional homes across your country are definitely a security issue.
https://www.abc.net.au/news/2024-10-05/robot-vacuum-deebot-e...
One of the leaked images taken by Roomba robot vacuums shows a lady sitting on her toilet - personal.
How would you define a domestic company?
The company's name was iRobot, not Roomba.
I spent a little time working there around 2017. Whatever you're implying my former colleagues' thoughts on the subject are (or mine, for that matter), you're probably wrong.
I miss her. Actual government for the people.
I miss the Biden administration
Large numbers of people outside of the United States probably do.
I miss him from inside the United States too.
China and Russia are loving things right now.
I miss every administration back to Roosevelt.
That's a sad thing to have to say, but yeah.
The president who helped kil 15k children? Why do you miss him, he should be in the jail cell next to trump.
True, but better nvidia than any other big tech contender. Nvidia has a very strong business incentive to make huggingface thrive, whereas pretty much everyone else has the opposite incentive.
Yeah I think this is probably one of the best outcomes you could hope for if you want to use open models.
Especially when all major labs are building their custom inference chips.
> That’s at least a plus. I will happily burn through as much VC money as they will give me to tinker with my projects.
The era of VC-funded home-delivery recipe boxes is still my favourite.
The Government plans to regulate open source ai. Nvidea is dependent on the Government to back loans, provide property, and make laws in their favor. Now they have ownership of what the Government wants to control. A perfect wedge they can use to get more from the Government.
100x this: "The Government plans to regulate open source ai." and ... s/regulate/restrict
Yeah this is the "early netflix" era. Take advantage while you can and plan for the future.
Counter point is China can afford to keep pumping out free models for long enough to crash the AI industry, As well as spin up memory production.
Its likely in the near future we will be able to buy 128gb mac minis and run local AI for free.
Why would China want to crash the AI industry? Their goal is not to damage the United States, necessarily. Their goal is to have the best domestic AI on the planet. They intend to do that through the way that they dominate every other industry: good enough quality at a much greater scale.
Surely crashing the Ai industry (in terms of reducing commercial revenue) makes it harder for the leaders to keep raising money and so keep investing in r&d to the same levels. Thus allowing competitors without access to latest American hardware to keep up.
When did apple stop charging more for their memory upgrades then gold by the ounce costs?
They didn't, but their price increases haven't kept pace with general memory price increases (yet) so currently their pricing seems reasonable.
If we survive, that is.
That means we will torrent these ai models. They are not pirated so there's no problem doing so
We're entering consolidation
Nvidia is a public company. What VC money?
I think this is good.. They have incentives to keep things free to keep people using their GPUs. I think that's one of the least enshittifying outcomes possible
This isn't a good thing for open source.
Nvidia don't share CUDA, don't open source their drivers, don't support capable but older hardware (forget Pascal etc), and generally charge a premium over competitors for hardware.
This acquisition will likely solidify this general stance, reduce free compute allowance for a subscription, cap downloads, push advertising, generally favour models that are Nvidia prescribed or have been sponsored, and potentially ban models and datasets that are deemed risky legally (abliterated etc).
I see no other reason why Nvidia would want this kind of vertical.
To play devil's advocate: Hugging Face was probably not profitable, and someone has to pay the bills long-term. Nvidia benefits from Hugging Face and the operating costs are pennies to them. For them it makes sense to acquire HF just to keep it running. HF shutting down or self-destructing in the search of profits would be costlier for Nvidia than just buying it now
That said, I share all your concerns. The days of a permissive hands-off HF may be numbered
They had incredible revenue growth the last few years and just broke 100M in revenue. I don't know what their internal spend was , but that was almost half of their recent round in ARR. Mostly likely they were profitable or on a clear trajectory to revenue growth. Huggingface hosts a lot of data and models, but mostly static cold storage is pretty cheap tbh.
Why do you think it ‘probably was not profitable’ it has a dominant position and there are many ways to monetise that.
While nvidia may not want open source drivers, they want open weight models and this acquisition allows them to keep pushing for that.
Commoditize your complement.
Nvidia don’t fundamentally care about open weight models
They care about their high margin GPUs being the dominant platform, otherwise they would have to reduce the price of their gpu/increase vram amounts.
Nvidia are making truck loads of money and want it to continue
They actually do when all their proprietary model customers are also building their own chips.
