Snowflake soars 33% on earnings beat, will spend $6B on Amazon cloud

Amazon said Wednesday that its cloud division has landed a $6 billion spending commitment from Snowflake, which includes the use of the company’s custom silicon and chips for artificial intelligence.

Snowflake’s purchase of services and technology from Amazon Web Services will occur over five years, according to a press release about the agreement. Snowflake intends to expand its use of Amazon’s Graviton general-purpose chips, as well as cloud-based graphics processing units for AI.

It’s the latest sign that AWS is gaining momentum in AI as clients turn to the market-leading cloud for more advanced technologies. In April, Claude creator Anthropic said it aims to spend over $100 billion on AWS over a decade. Amazon also has a deal with OpenAI.

Both of its agreements with the AI model companies include an equity investment, while the Snowflake deal does not. Snowflake, which went public in 2020, has a market cap of just over $60 billion, and has long relied on AWS.

Snowflake rose as much as 33% in extended trading after it announced strong results for its fiscal first quarter, which ended on April 30. The company reported 39 cents in adjusted earnings per share on $1.39 billion in revenue, up 33% year over year. Analysts polled by LSEG had expected 32 cents per share and $1.32 billion in revenue.

Guidance was also strong, as Snowflake called for a 12.5% fiscal second-quarter adjusted operating margin on $1.415 billion to $1.420 billion in product revenue. Analysts surveyed by StreetAccount had been looking for a 11.9% margin, with $1.37 billion in product revenue.

Snowflake also said it was acquiring AI startup Natoma for an undisclosed sum.

At the time of Snowflake’s IPO, it disclosed an amended deal with an unnamed cloud provider for $1.2 billion in spending over five years, with $350 million coming in the final year. The provider was Amazon, a Snowflake spokesperson told CNBC. In 2023, the agreement climbed to $2.5 billion.

The new $6 billion arrangement implies an average annual spend of $1.2 billion.

AWS announced its first Arm-based Graviton chip in 2018, and it remains the company’s most successful custom chip to date. Snowflake first talked about adopting Graviton in 2022.

Snowflake also has close ties to Nvidia, following a partnership announced in 2023. In November, Snowflake touted updates to simplify the process of running AI workloads on Nvidia GPUs.

The deal marks yet another large tech company choosing custom Arm-based processors over those based on traditional x86 architecture.

For decades, server chips have been built on the x86 instruction sets pioneered by Intel in the 1970s and Advanced Micro Devices a couple of decades later. Arm’s alternative power-efficient architecture went mainstream when Apple adopted it for the first iPhone in 2007. But it was Amazon that brought Arm chips into data centers with Graviton. Cloud rivals Google and Microsoft followed Amazon in bringing out custom Arm chips.

Fast-forward to 2026, and central processing units like Graviton are seeing a renewed flurry of demand as mass AI adoption shifts from call-and-answer chatbots to task-oriented agentic apps.

While GPUs like Nvidia‘s excel at training AI models because they have thousands of tiny cores narrowly focused on performing many operations simultaneously, CPUs have a smaller number of powerful cores running sequential general-purpose tasks. Agentic AI requires a lot of general compute power to move large amounts of data around for AI workflows, orchestrating across multiple agents.

In April, Meta said it would draw on hundreds of thousands of Graviton chips.

“Graviton is our industry-leading CPU chip, which allows Meta to run the CPU-intensive workloads behind Agentic AI with the performance and efficiency they need at their scale,” Amazon CEO Andy Jassy said on the company’s April earnings call.

WATCH: How Amazon chips are powering Anthropic without Nvidia