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Investing.com -- Qualcomm (NASDAQ:QCOM) announced Monday it will develop custom data center CPUs designed to link with Nvidia’s AI chips, marking a renewed push into the server processor market.
While Nvidia (NASDAQ:NVDA) dominates the AI accelerator space, its chips require CPUs—traditionally supplied by Intel (NASDAQ:INTC) and AMD (NASDAQ:AMD). Nvidia has also entered the CPU market with its Arm-based "Grace" chip.
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Now, Qualcomm is rejoining the race, leveraging Nvidia technology to improve communication between its CPUs and Nvidia GPUs.
“With the ability to connect our custom processors to Nvidia’s rack-scale architecture, we’re advancing a shared vision of high-performance energy-efficient computing to the data center,” Qualcomm CEO Cristiano Amon said Monday.
Qualcomm initially pursued an Arm-based server chip in the 2010s and tested it with Meta Platforms (NASDAQ:META), but scaled back the effort amid legal pressures and cost cuts. The initiative was revived following Qualcomm’s 2021 acquisition of a team of former Apple (NASDAQ:AAPL) chip engineers.
Since then, the company has resumed discussions with Meta and signed a letter of understanding with Saudi AI firm Humain to co-develop a custom data center CPU.
Qualcomm’s push into data center CPUs gained momentum with its 2021 acquisition of Nuvia, a company that develops Arm-based processor designs and plays a central role in Qualcomm’s renewed server chip ambitions.
The data center CPU space is fiercely competitive, with major cloud providers like Amazon (NASDAQ:AMZN) and Microsoft (NASDAQ:MSFT) already deploying their own custom-built processors, alongside established industry giants AMD and Intel.
Qualcomm’s expansion into this segment is part of a broader effort to reduce its reliance on smartphones, where it has long dominated with processors and modems.
The company is promoting its chips as energy-efficient and capable of running AI workloads directly on devices, rather than offloading them to the cloud. This on-device approach could enable faster AI performance and improved privacy, as sensitive data remains local to the hardware.
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