Amazon Web Services (AWS) and NVIDIA today announced a major expansion of their strategic collaboration to meet surging global demand for AI infrastructure. Building on 16 years of joint innovation and 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 work together across AI factories, CPUs, networking, open models, data processing and robotics.
AI workloads are scaling rapidly from model training to data processing for agentic AI, scientific discovery, enterprise automation and robotics. Customers are moving from pilot to production and need broader model choice, faster data pipelines and new capabilities for physical AI while maintaining security and reliability for mission-critical workloads.
AWS offers the widest range of GPU-based instances of any cloud provider. At NVIDIA GTC 2026, AWS announced plans to add more than 1 million NVIDIA GPUs starting in 2026, but demand has exceeded expectations. The additional 2 million NVIDIA Blackwell Ultra, Rubin and Rubin Ultra GPUs planned for 2027-2028 across AWS Global Infrastructure, including AI factories, will power workloads ranging from agentic AI and scientific discovery to enterprise automation and physical AI.
AWS will also expand NVIDIA Blackwell capacity, including NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs for Amazon EC2 G7 instances. G7 instances deliver 4.6x AI inference performance and 2.1x graphics performance compared to previous-generation G6 instances, with AWS as the first major cloud provider to offer RTX PRO 4500. The companies are also collaborating on NVIDIA Spectrum networking to optimize network performance for large-scale AI training workloads.
AWS and NVIDIA are working to bring Vera CPU-based infrastructure to AWS, providing an additional option to support agentic AI workloads that require high-performance CPU compute alongside accelerated infrastructure. Purpose-built for next generation AI, Vera complements AWS's strategy to offer broadest choice of compute.
At re:Invent 2025, AWS announced support for NVIDIA NVLink Fusion high-speed chip interconnect. NVIDIA and Amazon's Annapurna Labs are expanding that support to work on NVIDIA's new custom high-bandwidth memory (NVHBM) technology, which would give Trainium access to faster, more power-efficient memory. Combined with NVLink Fusion, Annapurna Labs can tap NVIDIA's custom memory technology and scale-up architecture within a common rack-scale architecture.
Government agencies need secure AI infrastructure for national security. AWS and NVIDIA plan to build AI factories for the U.S. government, delivering NVIDIA's AI stack including 100,000 GPUs on secure infrastructure for federal workloads classified at Impact Level 6 and above.
"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, optimizing 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."
"NVIDIA and AWS have built one of the great growth engines of the AI era, and demand is running ahead of every forecast," said Jensen Huang, founder and CEO of NVIDIA. "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."
Across the expanded collaboration, all NVIDIA GPU-based and Trainium-based EC2 instances are built on the AWS Nitro System and interconnected through EFA for security and reliability. NVIDIA's Nemotron family of open models is available on Amazon Bedrock as fully managed models and on SageMaker. GPU-accelerated data processing on Amazon EMR using G7 instances and cuDF delivers up to 3.7x faster speeds, while GPU-accelerated vector indexing on OpenSearch delivers up to 9x faster indexing. Amazon Robotics collaborates with NVIDIA to accelerate next-generation robots using Jetson, Omniverse and Isaac platforms for simulation and training.
About Amazon Web Services
Amazon Web Services (AWS) is guided by customer obsession, pace of innovation, commitment to operational excellence, and long-term thinking. By democratizing technology for nearly two decades and making cloud computing and generative AI accessible to organizations of every size and industry, AWS has built one of the fastest-growing enterprise technology businesses in history. Millions of customers trust AWS to accelerate innovation, transform their businesses, and shape the future. With the most comprehensive AI capabilities and global infrastructure footprint, AWS empowers builders to turn big ideas into reality.
About NVIDIA
NVIDIA is the world leader in AI and accelerated computing.