+1 on @SillyUsername. Combined with recent acquisition of OpenRouter we see exactly what we were increasingly concerned about: tightening (chocking?) of Open Weights locally-run models. The sequence and timing of these events make the intent very clear.
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.
Nvidia does frequently release new OSS Nemotron models where they implement new mechanisms.
NVIDIA is open source software first for almost everything. You cherry pick a couple of things, but it's not the general sentiment.
This is the world we live in now. 3-4 megacorps owning everything in every major product category - eyewear, cosmetic, consumer goods, media, tech; you name it.
We live in now?
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.
We need small companies worldwide, developing the things huggingface does. The us china and Europe dominate while the rest of the world sits by idly. Torrent and seed ai models. It's not piracy
If you can't beat them, buy them. Hallmark of late-stage capitalism.
> Hugging Face turned down a $500 million investment offer from Nvidia late last year that would have valued it at $7 billion, the Financial Times previously reported. Hugging Face said at the time it did not want a dominant investor that could sway decisions.
So instead they sold themselves to the same investor completely ?
Money always wins, sadly.
I mean, it's $500M versus $13B.
Real title: "Nvidia has been in talks to acquire Hugging Face for more than $13 billion"
HF is the default platform to find models. Not just ones published by big labs but also a lot of the distilled or fine-tuned versions, etc.
If Nvidia buying HF makes it tough for all the diverse models on HF, then what are some alternatives?
It seems models are the best things to be available on a Torrent platform? Of course HF is much more than just the files but perhaps the metadata can be separate and hosted on multiple community platforms.
If HF didn’t exist, model releases would likely have been on torrents like Linux iso’s back in the day.
I'd honestly prefer that. I'm usually on 5g if not 4g and pulling models is an absolute nightmare when I basically have to use HF and even with a token getting throttled. Although I have a pretty unique use case. Pulling wads of 5gb tensor files over cellular is painful.
I am on the same boat, I live in a small Himalayan village. I have 2x5G based devices and one Wireless bridge (Ubiquiti LiteBeam M5) for a local broadband. Generally I get 50 Mbps, sometimes up to 100 Mbps
> what are some alternatives
good old torrents
There's over 3 million models on HuggingFace. So many quants. I'd imagine less than 0.5% would actually be seeded.
I don't know anyone who "finds" models on HF. The announcements always come through Reddit, HN, Xitter, and various Discords. HF is just a place where some people bought a domain name, spun up a file server, and struck it rich. If they went away tomorrow, they'd be replaced the next day.
I don't understand the CUDA lockin in 2026...
Surely anyone can take any piece of CUDA code and tell some LLM to port it to another platform and keep grinding till performance is identical?
Sounds like that's what z.ai did to get GLM-5.3-Flash running on Huawei chips.
Time to fork it and build a new place for true open source.
Also consider:
Nvidia is investing $1 billion in Poolside and paying $6 billion to license its technology and hire most of its engineers.
They are the elephant in the room, with their CDS sky-high. Sounds like they are opinionated on the whole AI thing, trying to drive this with open-source models, countering OpenAI using Jalapeno.
Looks zero-sum for the players.
All the while Google silently planning to get milk from all layers.
I am just curious, and I genuinely want to know, how is a 150 million a year in revenue company worth 13 billion dollars?
Same reason why GitHub was acquired for $7.5B at $250 million ARR which is 30x revenues:
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.
That doesn't make much sense to me. Companies don't just buy companies for absurd multiples out of the niceness of their heart.
In the case of GitHub, it was likely for data reasons + wanting to own where developers do work (VScode + Github).
In the case of HuggingFace, honestly not sure as I'm not familiar enough with their business. But I can assure you that Nvidia didn't buy them for 13 billion cause HuggingFace were desperate. When you're desperate, you sell for less not more.
> But I can assure you that Nvidia didn't buy them for 13 billion cause HuggingFace were desperate.
From Nvidia's side? You get to keep the shell game of where your money and hardware are going spinning on the table for a little longer. If the party stops, Nvidia loses a zero right off their valuation instantly.
And, as a side benefit, you get to place your thumb on the scale of the open-weight hosting ecosystem. And maybe even fund a Chinese Anthropic or OpenAI at a discount.
OpenAI just popped out an inference ASIC. Google is on their 8th generation of TPU. Graviton is out from Amazon. The hosting companies want Nvidia out of their finances. Full stop. Nvidia has to do something, or it's going to get swept away.
Somewhere, there’s a slide deck that shows future revenue going hockey stick.
