Built for Vera Rubin, NVIDIA Spectrum-6 Arrives in Gigascale AI Factories

AI has entered the gigascale era.

The world’s most advanced AI factories are bringing together hundreds of thousands of GPUs and CPUs to train frontier models, power agentic AI and generate intelligence at unprecedented scale. At this level, networking becomes a critical computing power multiplier in driving token generation.

Marking a networking milestone, NVIDIA Spectrum-6 — a 102.4-terabit-per-second Ethernet switch system delivering 2x the capacity of previous-generation systems and built as part of the NVIDIA Vera Rubin platform — is arriving across the world’s gigascale AI factories.

Spectrum-6 anchors the next generation of the NVIDIA Spectrum-X Ethernet platform, delivering the bandwidth, scale and intelligence needed to operate an AI factory as one end-to-end computing system.

Leading AI Builders Move First

The world’s leading AI infrastructure builders — including CoreWeave, Microsoft, Nebius, SpaceXAI and Tesla — will be among the first to bring in Spectrum-6 to accelerate their AI factories.

For cloud providers, Spectrum-6 means more compute capacity can operate as a unified, high-performance resource, helping customers train models and deploy inference services faster.

“CoreWeave is built for the most demanding AI workloads, and networking is central to delivering that performance at scale,” said Min Jun, director of product for networking at CoreWeave. “Bringing NVIDIA Spectrum-6 and liquid-cooled Spectrum-X Ethernet infrastructure into our AI factories will help us deliver the bandwidth, resilience and efficiency customers need to train frontier models and deploy inference faster.”

“At gigascale, performance comes down to coordination: keeping every GPU in lockstep so one slow link doesn’t stall an entire job,” said Laurelle Roseman, vice president of global partnerships at Nebius. “That’s what NVIDIA Spectrum-6 goes after, and why we brought it in early — a fabric that stays fast and resilient as our customers’ most demanding workloads scale…