By Maria Larson
Copy Editor

Nvidia has agreed to acquire Hugging Face for $12.93 billion, a move that shows the company wants to expand beyond the computer chips powering much of the artificial intelligence boom.

Hugging Face is often described as the “GitHub for AI,” a place where developers, researchers and students share artificial intelligence models, data sets, applications and documentation.

Nvidia entered the definitive agreement Sept. 2. The transaction has not closed and is expected to be completed in the first half of 2027, pending regulatory approval and other customary conditions, according to Nvidia’s filing with the Securities and Exchange Commission.

According to TechCrunch, Hugging Face generates about $150 million in annualized revenue. Nvidia’s offer of $12.93 billion is roughly 86 times that figure.

The valuation reflects more than Hugging Face’s current revenue. Its strategic value lies in its developer community, library of models and data sets, and position as a starting point for many artificial intelligence projects.

Hugging Face is similar to GitHub, but instead of focusing mainly on computer code, it helps people find, share and use artificial intelligence tools. Users can browse models, read documentation, explore data sets, test applications and publish projects for others to use.

Nvidia said Hugging Face has more than 18 million developers, researchers and creators using its platform. The company also said the platform includes more than 3 million models, 500,000 data sets, 1 million applications and more than 200,000 companies.

Many models shared through Hugging Face are open-weight models. That means developers can access the trained model files and, depending on the license and hardware requirements, may be able to run or adapt them for their own projects.

For students, that can mean more than using a chatbot online. A student working on a chatbot, language-analysis tool or image-recognition assignment may use Hugging Face to find a model, examine documentation, locate a data set or test an application.

In some cases, developers can use a smaller version of a model that requires less memory and computing power. This process is called quantization. It can make some models more practical to run on a laptop, desktop computer or smaller cloud service, although a smaller version may not perform as well as the original model.

Not every model on Hugging Face is free, fully open or able to run on a personal computer. Models can have different licenses, access conditions and technical requirements. Still, the platform gives students, researchers and independent developers a way to experiment with artificial intelligence tools without building every system from scratch.

Nvidia is already one of the most powerful companies in artificial intelligence because it sells the graphics processing units, or GPUs, and data-center systems used to train and run many advanced AI models. The Hugging Face deal would extend Nvidia’s role into the software and developer side of the AI industry.

Nvidia has supplied many of the engines behind artificial intelligence. Hugging Face would bring Nvidia closer to the people deciding what to build with those engines.

The deal is strategic because many of Nvidia’s biggest customers are also looking for ways to become less dependent on Nvidia. Large cloud and AI companies still use Nvidia’s high-performance hardware, but some are investing in custom chips and alternative systems to lower costs and gain more control over their AI infrastructure.

Hugging Face users are not automatically Nvidia customers. A model downloaded from the platform may run on an Nvidia GPU, an AMD GPU, an Apple computer, a central processing unit, or CPU, or through a cloud provider. Hugging Face reaches developers before they decide which model, hardware or cloud service they will use.

Nvidia pledged that Hugging Face would remain an open and hardware-neutral platform. In its SEC filing, Nvidia said users would continue to be able to upload and download the models and data sets of their choice and that the platform would support other chipmakers. Nvidia also said developers would not be required to use Nvidia computing hardware to build or deploy AI projects through Hugging Face.

Still, the acquisition raises questions about concentration in artificial intelligence. Nvidia already has major influence over the chips and data-center infrastructure used to power AI. If the deal is approved, Nvidia would also own a major platform where developers discover, share and distribute AI models.

The question is not whether Nvidia will immediately close Hugging Face or force users to buy Nvidia chips. Nvidia has promised it will not. The larger question is whether a major platform for open AI can remain meaningfully neutral when it is owned by the company with the strongest financial reason to encourage developers to use its hardware.

Nvidia is paying nearly $13 billion for access to millions of developers, a large collection of models and data sets, and a stronger role in the future of artificial intelligence. Now, attention will turn to what Nvidia does with Hugging Face. Will the acquisition bring new tools and resources to the platform, or will it change the way developers use one of the largest AI communities in the world?