Curvature and convexity matters even in "hockey-stick" models =3
Strategically, it matters - and nvidia’s strategy is to basically own the entire industrial supply chain of the future - they have interests in their suppliers, their competitors, their users.
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.
If they are mostly paid in NVDA stock and NVDA is also valued at 40x revenues or whatever insane multiple then it makes sense.
> Here have some of my monopoly money I can print and come join us at Nvidia!
Heh, thats a weird way to announced the death of HuggingFace.
AI companies seeking to release their own chips and Apple Metal and other unified memory solutions will all eat into Nvidias high margin GPU sales.
This can only be bad news, Nvidia didn’t buy hugging face to be good custodians but for business reasons.
Let’s hope an alternative platform emerges and takes off.
I remember when people realized gaming cards could be used for general compute (GPGPU) on certain types of parallel numeric work. It was a very cool thing for many types of hackers and science and engineering students and NVIDIA went far out of their way to ensure we could never buy it.
The optimal market strategy there (as in a lot of places) wasn't "sell as much as you can". There's often a superior strategy, when (as with HPC) you have minority industry customers who are very rich and have low price sensitivity. It's to raise the price to what those special customers are willing to pay, and to drop everyone else.
What NVIDIA did was to rip out FP64 capability, systematically, from all of their consumer cards. They firewalled off "useful for GPGPU" as a differentiating feature, segmented the market, and astronomically raised the price of what (if you were looking soley at cost-to-manufacture) could have been easily affordable to any ramen student.
(It's a more obscure version of the Intel-made-ECC-memory-disappear story).
See, e.g.
https://news.ycombinator.com/item?id=47068890 ("15 years of FP64 segmentation, and why the Blackwell Ultra breaks the pattern (nicolasdickenmann.com)")
Yes, this is ironic - it was the tinkerers using CUDA on cheap graphics cards that made Nvidia stuff useful in constrained academic environments.
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.
The same is true for the simultaneous NVENC video encoding session limit which is artificially locked for consumer NVIDIA GPUs (see https://github.com/keylase/nvidia-patch)
Marginally misleading title, article mentioned that "Nvidia has been in talks", not agreed to anything just yet.
https://www.theinformation.com/articles/nvidia-agrees-buy-op... is a little more definitive but paywalled and still doesn't confirm the other side of the deal - Hugging Face agreeing to the purchase.
The companies have aligned incentives so I don't think this is a terrible acquisition for customers.
Vertically integrated monopolies naturally have aligned in incentives for themselves, which allows more capture which turns out bad for customers. Whether it is a monopoly is an open question.
This isn't vertical integration. This is a commoditize your complements play and that does benefit customers. Nvidia benefits from supporting the open model ecosystem, if models are a commodity the gpus become what's scarce.
Someone with financial / decision making weight their is going to ask why they are commoditizing models that run on "others" GPUs .... Since doing that makes their gpus less of the scarce resource..
of course it is
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...
I really hope they retain and pay Georgi Gerganov. We are toast without ggml.
13b Jesus christ
Nvidia’s backstop deals are now reaching $130 billion. If neocould sales collapse Nvidia can direct that capacity towards Hugging Face, and recover some of that by selling directly.
Me, discovering only now that Hugging Face was founded by French people.
We're definitely better at maths than at promotion.
stripe buys openrouter. nvidia buys hugging face. everyone on the hunt for the app that will function as hub/broker/search/marketplace for models.
This whole thing made the AI attack on HF even more suspicious...
I hope they're good stewards. This reminds me of the Microsoft GitHub acquisition in terms of the importance to the broader community.
As someone who've played video games and obsessed over graphics cards long before this all started, don't get your hopes up.
as gamers, we got burnt by nvidia way too many times. I'm still holding grudge over shutting down 3dfx.
Nvidia is indeed a terrible company when it comes to open source, etc. however, as someone who has been gaming on desktop hardware since the 6xxx card days, Nvidia hardware has always worked. I switched to Linux full time since the 2XX days (maybe it was the 280 gtx?) and never had a lot of the problems everyone else got on Linux (using only the closed source drivers).
Likewise, their hardware has been rock solid and very performant for me. I bought most of my current setup second hand and they've been going strong for years now.
NVIDIA introduced programs like The Way It's Meant to be Played, optimizing major game titles specifically for NVIDIA architecture, which made competitions like AMD cards underperform in critical releases.
I'm old enough to remember.
I fail to see how this is a problem?
