Amazon Web Services (AWS) plans to deploy two million additional Nvidia GPUs across its global infrastructure and deepen the two companies’ work across AI factories, CPUs, networking, open models, data processing and robotics.

The expansion complements Amazon’s custom silicon, giving its customers the freedom to choose the best compute for their workloads, whether that’s Nvidia GPUs, AWS Trainium chips or both working together.

AWS and Nvidia have collaborated to bring AI capabilities to users around the world for nearly two decades. In fact, the two companies together launched the world’s first GPU-accelerated cloud instance on AWS, and today AWS offers the widest range of Nvidia GPU products.

Now, as demand for AI accelerates, the two companies are taking that collaboration to a new level. AI workloads are scaling at a rapid pace from how models are trained and deployed, to how data are processed and used to power intelligent applications. Users are moving from pilot to production across agentic AI, scientific discovery, enterprise automation and robotics, and they need infrastructure that can keep pace.

“Customers want the freedom to choose the best tools for their AI workloads, and they want confidence that everything works seamlessly together,” said Matt Garman, CEO of AWS. “That’s why we’ve invested deeply with Nvidia to make AWS the best place to run Nvidia AI technologies, optimising performance across our infrastructure from networking and security to deployment. This expanded collaboration gives frontier labs, enterprises and governments even more ways to build and deploy AI on AWS.”

Jensen Huang, CEO of Nvidia, added: “Nvidia and AWS have built one of the great growth engines of the AI era, and demand is running ahead of every forecast. For 16 years, we have scaled Nvidia computing in the cloud together. Now we are expanding our partnership across the full stack – GPUs, CPUs, networking, open models and software – to make agentic and physical AI real at an unprecedented pace and scale that only AWS and Nvidia can deliver. This expansion reflects customers’ demand for Nvidia’s platform on AWS.”

AWS had announced plans to add more than a million Nvidia GPUs starting this year. Since then, demand has exceeded those expectations. AWS now plans to deploy an additional two million Nvidia GPUs in 2027 and 2028 across its global infrastructure, including AI factories. This capacity will power customer workloads ranging from agentic AI and scientific discovery to enterprise automation and physical AI. Customers are already seeing results from the collaboration, from faster drug discovery to more efficient fraud detection.

AWS and Nvidia are also collaborating on networking technology to connect GPUs more efficiently for large-scale AI training.

Last year, AWS announced support for Nvidia NVLink Fusion high-speed chip interconnect technology in Trainium chips. Amazon’s Annapurna Labs will now work with Nvidia’s new custom high-bandwidth memory technology, which, in partnership with memory suppliers, would give Trainium access to faster, more power-efficient memory.

Government agencies need secure AI infrastructure to keep pace with national security demands. AWS and Nvidia plan to build AI factories for the US government, delivering Nvidia’s AI stack, including 100,000 GPUs, on AWS’s secure infrastructure for federal and national-security workloads.

Learn more about how AWS (aws.amazon.com) and Nvidia (www.nvidia.com) are working together to help users build and deploy AI at aws.amazon.com/nvidia/.