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Home » Hugging Face goes from a ‘scrappy’ startup named after an emoji to $13 billion Nvidia acquisition
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Hugging Face goes from a ‘scrappy’ startup named after an emoji to $13 billion Nvidia acquisition

Press RoomBy Press Room3 September 20269 Mins Read
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Hugging Face goes from a ‘scrappy’ startup named after an emoji to  billion Nvidia acquisition

Welcome to Eye on AI. Emily Forlini here, filling in for Beatrice Nolan. In today’s issue:

  • Nvidia will purchase open-source AI platform Hugging Face for $13B
  • OpenAI debuts GPT-6 Astra model
  • Google debuts Gemini 3.8 Flash model
  • ChatGPT experiences second outage in three days—and Claude, Grok also go down

Reporting on AI every single day has admittedly made me bit numb to the astronomical sums of money flowing into the industry, but today my eyes did a cartoonish pop when I saw how much Nvidia is buying Hugging Face for.

“Nvidia has agreed to acquire Hugging Face for $12,930,300,000,” a blog post said. While it’s not the biggest sum we’ve seen in the AI industry, it’s quite the startup exit for Hugging Face. The company was founded in 2016 by three French entrepreneurs living in New York City, who named it after the 🤗 emoji. Over the next 10 years, it has grown into a trusted repository for AI developers.

“It’s been a wild ride for Hugging Face,” cofounder Thomas Wolf said on X. “We certainly did not anticipate, back in 2016, as a tiny team of scrappy underdogs, that the field would grow so much or that the impact we could have on it would become so massive.”

The deal also makes clear how important open-weight models, like the ones Hugging Face hosts on its platform, are for the future of Nvidia’s business. As OpenAI, Microsoft, Amazon, Meta, and other closed-source AI heavyweights that have been major customers of Nvidia develop their own chips to reduce reliance on Nvidia GPUs, the company sees open-weight models as a core future revenue stream.

For Hugging Face, getting bankrolled by Nvidia could mean major growth for the platform. It currently has 18 million individual users and 200,000 enterprise clients, Nvidia told reporters today. “Our goal is is to get to 100 million AI builders in the next few next few years, and we think with the support of of Nvidia, we have more chances to get there faster,” Hugging Face CEO and cofounder Clément Delangue said.

But while Nvidia and Hugging Face line their pockets, the individuals that created and listed models on Hugging Face haven’t seen a dollar.

“It’s unfortunate [Hugging Face] never found a way for us to monetize our creations,” Eric Hartford, creator of an open-weight model called Dolphin, Chief Scientist of lazarusaie.com, and the founder of quixi.ai tells Fortune. “If I got a dollar for every download of Dolphin I’d be rich.”

Hugging Face turned down Nvidia in the past. Why now?

Nvidia has had its eye on Hugging Face for years. It participated in the company’s 2023 Series D funding round, which valued Hugging Face at $4.5 billion, TechCrunch reports. Last year, Hugging Face turned down a $500 million investment offer from Nvidia that would have valued it at $7 billion, because the investment would have made Nvidia the company’s largest minority shareholder and the founders wanted the platform to keep its independence, according to The Financial Times.

So, why did they agree to the deal now? In a briefing with reporters today, Delangue did not confirm the $500 million offer, and said previous reporting on the company’s fundraising can be “quite far from reality” since Hugging Face never publicly comments on it.

“The truth is that throughout the life of Hugging Face, we always got quite a lot of offers for acquisitions that we turned down in the past,” Delangue said. “I think this summer the planets aligned…we increasingly were convinced that Nvidia would be the perfect home for us, and so our confidence grew tremendously, and we decided that it was the best thing to do for Hugging Face, but also for the field and for AI in general.”

He’s likely referring in part to a letter Nvidia CEO Jensen Huang signed on the importance of open-weight models, which became his first X post. “Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty,” the letter said.

Also this summer, Hugging Face gained more mainstream name recognition after OpenAI’s models hacked into its repositories during training. I have to imagine that boosted the company’s brand recognition, creating the perfect storm to coax a big offer out of Nvidia.

Can Hugging Face stay neutral, or will its models now favor Nvidia hardware?

Now, the big debate in the AI industry is whether Nvidia’s acquisition will subtly influence the open-source ecosystem to favor its hardware. Model creators could choose to build their models for Nvidia hardware, especially if that makes it easiest to launch them on Hugging Face and for others to use them.

Nvidia said Hugging Face “will remain an open platform” in which developers can freely choose the models, frameworks, and computing platforms that they want. “Nvidia compute will not be required to build on or deploy through Hugging Face,” the company said.

