Amazon Web Services (AWS) revenue growth reached 28% year over year during Amazon’s fiscal Q1.
That was the segment’s fastest growth rate in 15 quarters — almost four years. It also represented $2 billion quarter-over-quarter growth. AWS has reached a $150 billion annualized revenue run rate, Amazon CEO Jassy said on the merchant’s Q1 earnings call with investors.
In its fiscal Q1 2026, Amazon reported $181.5 billion in revenue, or 17% year-over-year growth. Its operating income reached $23.9 billon. AWS accounted for $37.6 billion of that total Amazon revenue in Q1. That’s just over 20% of Amazon sales in Q1.
“It’s very unusual for a business to grow this fast on a base this large,” Jassy said. “And the last time we saw growth at this clip, AWS was roughly half the size. We’ve never seen a technology grow as rapidly as AI.”
Since Amazon’s last quarterly call, Jassy said, the company has announced new agreements with OpenAI, Anthropic, Meta, Nvidia and more.
Jassy also noted that Amazon and Nvidia will be “partners for as long as I can foresee” and that Amazon has “immense respect for them.”
Amazon ranks No. 1 in Digital Commerce 360’s Top 2000 Database. The database is how Digital Commerce 360 tracks the largest North American online retailers by their annual ecommerce sales.
Amazon is also No. 3 in Digital Commerce 360’s Global Online Marketplaces Database. That database ranks the 100 largest such marketplaces by third-party gross merchandise value (GMV).
AWS growth boosts overall Amazon revenue in Q1
AWS launched in 2002, and its cloud computing capabilities launched in 2006. Three years after AWS launched, it has a $58 million run rate, Jassy said. Now, in the first three years of what Jassy called an “AI wave,” AWS’ AI revenue run rate is more than $15 billion.
Amazon SageMaker, a service within AWS, allows developers to build, train and deploy machine-learning models. Meanwhile, Amazon Bedrock is an AWS service that provides application programming interface (API) access to models from AI companies, including Anthropic. Amazon client spending on Bedrock increased 170% quarter over quarter in Q1. Bedrock processed more tokens in Q1 than all prior years combined.
Jassy said Amazon has made OpenAI models available within Bedrock. It added OpenAI’s GPT-5.4 on April 28, Jassy said. He added that the 5.5 model is “coming soon.”
Also on April 28, Amazon started the preview of Bedrock-manage agents that OpenAI powers. Jassy referred to it as the Stateful Runtime Environment. Stateful refers to systems and applications that retain data and context or “remember” previous interactions and data.
He said it “enables any organization to build generative AI applications and agents at production scale. We believe that modern agentic applications will be stateful, and this new technology will rapidly accelerate agentic AI adoption.”
Jassy went on to say that “most of the value companies derive from AI will be through agents.”
Amazon Trainium and Graviton AI-processing chips
Jassy said Amazon’s computer chips business “continues to grow rapidly.”
It saw nearly 40% quarter-over-quarter growth in Q1, he said. Amazon’s chips business now has an annual revenue run rate of more than $20 billion with triple-digit percentage growth year over year, he added.
“For our custom AI silicon, we’ve recently shared very large multiyear, multi-gigawatt Trainium commitments from the two leading AI labs in the world in Anthropic and OpenAI as well as an increasing number of companies like Uber betting on Trainium,” Jassy said.
Amazon now has more than $225 billion in revenue commitments for Trainium, Jassy noted. It began shipping its Trainium 3 chip at the start of 2026. Jassy said Trainium 4 is about 18 months from broad availability and has already been reserved.
Amazon Bedrock “runs most of its inference on Trainium and almost 80% of the Fortune 100 companies are using Bedrock,” Jassy said.
Additionally, Amazon announced that Meta has committed to using tens of millions of Graviton cores. Graviton refers to Amazon’s CPU chip. Jassy said it will allow Meta “to run the CPU-intensive workloads behind agentic AI with the performance and efficiency they need at their scale.”
“AI is commonly seen as a GPU story,” Jassy said. “But the rise of agentic workloads, real-time reasoning, code generation, reinforcement learning and multistep task orchestration is driving massive CPU demand as well. As AI systems shift from answering questions to taking actions and as post-training and inference scale up, the compute required pulls heavily on CPUs.”
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