Nvidia doubles down on neoclouds with $2B investment in Nebius

Nvidia doubles down on neoclouds with $2B investment in Nebius

NVIDIA and neocloud Nebius announced a strategic partnership to develop next-generation hyperscale AI cloud solutions for AI-native companies and enterprises. 

NVIDIA is set to invest $2 billion into Nebius, which will allow the company to deploy more than 5 gigawatts of NVIDIA systems by 2030.

“AI is at another inflection point – agentic AI, driving incredible compute demand and accelerating infrastructure buildout, ” says Jensen Huang, founder and CEO of NVIDIA. “Nebius is building an AI cloud designed for the agentic era, fully integrated from silicon to software and powered by NVIDIA’s next-generation accelerated compute. Together, we are scaling the cloud to meet the surging global demand for intelligence.”

The collaboration includes joint efforts in AI factory design, inference optimization, AI infrastructure deployment and fleet management.

Nebius will use the latest NVIDIA technologies such as the Rubin platform, Vera CPUs and BlueField storage systems. This further helps to meet the increasing global need of decentralized high performance AI computing and agentic AI.

Nebius’s AI cloud is an infrastructure designed around artificial intelligence applications, incorporating solutions from silicon through software.

NVIDIA’s investment in Nebius signals the acceleration of the neocloud era, where AI-native cloud providers emerge alongside hyperscalers to meet surging demand for GPU-accelerated compute. The partnership reflects a shift toward full-stack, vertically integrated AI infrastructure from silicon to software to cloud and highlights the need for massive new capacity, with plans for 5 GW of NVIDIA-based systems underscoring how power, cooling, and regional deployment are becoming the primary constraints. 

Strategically, this move positions NVIDIA to extend its platform beyond chip sales, enabling a distributed AI cloud model in which hyperscale, regional AI clouds, and edge infrastructure work together to support the growing requirements of inference-heavy and agentic AI workloads.

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