Superpower Daily
Deep Cogito Raises $43M to Build AI Models Enterprises Can OwnAWS Plans 2 Million Nvidia GPUs for 2027–28 and Federal AI Fact...OpenAI Details Agent Breach of Hugging Face, Halts Research Mod...Chronograph Connects Perplexity to Private-Capital Data, Adding...Lam Breaks Ground on Oregon Lab, First Step in $3B AI-Chip R&D...States Halt or Tighten AI Data Center Growth as a Cross-Partisa...Deep Cogito Raises $43M to Build AI Models Enterprises Can OwnAWS Plans 2 Million Nvidia GPUs for 2027–28 and Federal AI Fact...OpenAI Details Agent Breach of Hugging Face, Halts Research Mod...Chronograph Connects Perplexity to Private-Capital Data, Adding...Lam Breaks Ground on Oregon Lab, First Step in $3B AI-Chip R&D...States Halt or Tighten AI Data Center Growth as a Cross-Partisa...
Businesspublished

AWS Plans 2 Million Nvidia GPUs for 2027–28 and Federal AI Factories

The partnership reaches beyond GPU supply into CPUs, networking and AWS’s own Trainium chips. The largest capacity commitment remains a future deployment, making execution on the shared infrastructure the central test.

By 3 min read
AWS Plans 2 Million Nvidia GPUs for 2027–28 and Federal AI Factories
Sign in to save and react

Listen to this story

The audio brief

About 1:45
0:001:45
Read transcript
AWS is planning to deploy two million additional Nvidia GPUs across its global infrastructure in 2027 and 2028, alongside a separate, secure buildout of 100,000 GPUs for U.S. government workloads. The headline is future capacity, but the deeper move is architectural: AWS wants Nvidia GPUs and its own Trainium accelerators working together in the same rack-scale systems, rather than forcing customers to choose between them. AWS says next-generation Trainium chips will support Nvidia’s NVLink Fusion, a high-speed connection for linking processors, while Annapurna Labs is working with Nvidia on high-bandwidth-memory technology. The companies are targeting agentic AI, scientific discovery, enterprise automation, and physical AI. They’re also developing Nvidia Vera CPU systems for AWS, aimed at tasks such as code execution, tool use, sandboxing, analytics, data pipelines, and orchestrating AI agents. This follows an earlier AWS pledge to add more than one million Nvidia GPUs starting in 2026. The company says demand exceeded expectations, leading to the additional two-million-GPU commitment. But none of this new capacity is available yet. The federal figure refers to planned Impact Level 6-and-above infrastructure, not rentable capacity today. Customers can already access Nvidia Nemotron models through Amazon Bedrock and Amazon SageMaker, along with Nvidia GPU and Trainium-based EC2 instances using the AWS Nitro System and Elastic Fabric Adapter networking. The key question is whether AWS can deliver these planned systems as one integrated service, at the promised scale, across 2027 and 2028.

Story brief

3 key points

AWS is turning its Nvidia relationship into a multi-year capacity and systems bet: after an earlier plan for more than 1 million GPUs from 2026, it now targets 2 million additional Nvidia GPUs in 2027–28 and a 100,000-GPU secure buildout for U.S. federal workloads. The architecture is meant to combine Nvidia GPUs with future Trainium chips via NVLink Fusion, rather than choose one accelerator. None of the new...

  1. 01

    The 100,000-GPU federal figure covers planned Impact Level 6-and-above infrastructure, not currently rentable capacity.

  2. 02

    Next-generation AWS Trainium is expected to support Nvidia NVLink Fusion; Annapurna Labs is working on Nvidia HBM technology.

  3. 03

    Nvidia Vera CPU systems are being developed for code execution, tool use, sandboxing, analytics, pipelines, and agent orchestration on AWS.

AWS plans to deploy 2 million additional Nvidia GPUs across its global infrastructure in 2027 and 2028 and plans U.S. government AI factories with 100,000 GPUs on secure AWS infrastructure. The commitment pairs a large future capacity target with a deeper effort to join Nvidia hardware to AWS’s own AI chips and cloud systems.

A shared rack, not a single-chip strategy

The technical center of the deal is an effort to make AWS’s Trainium accelerators work more closely with Nvidia technology. AWS says next-generation Trainium chips will support Nvidia NVLink Fusion, a high-speed chip interconnect, while Amazon’s Annapurna Labs works with Nvidia’s custom high-bandwidth-memory technology. The intended architecture would integrate Trainium and GPUs in a common rack-scale design.

The companies are not presenting Nvidia GPUs and Trainium as mutually exclusive choices. AWS says the expanded capacity is intended for agentic AI, scientific discovery, enterprise automation and physical AI. For agentic systems, AWS and Nvidia are also working to bring Vera CPU-based infrastructure to AWS for code execution, tool use, sandboxing, analytics, data pipelines and orchestration.

A larger target after an earlier pledge

AWS had already said at Nvidia GTC 2026 that it would add more than 1 million Nvidia GPUs starting in 2026. It now says demand exceeded those expectations and has set out the additional 2 million-GPU plan for the following two years. The announcement is therefore a forward deployment commitment rather than capacity customers can assume is available now.

What customers can use now

  • Nvidia’s Nemotron family of open models is available through Amazon Bedrock and Amazon SageMaker.
  • AWS says Nvidia GPU-based and Trainium-based EC2 instances are built on the AWS Nitro System and connected through Elastic Fabric Adapter networking.

A secure route for federal workloads

The government portion gives the partnership a distinct planned deployment path. AWS and Nvidia plan to provide Nvidia’s AI stack through secure AWS infrastructure for federal and national-security workloads classified at Impact Level 6 and above. The 100,000-GPU figure describes the planned federal buildout, not capacity available today.

For AWS, the near-term evidence is existing software and instance integrations; the central test is execution on the planned infrastructure. Vera-based AWS systems remain under development, the federal AI factories are planned, and the 2 million additional GPUs are scheduled across 2027 and 2028. The partnership’s business effect will depend on those components arriving as an integrated service at the promised scale.

Editorial analysis

Our Read

Our read: The strategic signal is not simply that AWS wants more Nvidia chips. AWS is also preserving a role for Trainium by connecting it to Nvidia’s NVLink Fusion and memory work, while adding Vera CPUs for CPU-heavy parts of agent systems. That makes this a broader interoperability bet than a conventional cloud-capacity reservation. The next evidence to watch is product availability and deployment milestones: the 2 million-GPU commitment is scheduled for 2027–2028, while the practical question is whether Nvidia GPUs and Trainium arrive as a workable shared rack-scale option.

Related coverageNvidia Posts $96.22B Revenue and $108B Outlook as AI Chip Spending Holds Up

Sources

  1. aboutamazon.comAWS and NVIDIA expand partnership for next-gen AI infrastructure

Related coverage

Continue reading