However, some say there’s already a suspicion that Hugging Face is subtly biased toward Nvidia, and the acquisition is likely to accelerate that tilt.

“Hugging Face runs a giant library called Transformers, which is the gatekeeper for model releases,” Hartford said. “Though they have had a natural bias for Nvidia due to its overwhelming popularity, they haven’t been unnaturally biased, or mis-incentivized. With Nvidia ownership that all changes. They will still be the gatekeepers, and they will be unnaturally incentivized to favor Nvidia and disfavor Nvidia’s competitors. Not because of a conspiracy theory, but [because of] the dynamics of ownership.”

Nvidia also offers its own open models and data on Hugging Face, and says it’s “the largest contributor” on the platform, offering “more than 500 models” and “more than 250 open datasets.” It could advertise these models on Hugging Face now, as the platform owner, and gain more users.

On a more optimistic note, all of this could be a good thing for the business world. Open-weight models offer more customization and transparency than closed alternatives from the likes of OpenAI or Anthropic. It’s possible this acquisition makes it easier for organizations that are open-source-curious to finally take the plunge, opening up new ways to use AI.

With that, here’s more AI news.

Emily Forlini
[email protected]
@emilyforlini

FORTUNE ON AI

OpenAI launches GPT-6 Astra, its most powerful model yet and touts its ability to use your computer—by Emily Forlini

Google shipped four Gemini Flash models in 106 days. But its flagship frontier model is still nowhere to be seen—by Wen Shao

Safety experts warn novel design of OpenAI’s Astra model could make future AI agents harder to monitor—by Jeremy Kahn

Anthropic pauses some AI training following rogue agent hacks. Here’s how it compares with OpenAI—by Beatrice Nolan

Mamdani to New York City kids: No AI until high school—by Catherina Gioino

AI IN THE NEWS

ChatGPT, Claude, and Grok are experiencing outages. ChatGPT is down for the second time this week, and now Claude and Grok are also either fully down or experiencing issues, according to MacRumors via DownDetector. Wondering when you’ll be able to get any work done again? You can track the status here for ChatGPT, Claude, and Grok.

Anthropic lines up against OpenAI and Google over Massachusetts AI bill. Anthropic is breaking with OpenAI and Google over a Massachusetts proposal that would require major AI developers to hire independent evaluators to assess their models for catastrophic risks every four months. Anthropic and AI safety groups argue the measure would raise the bar for safety without stifling innovation, while OpenAI and Google warn that state-by-state testing mandates could create fragmented oversight and compliance uncertainty. The fight highlights states’ growing role in AI regulation as Congress remains slow to act, with Massachusetts’ approach potentially serving as a model for legislation elsewhere. Read more here from The Information. 

Novice hikers who planned their trip with Gemini call for rescue. A trio of inexperienced hikers that relied heavily on Gemini to plan their route up California’s Mount Shasta eventually got lost and had to get rescued by U.S. Forest Service rangers. “They were advised by Gemini to bring far less food and water than their group required,” rangers said, calling the reliance on AI a “critical misstep.” More from NBC Bay Area.

Vice President JD Vance says some AI use has “dark, satanic energy.” In an interview with Christian podcaster Bryce Crawford, Vance expresses more hesitation about AI, including data centers, than we typically hear from the Trump Administration, NBC News reports. Meanwhile, Trump says communities that don’t want data centers built will “end up being backwards and poor” on Truth Social.

EYE ON AI NUMBERS

22%

Although it might seem like AI has taken the entire business world by a storm, a new Gartner survey finds just 22% of organizations have successfully implemented and scaled up AI operations across multiple divisions.

The most common uses for AI, as reported by C-suite leaders, are cybersecurity threat detection and response (54%), IT service desk automation (54%), and automated code generation and refactoring (44%).

AI CALENDAR

Oct. 1: Fortune AIQ conference, New York. Apply here to attend.

Oct. 2-4: The Curve, Berkeley, Calif. 

Nov. 16-17: Fortune 500 Innovation Forum, Detroit. Apply here to attend.

Dec. 6-12: Neural Information Processing Systems (Neurips) conference. Sydney, Australia.

Dec. 7-8: Fortune Brainstorm AI, San Francisco. Apply here to attend.

Inside the “lifemaxxing” economy

Nearly half of all Americans wear a fitness tracker, up from just 13% a decade ago. But while early wearables just counted steps, connected fitness giants like Oura and Tonal are using artificial intelligence to predict your recovery before you even feel it. Fortune senior writer Allie Garfinkle goes inside the $2 trillion wellness economy to test the tech, analyze the multi-billion-dollar data moats, and ask a fundamental question: Is hyper-optimization making us peak performers, or just more anxious? Watch the video here. 

 

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