NVIDIA invests $2 billion in Nebius to build the largest AI cloud on the planet
NVIDIA just put $2 billion on the table to accelerate the future of cloud computing focused on artificial intelligence. The chip giant announced on March 11, 2026, a strategic partnership with Nebius, a cloud company that was built from scratch with AI as its sole focus. The goal is as ambitious as the check itself: deploy more than 5 gigawatts of computational capacity by the end of 2030, representing an infrastructure capable of powering entire AI factories at a scale never seen in the market. The collaboration spans from the design of massive data centers to the creation of an optimized stack for inference and agentic AI, covering multiple generations of NVIDIA hardware, including the Rubin platform, Vera CPUs, and BlueField storage systems.
This move signals something important for anyone following the sector: the race for AI infrastructure has gone from being a trend to an urgent necessity, with companies fighting over every watt of available capacity on the planet 🌍. The billion-dollar investment shows that NVIDIA doesn’t just want to manufacture the most powerful chips in the world — it also wants to ensure there is a robust network of partners capable of putting all that computational power into the hands of developers, startups, and large corporations building the next generation of intelligent applications.
What Nebius brings to the table
Nebius may not be as well-known as other cloud providers, but those who know the behind-the-scenes of the market understand that this company has a massive differentiator. Listed on Nasdaq under the ticker NBIS and headquartered in Amsterdam, Nebius is not a generic cloud provider that decided to offer GPUs as an add-on product. The entire architecture of its data centers, the way it handles server cooling, the internal network layout, and even the software layer were all designed from day one to run heavy AI workloads. That means less energy waste, lower latency between compute nodes, and an efficiency that traditional providers would struggle to replicate without rebuilding a significant portion of their infrastructure from the ground up.
In the words of Arkady Volozh, CEO of Nebius, the company was built for AI from day one rather than being adapted from a general-purpose cloud. The pitch is to deliver exactly what developers actually need. With the $2 billion investment from NVIDIA, Nebius gets the financial runway to expand its operations aggressively. The company already operates data centers in strategic locations and is pushing forward with multiple gigawatt-scale AI factories across the United States.
The goal of reaching 5 gigawatts of computational capacity by 2030 is not just a nice number in a press release. To put it in perspective, 5 gigawatts is roughly the amount of energy that powers a mid-sized city, and all of that power will be dedicated exclusively to processing language models, training neural networks, running real-time inference, and operating autonomous AI agents. The scale is genuinely impressive and positions Nebius as one of the leading global players in cloud services specialized for artificial intelligence.
Another key point is that Nebius is not going to simply stack GPUs in racks and hope customers figure out how to use them. The partnership with NVIDIA includes the co-creation of an optimized software stack — an integrated set of tools, libraries, and frameworks that lets developers squeeze maximum performance out of the hardware without needing to become chip architecture experts. This full-stack approach, combining cutting-edge hardware with finely tuned software, is exactly what the market needs to democratize access to high-performance AI computing and lower the barrier to entry for companies of all sizes.
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The four pillars of the collaboration
The official announcement details four joint workstreams that give a good sense of how deep this partnership really goes. This is not a simple chip supply deal. It is an engineering collaboration that touches virtually every layer of cloud computing infrastructure for AI.
AI factory design and support
The first workstream involves AI factory design and support. NVIDIA will share partner design materials, participate in project review and acceptance processes, provide early hardware samples, offer system software support, and assist during the initial operational phase of the data centers. On top of that, there will be periodic technical and business reviews between the two companies. This level of closeness is rare and shows that NVIDIA is treating Nebius as a top-tier strategic partner with privileged access to resources typically reserved for the largest technology companies in the world.
Inference and agentic AI
The second workstream focuses on inference and agentic AI. The two companies will work together to create a reference inference stack using NVIDIA’s latest software technologies, optimized models, and specialized libraries. The goal is to give developers and businesses a platform where running AI models in production is as simple and efficient as possible. This is particularly important in today’s landscape, where most of the computational demand in AI is shifting from training to inference, as more and more applications need to serve real-time responses to millions of users simultaneously.
AI infrastructure deployment
The third workstream covers AI infrastructure deployment itself. Nebius will get early access to multiple generations of NVIDIA compute architectures, including the Rubin platform, Vera CPUs, and BlueField storage systems. This priority access allows Nebius to plan its data centers well in advance, ensuring that each new campus is ready to receive the most advanced hardware on the market as soon as it launches.
Fleet management
The fourth and final workstream is fleet management. NVIDIA will provide its latest GPU health monitoring tools and software recommendations so that Nebius can optimize the holistic performance of its entire installed hardware base. At gigawatt-scale operations, the ability to detect and resolve issues before they affect customers is critical to maintaining the availability and performance levels that the AI market demands.
Next-generation hardware at the heart of the strategy
One of the most interesting details of this partnership is the long-term commitment to multiple generations of NVIDIA hardware. We are not just talking about the current Blackwell GPUs, which are already considered state of the art in artificial intelligence processing. The agreement provides that Nebius will have priority access to the Rubin platform, NVIDIA’s next GPU architecture designed to deliver significant performance leaps in generative AI and complex inference tasks. Additionally, the partnership includes the Vera CPUs, NVIDIA’s new ARM-based processors that promise to redefine energy efficiency in data centers, offering a high-performance alternative for workloads that currently rely on traditional x86 processors.
