Nvidia has introduced a new commercial model designed to help AI startups and other emerging technology companies access the high-performance computing infrastructure needed to develop and operate artificial intelligence services.

The initiative will see Nvidia partner with AI cloud providers to deploy large-scale, multi-tenant “AI factories”, with the companies sharing revenue generated by the resulting cloud capacity.

Under the arrangement, cloud providers will procure and operate infrastructure powered by Nvidia technology before selling computing services to AI-native businesses, model developers, enterprises, research organisations and regional technology companies.

Nvidia will receive its standard revenue from the sale of its hardware while also taking a share of the cloud revenue earned from the capacity supported through the programme. The company will additionally provide credit support intended to help cloud operators finance the infrastructure.

Writing on its blog, the chipmaker said the structure is designed to address the financial barriers facing emerging AI companies, which can struggle to secure access to the capital-intensive infrastructure required for training and running AI models.

According to Nvidia, even long-term customer commitments have historically proved insufficient to unlock financing for large-scale computing deployments.

The company said demand is changing as AI moves beyond model development and towards production inference, where deployed systems continuously process requests and generate outputs at scale.

This shift is increasing demand for computing facilities that can come online quickly, maintain high utilisation and support multiple customers and workloads.

First AI Factories Take Shape

Sharon AI and Firmus Technologies are among the first cloud providers working with Nvidia under the new model.

Sharon AI plans to deploy up to 40,000 Nvidia Grace Blackwell GB300 GPUs as part of its computing infrastructure.

“This strategic collaboration with NVIDIA marks a pivotal moment in Sharon AI’s mission to deliver sovereign, large-scale AI compute infrastructure,” said James Manning, cofounder and CEO of Sharon AI.

Firmus, meanwhile, is developing an Nvidia DSX-aligned AI factory campus in Batam, Indonesia. The site is expected to scale to 360 megawatts and support as many as 170,000 Nvidia GPUs.

“AI-native companies need access to scalable, energy- and cost-efficient compute infrastructure to compete globally,” said Tim Rosenfield, co-CEO of Firmus Technologies. “Firmus AI cloud is building a NVIDIA DSX-aligned AI factory, which will enable our cloud to help more customers access the compute they need to build and scale AI.”

Nvidia said the cloud facilities will be designed around customer demand and will serve a variety of users and workloads across different regions.

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The company pointed to AI-native businesses including Baseten, Fireworks AI and Together AI as examples of where computing demand is heading.

Such companies require immediate access to cloud capacity for model training, post-training, fine-tuning and high-volume agentic inference, serving developers, digital-native businesses and larger enterprises building AI applications.

As customer usage increases, these businesses need reliable access to large quantities of accelerated computing power. They also require commercial flexibility while their services move from initial pilots into full production.

The new structure forms part of Nvidia’s broader effort to extend its position across the AI ecosystem, spanning processors, cloud infrastructure and data centres.

By supporting cloud providers and improving access to computing capacity for younger AI companies, Nvidia can expand the use of its technology while building longer-term commercial relationships with businesses whose infrastructure requirements may grow substantially.

Rapid growth in AI development and data-centre spending has been a major driver of Nvidia’s financial performance over the past three years, helping the company become the most valuable business on Wall Street.