AMD could’ve done the same.
Amd and Intel have the same programs.
But they don't/didn't have the same level of market share as Nvidia, particularly in the PC gaming market. Nvidia had 65%-85% market share, and still worked with game studios to make sure their competitions failed. That's the opposite of good stewardship that's all I'm saying.
You are being disingenuous.
They worked with studios to optimize games for their hardware. I don’t think they went around sabotaging other companies hardware. They did what was good for them.
Why did competition not do the same?
3dfx was going through bankruptcy
I think they will be, Nvidia has released open source model that also included the data it was trained on. I think they are the only ones that have done that.
Handing out digging spots if you are the shovel manufacturer sounds reasonable.
As long as the spots continue to be compatible with shovels from other shovel manufacturers
So, this is the end?
Forgive me for newb question, but why Hugging Face is a thing at all? Couldn't models be simply distributed via torrents? And the whole aggregator thing would come down to indexing magent links published by model providers?
Then someone would still create a website with an index of all the open models. Where people discuss & rank the models, show related models, ...
And now you've recreated most of HF
Why don't we use message boards instead of Google? Couldn't websites be distributed via direct DNS requests instead of Google serving links?
Why is any file hosting service ever a thing at all, when literally any file can simply be distributed via torrents?
There's a herding effect with torrents where popular things are quick to get, unpopular things may be very difficult to get, because the majority of users delete files to save space.
I might host 3 or 4 models that I've downloaded recently, but I won't be hosting the 50 or so that I've tried in the last two years.
And who seeds it? If you're going to pay a host to seed it, they might as well just provide HTTP and let you add them as a web seed to your torrent, which we could be doing already.
But if you don't pay a host to seed it, either the host's business model won't play well with torrents, or there's no host and a torrent will rot.
(It was a retrospective question.)
Torrents are unreliable, also for an agent or script it's easier to just do wget model
You are not the first or 100th person to come up with this idea. I don't really get it either but there must be a reason it hasn't really happened.
Well, ask yourself: "Why am I on Hacker News?". You could just "as easy" use free / opensource alternatives like Lemmy, Mastodon, etc.
> Forgive me for newb question, but why Hugging Face is a thing at all?
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.
The important thing about HuggingFace isn't the safetensors files, it's the READMEs and the Google search placement. It's easy to reproduce their distribution with torrents, it's very hard to then establish yourself as the default option.
It would be far more efficient to decentralize the data. But HF provides convenience, they subsidize the cost. They gained millions of users, and many enterprises. They can now sell the popularity of their platform. Nobody can buy a p2p network of people.
beating the dead horse after other dozen comments, but the same reason we use github / gitlab instead of using Savannah
Very "why would anyone use Dropbox when I can setup a SFTP server" vibes.
Or even “why would I pay for a flight when I can simply walk across the country”
It’s all about the convenience, minimising the time and effort from “looks interesting” to “running the model”.
Nvidia don’t care if you do it on their cloud, someone else’s cloud, or on your own machine - they win either way, as it further propagates the technology on which they are building their future.
Torrents aren't that scary. If you have the patience for local AI you can figure out qBitTorrent in less than an hour.
hugging face is basically a real easy way to run llms. They also provide a bunch of libraries to do things like split compute across all your resources.
They were already pretty vocal about it, but this makes Nvidia pretty much the de facto face of open weight models.
As battle lines get drawn over duopoly vs. open weight it’ll be interesting to see what Nvidia does. They definitely want a piece of more of the stack especially as Huawei chips become more and more of an alternative to cuda.
Alibaba already has modelscope and their own chips, and qwen models. Nvidia is doing the same with chips, huggingface and nemotron models
Fix your title it's not finalized yet!
According to The Information, it seem it's finalized? https://www.theinformation.com/articles/nvidia-agrees-buy-op...
Then use that as the link.
Everything I can find online is referring to this one source. That doesn't tell me if it's happening or not.
Like some other folks, I wonder whether this will be a good thing, or a bad thing.
I feel like if Nvidia ends up turning into a bad actor, in terms of restricting/censoring models... another HF will spring up.
NVIDIA had more open-source models on huggingface than any other company. A lot better them than any other frontier lab, tbh.
Monumental implications on OS models. Proper investment in US OS incoming? HF has the best possible distribution to that audience
What does Linus’s hatred of NVidia drivers imply for this situation?
The lowest hanging fruit that hf could offer is community monitored commands for running local models.