This multi-generational vision is strategic because data center infrastructure development doesn’t happen overnight. Building a computing campus with gigawatt-scale capacity involves years of planning — from negotiating energy contracts and environmental permits to civil engineering of the buildings and installation of cooling systems. By securing access now to NVIDIA’s most advanced platforms as they roll out, Nebius can design its data centers with the flexibility to receive hardware upgrades without having to overhaul the entire physical infrastructure. That is a huge competitive edge in a market where deployment speed can mean the difference between winning or losing a major enterprise contract.
Jensen Huang and Arkady Volozh on the AI moment
Jensen Huang, founder and CEO of NVIDIA, did not hold back when commenting on the partnership. According to him, AI is at yet another inflection point, with agentic AI driving incredible demand for compute and accelerating infrastructure buildout at a frantic pace. Huang highlighted that 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 computing. Together, the two companies plan to scale the cloud to meet the surging global demand for intelligence.
On the Nebius side, Arkady Volozh reinforced that the company has always been built for AI, and that now, with NVIDIA, that vision extends across the entire technology stack — from gigawatt-scale AI factories to inference and software. The Nebius CEO positioned the company as one of the first and largest clouds dedicated to AI builders worldwide. This statement reveals the company’s ambition to compete directly with the biggest cloud providers on the planet, but with a much sharper focus on the artificial intelligence niche.
Agentic AI as the engine behind this partnership
The emphasis on agentic AI deserves special attention and stands out as a central theme of this collaboration. The term refers to artificial intelligence systems capable of acting autonomously, making decisions, executing complex tasks, and interacting with other systems without constant human intervention. It is the kind of technology behind advanced digital assistants, enterprise process automation, and even robots operating in industrial environments.
For these agents to truly work at scale, they need a cloud that offers not just raw processing power but also ultra-low latency and high availability. Unlike model training, which can tolerate some variation in response time, real-time inference for autonomous agents requires every request to be processed in milliseconds. An AI agent that takes too long to respond or goes down simply does not work for business-critical applications. That is exactly what the NVIDIA and Nebius partnership aims to deliver — creating a platform where real-time inference for AI agents becomes viable and cost-effective for any company that needs that capability 🤖.
What this means for the cloud and AI market
The partnership between NVIDIA and Nebius is not happening in a vacuum. It is another piece on a board that is being rearranged rapidly. Over the past two years, we have seen massive investments from companies like Microsoft, Google, Amazon, and Oracle to expand their AI-focused cloud capabilities. Demand for high-performance GPUs has far outpaced available supply, creating wait times that in some cases stretched to months. With this deal, NVIDIA diversifies its network of infrastructure partners and ensures that the computational capacity needed to sustain the explosive growth of AI does not remain concentrated solely in the hands of the traditional big tech players. That is good for the ecosystem as a whole, because more competition in the cloud market tends to drive prices down and improve service quality for end customers 🚀.
For startups and mid-sized companies developing artificial intelligence solutions, the arrival of specialized providers like Nebius — now supercharged by NVIDIA’s investment — represents a real opportunity. Many of these companies face difficulties securing GPU allocations from mainstream providers, whether due to high prices, restrictive minimum contracts, or simply a lack of inventory. A cloud provider that was built from scratch for AI can offer more flexible plans, better technical support for specific workloads, and most importantly, a performance-per-dollar ratio that makes sense for those trying to train or serve models without burning through their company’s cash reserves.
Sustainability and energy consumption at gigawatt scale
Looking at the bigger picture, the 5-gigawatt target by 2030 also raises important questions about sustainability and energy consumption. The data center industry already accounts for a significant share of global electricity usage, and the explosion of artificial intelligence is accelerating that demand exponentially. NVIDIA has been investing heavily in energy efficiency across its new architectures, and Nebius states that its data centers are designed with advanced cooling technologies and a focus on consumption optimization.
Still, the proposed scale is so massive that the industry will need to keep innovating to ensure the growth of AI does not come with an unsustainable environmental footprint. This is a challenge shared by the entire industry and one that will require creative solutions in the coming years. The adoption of more efficient processors like the Vera CPUs and architectures optimized for inference — which consume less energy per operation than model training — are steps in the right direction. But the global energy bill for AI is something governments, companies, and society at large will need to keep a close eye on.
A new chapter in the race for AI infrastructure
The partnership between NVIDIA and Nebius marks a new chapter in how artificial intelligence infrastructure is being built around the world. By investing $2 billion in a company focused exclusively on cloud for AI and by sharing priority access to its most advanced hardware platforms, NVIDIA is betting that the future of cloud computing will become increasingly specialized. Instead of generic data centers trying to handle every type of workload, the trend points toward facilities designed from the foundation up to maximize performance for artificial intelligence applications.
For developers and companies that rely on AI computing, this kind of partnership is encouraging news. More capacity, more competition, and more innovation at the infrastructure layer mean that access to high-performance GPUs should become progressively easier and more affordable in the years ahead. And with agentic AI gaining traction as the next big wave of applications, having a cloud optimized for that type of workload can make all the difference between a good idea and a product that actually works in production.
