Companies Deepen Integration Across the AI Stack, Bringing NVIDIA Vera CPUs, Advanced Networking, Nemotron Open Models and Physical AI Technologies to AWS as Customer Demand Accelerates<\/p>\n
Amazon Web Services (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), and NVIDIA (NASDAQ: NVDA) today 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\u2019s 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 at unprecedented scale.<\/p>\n
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.<\/p>\n
To meet this surging demand from frontier labs, global enterprises, startups and governments, AWS and NVIDIA are building on 16 years of joint innovation to expand AI compute capacity and bring new co-engineered solutions to customers faster. As part of the expanded collaboration, the companies are working to:<\/p>\n
\n\tDeploy 2 million additional NVIDIA GPUs across AWS\u2019s global infrastructure in 2027-2028
\n\tBring NVIDIA Vera CPU\u2011based infrastructure to AWS
\n\tExtend NVIDIA NVLink Fusion\u2122 with custom NVIDIA high\u2011bandwidth memory (NVHBM)
\n\tBuild AI factories for the U.S. government, including 100,000 GPUs on secure AWS infrastructure for running federal and national\u2011security workloads
\n\tIntegrate the NVIDIA platform with the AWS Nitro System and Elastic Fabric Adapter (EFA) for enhanced security and reliability
\n\tContinue to support NVIDIA Nemotron\u2122 open models on Amazon Bedrock and Amazon SageMaker, giving customers more open model choice
\n\tAccelerate data processing and vector indexing on Amazon EMR and Amazon OpenSearch with NVIDIA cuDF and cuVS CUDA-X\u2122 libraries for faster, more cost\u2011efficient analytics and AI applications
\n\tFurther advance robotics workloads through Amazon Robotics\u2019 adoption of NVIDIA\u2019s physical AI platform, speeding innovation in warehouse automation and next\u2011generation robots
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\u201cCustomers want the freedom to choose the best tools for their AI workloads, and they want confidence that everything works seamlessly together,\u201d said Matt Garman, CEO of AWS. \u201cThat\u2019s why we\u2019ve 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.\u201d<\/p>\n
\u201cNVIDIA and AWS have built one of the great growth engines of the AI era, and demand is running ahead of every forecast,\u201d said Jensen Huang, founder and CEO of NVIDIA. \u201cFor 16 years, we have scaled NVIDIA computing in the cloud together. Now, we are expanding our partnership across the full stack \u2014 GPUs, CPUs, networking, open models and software \u2014 to make agentic and physical AI real at an unprecedented pace and scale that only AWS and NVIDIA can deliver. This expansion reflects customers\u2019 demand for NVIDIA\u2019s platform on AWS.\u201d<\/p>\n
Massive Expansion of AI Compute Capacity Support for NVIDIA Vera CPUs on AWS
\nAWS offers the widest range of GPU-based instances of any cloud provider to power a diverse set of AI and machine learning workloads. At NVIDIA GTC 2026, AWS\u00a0announced plans<\/a> to add more than 1 million NVIDIA GPUs starting in 2026. Since then, demand has exceeded those expectations. AWS plans to deploy an additional 2 million NVIDIA Blackwell Ultra, Rubin and Rubin Ultra GPUs in 2027-2028 across AWS Global Infrastructure, including AI factories. This additional capacity will help power customer workloads ranging from agentic AI and scientific discovery to enterprise automation and physical AI. In addition, AWS will expand NVIDIA Blackwell capacity, including NVIDIA RTX PRO\u2122 4500 Blackwell Server Edition GPUs for\u00a0Amazon EC2 G7 instances<\/a>. G7 instances deliver 4.6x AI inference performance and 2.1x graphics performance compared to previous-generation G6 instances. AWS is the first major cloud provider to offer compute instances accelerated by RTX PRO 4500. AWS and NVIDIA are also collaborating on NVIDIA Spectrum\u2122 networking to further optimize network performance for large-scale AI training workloads across GPU clusters.<\/p>\n
\nAWS 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 the next generation of AI, Vera complements AWS\u2019s strategy to offer the broadest choice of compute \u2014 from AWS custom silicon to the latest accelerators and CPUs from partners.<\/p>\n