Nvidia Hugging Face Acquisition Confirmed at $12.93 Billion

The Nvidia Hugging Face acquisition is now official, with Nvidia agreeing to buy the AI developer platform for $12.93 billion. Nvidia announced the deal on September 3 after weeks of reports about a potential transaction. The agreement is expected to close in the first half of 2027, subject to regulatory approvals and other customary closing conditions.

Hugging Face is one of the largest open AI platforms, hosting more than 3 million models, 500,000 datasets, and 1 million applications. Nvidia says more than 18 million developers, researchers, and creators use the platform, while more than 200,000 companies use it to discover, evaluate, customize, and deploy AI.

What the Nvidia Hugging Face acquisition includes

Nvidia's SEC filing says the transaction includes approximately $11.9 billion payable to Hugging Face stockholders, subject to adjustments, plus an equity-based retention program of up to about $1 billion for employees who join Nvidia. The headline transaction value announced by Nvidia is $12.9303 billion.

The deal gives Nvidia a much larger role in the software and developer layer around AI models. Hugging Face provides model repositories, datasets, libraries, applications, evaluation tools, and deployment services. Its platform is used across different model builders and hardware ecosystems rather than being tied to a single chip vendor.

Nvidia says it will provide Hugging Face with additional infrastructure, engineering resources, and global reach. The company specifically highlighted improvements to platform reliability, safety, model evaluation, inference, and deployment capabilities.

Hugging Face will remain an open platform

The most important condition for developers is Nvidia's commitment to keep Hugging Face open. Jensen Huang said developers will continue to choose the models, frameworks, clouds, inference providers, and computing platforms they want. Nvidia compute will not be required to build on or deploy through Hugging Face.

Nvidia also said Hugging Face will continue supporting open-source and open-weight models from across the ecosystem, along with multi-cloud and multi-accelerator development and deployment. That means the acquisition does not formally turn the platform into a Nvidia-only environment.

That distinction matters because Hugging Face's value comes partly from being a neutral place where developers can work across competing AI stacks. The platform has models and datasets from many organizations, while Nvidia is one of the dominant suppliers of the computing hardware used to train and run AI.

Why Nvidia is buying Hugging Face

The Nvidia Hugging Face acquisition expands Nvidia beyond chips and into a developer platform that sits closer to the day-to-day process of building AI applications. Nvidia has already invested heavily in open models through its Nemotron family and says it has released more than 500 models and more than 250 open datasets on Hugging Face.

The strategy also gives Nvidia a direct relationship with a large community of developers and companies evaluating AI models. That can help Nvidia support workloads across training, inference, evaluation, and deployment rather than competing only at the hardware layer.

The move is especially relevant as major AI customers develop their own accelerators and as open-weight models become more capable. Nvidia can use Hugging Face's platform reach to strengthen the software ecosystem around AI while still allowing users to deploy models on competing hardware.

Saganote previously covered the reported deal in Nvidia's $12.9 Billion Hugging Face Acquisition. Nvidia has now moved the story from reported negotiations to a signed definitive agreement, with closing still dependent on regulatory approval.

What changes for Hugging Face users

For users, the immediate promise is continuity rather than a new Nvidia-only service. Existing open-source and open-weight workflows are expected to remain supported, and Nvidia says users will retain the ability to choose different cloud and accelerator providers.

The bigger change could come from the resources Nvidia puts behind the platform. More infrastructure could improve hosting and inference capacity, while additional engineering resources could expand model evaluation, safety, and deployment features. Those are areas where scale matters as the number of models and applications on the platform continues to grow.

The transaction is not closed yet. Nvidia expects the acquisition to complete in the first half of 2027 if the required regulatory approvals and other closing conditions are satisfied.