Nvidia Buys Hugging Face for $12.9 Billion and Pledges to Keep Platform Open

Nvidia Buys Hugging Face for $12.9 Billion and Pledges to Keep Platform Open

Nvidia announced Thursday that it has agreed to acquire Hugging Face for about $12.9 billion, bringing one of the largest platforms for open AI models, datasets and applications under the chipmaker. Nvidia said Hugging Face will continue operating as an open platform, with developers remaining free to choose their preferred models, frameworks, cloud providers, inference services and computing hardware.

The deal combines Nvidia’s infrastructure and engineering resources with a platform used by more than 18 million developers, researchers and creators. Hugging Face hosts more than 3 million models, 500,000 datasets and 1 million applications, while more than 200,000 companies use the service to discover, test, customize and deploy AI.

Nvidia is paying $11.9 billion to Hugging Face shareholders, while another $1 billion in equity is intended to retain employees who join Nvidia, according to a securities filing cited in the additional reporting. The transaction is expected to close in the first half of next year.

A central part of Nvidia’s announcement is its commitment to preserve Hugging Face’s hardware and software independence. The company said Nvidia compute will not be required to build on the platform or deploy models through it. Hugging Face will also continue supporting open-source and open-weight models from other developers, along with multi-cloud and multi-accelerator deployment.

That commitment addresses one of the most important questions created by the acquisition: whether ownership by the dominant supplier of AI computing hardware could change how Hugging Face supports competing infrastructure. Nvidia said developers will continue to decide which hardware and services best fit their work.

Nvidia already has a substantial presence on Hugging Face. The company has published more than 500 models and over 250 open datasets on the platform and describes itself as Hugging Face’s largest contributor of open models and data.

CEO Jensen Huang has also publicly backed open-weight AI. In announcing the transaction, Nvidia argued that giving organizations access to models they can modify and deploy themselves expands the number of companies, universities and public institutions able to build AI systems without developing every model from the beginning.

The acquisition gives Hugging Face considerably more resources to expand its infrastructure. Nvidia said its engineering capacity and global reach could be used to improve areas including platform reliability, safety, model evaluation, inference and deployment while maintaining the broader open ecosystem around the service.

Hugging Face has recently been drawn into the debate over access to advanced AI systems. The company was hacked during a testing incident involving OpenAI models and later said it had relied on an open Chinese model to defend its systems because restrictions on closed models limited how they could be used.

The transaction also represents a sharp increase from Hugging Face’s previous private-market valuations. The company was valued at $4.5 billion after raising $235 million in 2023. According to the Financial Times reporting cited in the additional article, Hugging Face rejected a $500 million Nvidia investment last year that would have valued the company at $7 billion.

Hugging Face CEO Clem Delangue told CNBC that he approached Nvidia about a transaction over the summer after concluding that open-source AI had reached a “turning point and that it needed more resources, more scale, more visibility.”

Nvidia said the Hugging Face team will join the company while retaining the Hugging Face brand. Huang framed the acquisition as an expansion rather than a shift away from the platform’s existing model.

“To the millions of builders on Hugging Face: thank you for pushing the boundaries of what is possible,” Huang said. “Together, we will make AI more open, more capable and more accessible to people and institutions around the world.”

This analysis is based on reporting from NVIDIA.

Image courtesy of NVIDIA.

This article was generated with AI assistance and reviewed for accuracy and quality.

Updated Sep 3, 2026

About this article: This article was generated with AI assistance and reviewed by our editorial team to ensure it follows our editorial standards for accuracy and independence. We maintain strict fact-checking protocols and cite all sources.

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