Nvidia has agreed to acquire Hugging Face for $12.9 billion, according to The Information, citing a person familiar with the deal. If the report is accurate and Nvidia indeed buys Hugging Face, the purchase could strengthen Nvidia's open-model strategy, provide another route to sell AI hardware, and help defend its hardware business as Anthropic, Google, OpenAI, and other major hyperscalers develop their own accelerators.Go deeper with TH Premium: AI and data centers(Image credit: Microsoft)The data center cooling state of playThe custom AI ASIC state of play America’s AI chip rules keep changing — and the rest of the world is paying the priceGTC 2026: Ian Buck press Q&A transcript — VP of Hyperscale and HPC speaks out on shelving CPX and shipping LPU decode this yearDemand for data center CPUs has surged, and AI agents are responsibleNvidia sells hundreds of billions worth of AI hardware every year. Although the ubiquity of its CUDA software stack and leading performance of its hardware are the primary reasons why Nvidia's AI platforms are sold like hot cakes, another important factor is that many AI models were trained on Nvidia hardware and are optimized to run on it. Therefore, the more models trained on Nvidia hardware, the more products the company is going to sell eventually. Hugging Face is an AI development platform best known for the Hugging Face Hub, a GitHub-like repository where researchers and developers publish, discover, download, and collaborate on AI models, datasets, and applications. Hugging Face also develops widely used software such as the Transformers library and provides tools and cloud services for training, optimizing, and deploying models on different types of AI hardware.In addition to hosting models, datasets, and applications, Hugging Face provides software that helps developers optimize and deploy AI models on different CPUs, GPUs, and AI accelerators, while its Inference Endpoints service lets customers run models on managed infrastructure hosted by AWS, Google Cloud, and Microsoft Azure.To make things simple, Inference Endpoints allows customers to select the provider, region, hardware type, and instance. What is important here is that the hardware used by Amazon, Google, and Microsoft is not all Nvidia. Hugging Face currently offers, depending on the provider, AWS Inferentia, AMD Instinct, Google TPU, Intel CPUs, and Nvidia accelerators, among other configurations.OpenAI models, datasets, popular applications, and abilities to optimize and deploy AI models on different hardware make Hugging Face strategically important to Nvidia. On the one hand, the company can make the platform exclusively rely on its hardware, though this may face a backlash from the community, so this is something unlikely to happen in the short term (even assuming Nvidia is indeed set to buy Hugging Face). On the other hand, Nvidia wants open models to remain competitive with proprietary offerings from companies like Anthropic and OpenAI that may eventually get optimized for proprietary non-Nvidia hardware. Nvidia has been building its own Nemotron open models and has committed tens of billions of dollars to the effort. Furthermore, as Hugging Face grows, so is adoption of AI hardware in general and Nvidia hardware in particular.Hugging Face is growing rapidly, but its revenue remains modest compared with the purchase price, according to The Information. The 10-year-old company recently reached approximately $150 million in annualized revenue, compared with about $100 million several months earlier, which puts Nvidia's price at roughly 80 times forward revenue, something that clearly highlights the strategic nature of the acquisition. Negotiations reportedly began after Hugging Face received acquisition interest elsewhere.CEO and co-founder Clem Delangue said in June that paying subscribers doubled during the first half of 2026 and recently said the company was close to profitability. Demand has benefited from improving Chinese open models from Z.ai, Moonshot, and DeepSeek. If Nvidia proceeds with the takeover, the transaction will be a part of Nvidia's increasingly aggressive investments across the AI ecosystem that spans from hardware to models to software. Last week, Nvidia agreed to pay $6 billion to license development technology from open-model developer Poolside and offered jobs to more than 100 employees. Nvidia also acquired Groq, Enfabrica, Essential AI, Illumex, and Kumo AI, just to name some.