Right now it is a pain to find the correct incantation.
Not good news and in the long run this circular move will fail for them. What are the alternatives?
Is there any cash involved or is this all stock?
Huggingface sold out. Sad day. All the good companies lose their 'dont do evil' clause as soon as they make bank
You've sold out when you became VC Funded... It's just a matter of how long the free punch lasts.
What, are you expecting them to just work for good vibes?
It was either they (literally) sell out or enshittify. Choose your poison. Hosting and running LLMs is an expensive business to be in. There wasn't ever going to be a good ending to this story. The original investors need to be made whole.
To be fair, this is the best thing that can happen for the founders. I don't blame them.
Looks like owning the hardware wasn't enough and they want to own the ecosystem as well
What’s with all the big acquisitions recently? Is it advantageous for some reason to announce all of this stuff now?
No, its just the final stage of the bubble before it all comes crashing down. :)
The VC capital for AI is probably drying up. Now the question is: who will buy OpenAI and Anthropic?
The public
Not if they can't indefinitely contain ram and SSD procurement. And they can't and the Market already showed with specex that they are unwilling to float these fly by night outrageous 'investments' onto institutional holders.
Institutional holders mass revolted at spacex getting into the basket.
AI costs more than having people do the work. Q2 CFO reaction proved that.
No, what? Did they just do this to make Chinese models harder to acquire outside of China?
They will just download them from modelscope
Great for Nvidia. Bad for the rest of us. Oh well, so much for hugging face.
That's a great news for a few rich wallets and bad for all of us.
I'm puzzled by the reactions. This is not a good thing. Yes, they're releasing more open source code and models, but they do it BECAUSE OF pressure from the community and other open source projects.
But Nvidia is a terrible open source and consumer company. They gatekeep a lot and oftentimes it's only open source in name. Outside contributions are often slow-walked or rejected if they don't align with business incentives , and leadership is retained 100% in a couple of people from a certain country.
Linus Torvalds: 'Nvidia has been the single worst company we've ever dealt with'
His other comments on Nvidia often contain expletives.
Linus isn't wrong but at the same time NV has shipped more compute than AMD and Intel combined to consumers. The kind of performance I get out of a modest outlay never ceases to amaze me.
Sales volume has no correlation with how good a company is for an ecosystem. See Microsoft, Adobe, Apple, Sony, and so on.
NV is a very different beast from all of those. I have yet to regret buying any of their products and I wouldn't touch your list with a stolen 10' pole.
In fairness, most of those comments were made before Nvidia capitulated in the EGLStream war and released open kernel modules.
Isn't it super easy for the community to just replace HuggingFace? Isn't it pretty much just a repo/index for open-weight models? Why is it even worth anything?
> Isn't it pretty much just a repo/index for open-weight models?
No, its not just a repo/index (they also have training, inference hosting, and they develop/maintain a bunch of core AI infrastructure software), and even if it was just a repo/index, replacing a bug centralized repo/index that used by an large community isn’t trivial.
Not just a repo/index but they also offer reasonably-priced compute, with a free tier not to sniff at, on which to run the models.
Network effects. It's like a social network for LLM nerds as well as hosting and rating models, etc.
It also means that finding models that aren't "approved" will be dealt by other websites.
good or bad, it comes down to a financial decision. Nvidia was willing to offer the highest bidding price, and HF was willing to sell.
Brilliant replacement of http://build.nvidia.com to increase developer reach and deployment of nvidia open models!
HuggingFace offers abliterated/uncensored models, which would seem to run contrary to the "AI is too powerful for regular people" narrative that the big players are pushing.
My primary concern is that Nvidia will bow to the pressure and restrict abliterated/uncensored models on HF.
Pretty sure Nvidias dream is that OpenAI and Anthropic get into a hacking war using Nvidia cards.
The problem for them is that the leading provider of training and inference is actually AWS...
That is a very good point. I will set aside some storage and download those models that I think are most at risk from a corporate clean-up action.
I don't think nvda has ever pushed the idea that ai is too powerful for regular people.
That's the anthropics and openais of the world.
Is it because OpenAI hacked it? :)
I wonder if OpenRouter being acquired was a catalyst for this deal.
Let the enshittification commence.
Its becoming impossible to track all the acquisitions.
Nvidia overpaid for Hugging Face.
Monumental implications on OS
Hold on, these say no deal has been reached yet.
