March 20, 2026

Nvidia builds networking giant to rival chips

nvidia builds networking giant to rival chips2
Photo source: The New York Times

Nvidia is quietly forging a multibillion-pound networking empire to rival AI chips.

Jensen Huang saw it coming early. In 2010 he pushed Nvidia into AI hardware. The 2020 $7 billion Mellanox buy then turbocharged data centre networking into a revenue beast.

Latest fiscal 2026 figures show £11 billion quarterly—up 267 per cent—totalling £31 billion yearly. It tops Cisco’s full networking in one quarter alone.

Powering “AI factories” are NVLink interconnects, InfiniBand Switches, Spectrum-X Ethernet, and co-packaged optics. They bind GPUs in hyperscale setups for Microsoft and Google.

Despite this, the unit trails GPU hype and legacy gaming in the spotlight.

Kevin Cook of Zacks told TechCrunch “[Nvidia’s networking business] reports $11 billion for the quarter; that number is greater than Cisco’s networking business, almost as big as the full-year estimates.” It matches Cisco’s annual in three months.

nvidia builds networking giant to rival chips
Photo source: CNBC

Kevin Deierling, networking SVP from Mellanox, debunks myths. “People think of networking as just, ‘I got a printer, and I need to connect to it,’” Deierling said. “Jensen said this the first day when he acquired us, he said the data centre is the new unit of computing. Networking is a lot more than just moving the smaller amounts of data between a compute node; it’s actually a foundation.”

“When Jensen bought Mellanox in 2020, he saw that was the missing piece to make GPUs a complete package,” Cook said.

Nvidia offers full stacks via partners. “I can’t think of other companies that have [the] full-stack capabilities that we have,” Deierling said. “We are really different. We build the full compute stack, fully integrated stack, and then we go to market through all of our partners.”

GTC unveiled Rubin chips and Spectrum-X upgrades. “It’s no longer a peripheral to connect the printer, some other slow I/O device,” Deierling said. “It’s fundamental to the computer. Today, the network is the back lining of the AI factory, and it’s super important.”

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