Qualcomm and Amazon Partner

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Qualcomm shares surged in premarket and regular trading after the company announced a data center infrastructure partnership with Amazon Web Services on Tuesday.

Qualcomm and AWS Partner on Custom Silicon for AI Inference

According to corporate press materials, Qualcomm will work with Amazon across multiple generations of customized silicon to help build out AWS’ AI infrastructure. The collaboration specifically targets inference workloads, combining Amazon’s comprehensive, secure, and price-performant AI infrastructure with Qualcomm Technologies’ leadership in power-efficient processing, silicon design and system-level integration.

“As AI workloads grow exponentially — driving unprecedented demand for compute, storage, networking and memory bandwidth, and energy-efficient infrastructure — the collaboration brings together Amazon’s comprehensive, secure, and price-performant AI infrastructure with Qualcomm Technologies’ leadership in power-efficient processing, silicon design and system-level integration,” the statement said.

Building Out the Dragonfly C1000 and Data Center Roadmap

Qualcomm is known for making processors that power smartphones and other mobile devices. But the company made a big splash in June, when it revealed a central processing unit for data centers called Dragonfly C1000, and said that Meta would use it when it starts production in 2028. The chipmaker said the new CPU was built for agentic AI and focuses on offering computing performance without using too much power.

Qualcomm said at the time that it’s targeting $15 billion in data center sales in fiscal 2029, and pointed to a roadmap for going after the market with several different products, including an AI chip and a product that will tie multiple chips together. Securing Amazon Web Services as a second major hyperscaler customer provides a substantial validation of that roadmap. Like Meta, Amazon’s annual capital expenditures on AI infrastructure is reaching into the hundreds of billions of dollars.

Amazon Expands Its Semiconductor Ambitions

Amazon CEO Andy Jassy first raised the prospect of selling chip racks to outside customers in his April 2026 shareholder letter, putting the company’s annualized chip revenue at roughly $20 billion across its Trainium, Graviton, and Nitro product lines and suggesting that selling to external customers could push that figure toward $50 billion annually. Amazon’s senior vice president overseeing semiconductor, AI, and quantum efforts, Peter DeSantis, has separately confirmed that Amazon is in talks to sell its Trainium AI chips — previously available only through AWS — to other companies’ data centers. We view AI infrastructure as rapidly evolving, DeSantis said. And we're constantly looking at ways to get to more customers. DeSantis positioned Amazon as a direct peer to Nvidia in chip development, saying the company is one of a very few players who have the ability to design a chip, design the physical attributes of that chip, and then do the production of that chip.

The Shift Toward Central Processing Units in AI Workloads

Nvidia has emerged as the world’s most valuable company by dominating the market for graphics processing units (GPUs), which are needed for building sophisticated AI models and running the heftiest workloads. While GPUs are ideal for training and running 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. However, more chipmakers are getting involved in the AI boom now that the CPU is proving key for AI.

Bank of America predicts the CPU market could more than double, from $27 billion in 2025 to $60 billion by 2030. Intel and Advanced Micro Devices are both seeing surging demand for their data center CPUs, and Nvidia in March offered new details about its agentic-optimized CPUs. Dion Harris, Nvidia’s head of AI infrastructure, told CNBC at the time that, CPUs are becoming the bottleneck in terms of growing out this AI and agentic workflow.