Nvidia Deepens Grip on Cloud AI With Major AWS Chip Deal

Nvidia will supply Amazon Web Services with a massive volume of GPUs through 2027 as the cloud provider ramps up its AI infrastructure and looks to meet growing demand.

AWS announced earlier this week that it plans to deploy around 1 million Nvidia GPUs as part of its expanded AI infrastructure buildout. An Nvidia executive confirmed with Reuters on Thursday that the rollout is expected to run through the end of 2027.

Commencing this year across AWS’s global cloud regions, it will be rolled out alongside expanded work with Nvidia on networking and other infrastructure to build systems “capable of reasoning, planning, and acting autonomously across complex workflows,” AWS said, pointing to its work on agentic AI systems.

AWS continues to develop AI chips for both training and inference. The collaboration suggests demand may be shifting across the AI stack, while a growing share of activity appears tied to running models in live services.

The deal comes as U.S. prosecutors pursue a case alleging Nvidia chips were smuggled to China, placing the company’s global supply and controls under renewed scrutiny.

Since 2022, Nvidia’s most advanced chips have been tightly controlled as part of a broader U.S. strategy to limit China’s progress in advanced computing and AI. 

Thursday’s development closer to home could all but widen that gap.

Changes in pace

Observers say the deal structure offers clues about where demand is building and how the underlying infrastructure is changing at an increasingly rapid pace.

“Nvidia is becoming the infrastructure layer underneath the cloud providers, not just a chip vendor to them,”  Dermot McGrath, co-founder at strategy and growth studio ZenGen Labs, told Decrypt.

Chips in the deal are geared toward running AI models at scale, with a focus on lowering the cost of use, McGrath said, noting that inference now accounts for roughly two-thirds of AI compute, up from about a third in 2023.

The market for inference-focused chips is expected to exceed $50 billion by 2026, he added, citing Deloitte estimates.

AWS can use both Nvidia and its own chips in the same systems, giving customers more choice than rivals that keep theirs closed, McGrath explained, adding that this flexibility “is a differentiator.”

“Now Nvidia is doing the same thing one layer down, with networking and rack architecture instead of a programming model,” he said.

Inference chips are processors designed to run trained AI models in real time, rather than requiring retraining.

Demand for inference is “driving long-term commitments” for more compute power, and is creating closer ties between cloud providers and chipmakers, Pichapen Prateepavanich, policy strategist and founder of infrastructure firm Gather Beyond, told Decrypt.

“Cloud providers want independence over the long term, but in the near term they need Nvidia to remain competitive,” she said, noting how this creates a dynamic where cooperation and competition happen at the same time.

Still, control over AI infrastructure is also changing.

What’s happening is an “infrastructure flip,” Berna Misa, deal partner at Boardy Ventures, an AI-led investment fund, told Decrypt.

Nvidia is “embedding its full stack across compute, networking, and inference inside AWS data centers that ran proprietary gear for years,” she said.

But while AWS is developing its own AI chips, this “doesn’t change the math,” she explained, noting that inference relies on multiple components across the stack, with Nvidia supplying most of them.

“When you’re that deep in your customer’s stack, switching cost and the context layer that comes out of it becomes the moat,” she said.