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This landmark $38 billion deal between AWS and OpenAI aims to supercharge AI innovation with unparalleled access to cutting-edge computing resources, driving advancements in generative models and beyond.
AWS and OpenAI have announced a multi-year strategic partnership that will see OpenAI leveraging AWS’s world-class infrastructure to run and scale its advanced AI workloads. This $38 billion deal, which will grow over the next seven years, marks a significant step in providing OpenAI with the compute power needed to push the boundaries of generative AI.
The rapid advancement of AI technology has created an unprecedented demand for computing power. As companies like OpenAI continue to develop more sophisticated models, they need robust and scalable infrastructure to support these efforts. AWS’s leadership in cloud infrastructure, combined with OpenAI's expertise in generative AI, is a powerful combination that will benefit millions of users.

This partnership will help millions of users continue to benefit from advanced AI applications like ChatGPT. By providing OpenAI with the necessary compute resources, AWS is enabling faster model training and more efficient inference, which translates into better performance and new features for end-users.
“Scaling frontier AI requires massive, reliable compute," said Sam Altman, co-founder and CEO of OpenAI. “Our partnership with AWS strengthens the broad compute ecosystem that will power this next era and bring advanced AI to everyone.”
“As OpenAI continues to push the boundaries of what's possible, AWS’s best-in-class infrastructure is essential in supporting their mission,” added an AWS spokesperson.
This strategic partnership between AWS and OpenAI is a significant milestone in the AI landscape. By combining AWS’s world-class infrastructure with OpenAI’s cutting-edge research, both companies are well-positioned to drive innovation and deliver advanced AI solutions to users worldwide.
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About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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4 November 2025
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