Snowflake is committing $6 billion over five years to Amazon Web Services for Graviton compute and AI infrastructure, the data company’s largest cloud spend commitment to date and a clear sign of its ambitions in the AI space.
This multi-year strategic collaboration agreement, announced by AWS on Wednesday, covers AWS’s ARM-based Graviton processors and GPU-accelerated EC2 instances, which Snowflake will use for AI model training and inference.
Interestingly, there’s no mention of AWS’s specialized Trainium chips here (though there are accelerated EC2 instances with Trainium chips attached). Since AWS’s announcement specifically refers to “GPU-accelerated” instances, the focus here is likely on Nvidia GPUs.
Given that Snowflake supports a variety of cloud vendors, the company likely doesn’t want to lock itself into a vendor-specific platform (and commit engineering resources to support it). For ARM-based general compute instances, this is far less of a worry at this point.
The deal also expands the two companies’ joint go-to-market through AWS Marketplace, where AWS says Snowflake has now surpassed $7 billion in lifetime sales.
A $6 billion commitment is notable on its own (that’s 6 Instagrams, after all), but what’s maybe just as interesting here is that Snowflake will use AWS’s cost-efficient Graviton instances to help power Snowflake’s traditional data warehousing business — and maybe free up financial resources for the far more expensive AI training and inferencing workload.
Under CEO Sridhar Ramaswamy, who succeeded Frank Slootman in 2024, Snowflake has been repositioning from a cloud data warehouse into what the company now calls “the platform for the AI era.”
Cortex AI, Snowflake’s suite of AI products, lets customers build and deploy applications for text-to-SQL, summarization, sentiment analysis, and entity extraction directly on governed data inside Snowflake. With Cortex Code, Snowflake also offers an AI coding agent.
“We are moving into the era of the agentic enterprise, where AI systems don’t just answer questions, but help organizations reason over trusted data, coordinate workflows, and drive real business outcomes,” Ramaswamy says in the announcement. “With AWS, we are making it easier for enterprises to bring AI directly to governed data.”
Snowflake is also expanding its AWS footprint to 10 new regions, including New Zealand, South Africa, Thailand, and the AWS European Sovereign Cloud. The sovereign cloud piece here is especially important, given that enterprises are increasingly dealing with localized data residency requirements (especially in Europe). Support for these is becoming a prerequisite for many companies when choosing a vendor — and not just for AI workloads.
It’s worth noting that Snowflake’s annual Summit conference is happening June 1-4 in San Francisco. It doesn’t take a crystal ball to predict that we will hear more about the company’s AI focus — and how it plans to use all of these compute resources — there.
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