Nvidia doesn’t need to block rival chips on Hugging Face. It just needs the defaults.

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Nvidia has reportedly agreed to buy Hugging Face for $12.9 billion, putting one of the biggest names in AI hardware in charge of a platform developers rely on to find and run open models.

The Information first reported the deal Wednesday, citing a person familiar with the agreement. Nvidia and Hugging Face had not publicly confirmed it as of publication.

Hugging Face doesn’t push developers toward one chipmaker, which is what makes the acquisition interesting. Its Optimum libraries work with Nvidia’s TensorRT-LLM and also support hardware from AMD, Intel, and AWS. Projects such as Optimum AMD and Optimum Intel let developers run Transformers and Diffusers models on non-Nvidia hardware.

The company also plays a role in what happens after a developer chooses a model, including how easily they can get it running on the hardware they want to use. Nvidia’s ownership could change how equal those paths really are.

The company also plays a role in what happens after a developer chooses a model, including how easily they can get it running on the hardware they want to use.

Hugging Face already sits between the model and the chip

Hugging Face has expanded well beyond file hosting. With Inference Endpoints, developers can deploy a model from the Hub while Hugging Face handles the underlying infrastructure.

Those hosted deployments can run on AWS, Microsoft Azure or Google Cloud, but most of the GPU options Hugging Face lists are Nvidia chips, including the T4, L4 and A100. That gives developers a wider choice of hardware through Hugging Face’s open-source libraries than …

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