Nvidia has already a good free offer with Nim and a lot of compute power available. Plus, they obviously have interest in spreading open models culture.
So is the next step to just basically create a cloud business.
they basically own chips - data centers - discovery etc?
I'm more worry than positive tbh.
Good timing
I’ve asked ChatGPT etc a few times how Hugging Face makes money. Never quite got to understanding . Good for them.
You could just go to their website and look at the pricing pages? Why are you asking an LLM?
Because I never ever see anyone talking about using it, except for occasional reference to weights.
Gemini did a good job of explaining it. fwiw, it may have helped that i accused Gemini of leading me to a "scam site" like "mega dot com"
Congrats to the team. I have a strong feeling this will go down in history as one of the last great exists before the bubble bursts.
12-24 months from this acquisition will likely look like a crazy burn of capital and cash.
Best case scenario
Big Wolf buying the sheep farm. Nice
not even 27b :C
Boy, there sure is a lot of money flying around...
First they came for all the dev tooling - uv, Cursor, etc. Now the routers and providers - Open Router, Hugging Face...
Who or what is next? And what is the endgame I wonder??
We keep talking about EU having to be more present in the AI race, but if the lifecycle of European AI companies is to be bought by US ones, what’s the point?
Wow, nice strategic move and price seems a bit low tbh. Good deal.
welcome nvidia :)
I wanted to pray for AMD to attack somehow but then I remembered their owner CEO's are cousins. Should we pray for Chinese GPUs?
nvidia antitrust incoming
Oh jeez
I really wonder why Nvidia would do this.
Ai companies are making their own chips, Apple unified and other unified ram solutions also a threat
Nvidia is making tons of money by selling GPUs at a very high profit margin. They will do anything to remain dominant
Keep alive the on-prem hardware sales? Not as big part likely but still something good to have. On-prem hardware needs models to be available to be useful. So pushing those could sell more on-prem hardware.
Owning the roots, the trunk, the branches and the tip of the leafs.
Oh no. I use huggingface all the time. Sad news.
whoa
This is huge!
s-1.site
Just like that they lost their ethos. AI oligarchy in the US is now cemented.
I really wish I'd done better bookmarking back when Nvidia was talking about acquiring ARM. There were all kinds of things coming out saying, if we do this, even though we will be taking over ARM, it will transform us from the inside out. We would become a new different company, that cares about something beyond our own self interest, our own chips.
This feels like a similar leap of faith. One that is hard to believe in. Thankfully, I think Nvidia can keep the lights on here & keep this going. I don't think they have to do much, per se. But it felt implausible then to image an Nvidia that gave a shit about anyone else, an Nvidia that actually gave a flying fuck about drivers or upstream Linux or ecosystems that weren't entirely within their own control.
Similarly the upper quartile of succes here feels mostly like benevolent neglect. I think we can hope for Nvidia to just not mess up a good thing, for them to understand that this open model open ai universe hinges upon Hugging Face, and for them to pretty please keep caring about the existential risk of the hyper-ai'ers all building their own properietary models on proprietary hardware and leaving Nvidia behind some day, and HF being the hedge against being left behind.
um um um um do we want nvidia to be on the same network as hugging face given the recent incidents?
could you elaborate on what happened?
the title of this post is misleading… “in talks” != not “agrees”
It’s not misleading according to the The Information piece (second link)
> Nvidia Agrees to Buy Open Source Model Repository Hugging Face For $12.9 BillionThe story is in an intermediate state right now, but as semiquaver points out, The Information is reporting it as fact. Since their reporting tends to be as reliable as it is hardwalled, we went with their claim in the title.
Anyone old enough to remember anti trust laws or even just laws?
Please don't post unsubstantive comments to Hacker News.
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.
You are right but its the initial shock on bad news, hopefully this will spawn alternative competing services.
I thin HF holds huge power in how they’ve consolidated all the open models and data, but monopoly feels like a stretch here. They are in reality a fairly small startup with lots of alternatives (all of which are much worse at this point granted) and are mostly a loss leading part of the open source ecosystem. I think it would be very hard to make a case against this on monopoly grounds, though I wouldn’t be opposed to someone trying if they thought it was possible.
The AI judge doesn’t have that feature yet
Laws are for poor people
tldr: the marketplace for opensource models became wide open
DISASTER.
Licensing. (And there is no 2nd Amendment for this one)
EU regulators...wake up!
They absolutely should, but what would be their impact on American companies buying each other out?