Amazon Web Services (AWS) and Nvidia have announced a major expansion of their strategic collaboration to meet surging global demand for AI infrastructure as demand continues to accelerate.
Building on already-rapid customer adoption of Nvidia-accelerated compute on AWS, the companies plan to deploy 2-million additional Nvidia GPUs across AWS’s global infrastructure and deepen their work together across AI factories, CPUs, networking, open models, data processing and robotics, delivering co-engineered AI solutions that enable customers to accelerate AI development and deployment.
AI workloads are scaling at a swift pace, from how models are trained and run, to how data is processed, indexed and used to power intelligent applications. Customers are moving from pilot to production and scaling workloads across agentic AI, scientific discovery, enterprise automation and robotics.
They need broader model choice, faster data pipelines and new capabilities for emerging use cases like physical AI. They also need confidence that the underlying infrastructure can keep pace with their own ability to innovate while maintaining the highest level of security and reliability for mission-critical workloads.
To meet this surging demand from frontier labs, global enterprises, startups and governments, AWS and Nvidia are bringing new co-engineered solutions to customers faster.
As part of the expanded collaboration, the companies are working to:
- Deploy 2-million additional Nvidia GPUs across AWS’s global infrastructure in 2027-2028
- Bring Nvidia Vera CPU‑based infrastructure to AWS
- Extend Nvidia NVLink Fusion with custom Nvidia high‑bandwidth memory (NVHBM)
- Build AI factories for the US government, including 100 000 GPUs on secure AWS infrastructure for running federal and national‑security workloads
- Integrate the Nvidia platform with the AWS Nitro System and Elastic Fabric Adapter (EFA) for enhanced security and reliability
- Continue to support Nvidia Nemotron™ open models on Amazon Bedrock and Amazon SageMaker, giving customers more open model choice
- Accelerate data processing and vector indexing on Amazon EMR and Amazon OpenSearch with Nvidia cuDF and cuVS CUDA-X libraries for faster, more cost‑efficient analytics and AI applications
- Further advance robotics workloads through Amazon Robotics’ adoption of Nvidia’s physical AI platform, speeding innovation in warehouse automation and next‑generation robots
“Customers want the freedom to choose the best tools for their AI workloads, and they want confidence that everything works seamlessly together,” says 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, founder and CEO of Nvidia, says: “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.”