Demand is so high coming from so many directions. Whatever is built is consumed and demand is totally objective. Everybody sees how much new value this thing generates. You can do either 10 times more things or 10 times cheaper and it's a huge, huge industrial next step.
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Arkady, I am thrilled to be back together discussing Nebius with you. You and I actually set out to have this conversation one year after our first podcast, but with everything going on inside of Nebius, I think this was the first window of time we could find. Just in the last two months, you guys have announced large-scale customer commitments, rapid capacity expansion, a deepening partnership with Nvidia, major financings, and continued build-out of your AI cloud platform. I promise you, we will hit all of those today. But I do think that there's a bigger story brewing here around what exactly it is that you're building, a story that illustrates why when put together all of these announcements are far more strategic than they may appear at first glance. To get at that story, I want to take us back to where we left off. It's mid 2024. Nebius has emerged on the scene as the newest entrant in the AI infrastructure race. What is it that the market maybe got wrong or didn't understand about what it was you were building?
I think back then we had a clear vision. We started with a tiny 25-megawatt data center and we had a clear vision that this is a huge build ahead of us and we will need to build a lot in terms of scale and in terms of new functionality, new features, new tools which needs to be built for this new era. We saw our niche from the very beginning as helping people build AI. We had this experience. We were building AI in the previous 20 years and we built a big infrastructure for that, both physical and tooling, and we realized that in this new world there will be needed hundreds if not thousands times more than we have built before and it will require a completely new set of tools with our experience both in hardware and software and building scale systems. We left behind hundreds of megawatts of built data centers. At the same time, we are totally new startup on the market. And we understand very well the life of startups or the lives of enterprises trying to go into this new unchartered territory of AI. By understanding them deeply, we understand what tools they will need. When we started almost two years ago, there was this vision that we need to build something very very big. We should own the full stack. We should build through the whole stack. We need to optimize it, which means that we need to own the data centers. We need to build our own racks and we need to build all the software layers on top of it from basic cloud to all new services for today we can say inferencing or agentic whatever comes next. We felt that by our qualification we're one of the few teams in the world who can build it both in scale and functionality. We understand what needs to be built and I think when we started people just didn't look at us this way but again there was different times, people probably didn't understand well what kind of things we're facing. Now, much three years later, people understand that whatever we will build will be consumed and we need to go to space for that maybe even. And people also understand that it should be a new thing. It's not just old classical cloud and tooling reshaped for this new era. It's a completely new set of tools for a completely new set of users. It's not just software engineers who are using it now and they need different tools and that's what we're building, at big scale, full stack, optimized, cost effective.
Yeah, I think unpacking that a bit, I think people may underestimate just how much depth is behind the team inside of Nebius. I mean what you just articulated requires domain expertise from land and power acquisition through to hardware development of racks through to a large corpus of engineers going and scaling the software primitives on top of that infrastructure. Your team didn't start from zero. Could you tell us a bit about the team that you've built inside of Nebius and why it's unique for such a young company?
A year and a half ago, when we started, almost two years already, we were quite an unusual startup because we came with a lot of experience, with 20, 30 years of experience of building large-scale infrastructure for machine learning before it was called AI. We worked with Nvidia many years before this company was created. Again, we started from a very small installation which we inherited, just 25 megawatt. 18 years later, we already were running 10 times of this and this year we're building, we're growing again. Nebius will be this hopefully big, huge platform with hundreds of thousands of GPUs of capacity and layers and layers of services tailored, built from scratch for this new AI era for developers, serving the workloads which are demanded by them now, not what was demanded a decade ago.
You mentioned the long-standing relationship with Nvidia. So I want to transition us to some of these big announcements that we've seen from Nebius over the past couple weeks. Help us connect all of them and why don't we start with Nvidia.
It's not just investment, just money for us. It's actually much deeper work which is going on behind this investment with Nvidia, where together we develop and optimize, we help them optimize their systems. It's a lot of engineering work between the teams in the background. It's again a sign of a deeper collaboration with Nvidia and we are extremely proud of course that they become our partner and shareholder. But again, it's not about just money. It's good to have $2 billion but what we're building requires tens and hundreds of billions of dollars.
Let's shift focus to another big announcement that you guys have made, which is a large commitment from Meta. The headline of that commitment is $27 billion. But really, I think what's most interesting is how you architected that relationship. Can you talk a bit about what that $27 billion really means to Nebius and what it means to the overall platform that you're building for the cloud?
When you see the news about this 27 or so billion dollars, you should actually understand that in this particular contract there are actually two contracts inside. One is $12 billion when we really provide bare metal capacity to Meta for themselves to use and for this we are getting the second part of the contract which is $15 billion of back-top. What it means for us, we will be building, we will use Meta's readiness to offtake it, go to the bank and finance this capacity for our own cloud, much higher levels of the cloud which we will be selling on spot to thousands, tens of thousands of smaller clients.
We're all watching those charts showing GPU per hour rates go through the roof. And I guess what I'm hearing from you is that $15 billion contract is locked in at today's long-term rates should you not be able to sell it. But what you're saying is you're going to take that $15 billion of capacity and bring it to your core customer, that retail customer that leans on your software, services, tooling on top of the infrastructure and pays what you call spot rates in the market, much higher rates, effectively meaning that 15 billion could mean 50%, 100% more to Nebius over the life of that contract. Isn't this a similar thing to what we saw happen with Microsoft as well?
Different but similar thing happened with our Microsoft contract last year. It was 17-plus billion dollar contract where Microsoft actually got bare metal capacity from us and we're building bare metal capacity for Microsoft AI lab, but it allows us to go to the banks and use this contract to finance construction of our own cloud. So we use these big bare metal contracts not as our main line of business but as one of the ways to finance building our own cloud for the rest of the market.
That's interesting. You have said that before that these large deals with some of the big hyperscalers are a great way to finance what we do. I think getting off the blocks to be able to deliver capacity to small startups, startups that frankly don't have a contract that a bank cares to lend against, is a big kind of chicken-and-egg problem I think for the ecosystem. I know you have a number of thoughts around how many GPUs are actually serving that end of the market, the core end of the market that Nebius has targeted. You mentioned how we got in there and how we're trying to find ways in there to finance our way through it. But talk a bit more about that core customer to us and how we serve them.
So we see the main market for us, our main business model, in serving the AI-native startups and enterprises going online, and these are again thousands of different clients. They don't have behind them this huge piles of capital to build their own capacity, their own thousands of GPUs. We're building a cloud for them, a big cloud. What we're building is actually even this year will be measured in hundreds of thousands of GPUs. So it's basically the same scale as the other big hyperscalers. It's shorter-term, smaller contexts, but in large, much larger amount of clients who actually need much more services from us, which is important. We just don't just provide them with GPUs or bare metal. The big clients like Microsoft and Meta, they don't need our software stack. They have their own. These guys, they don't have their own stack. They need a lot of help from us. When we are building tools for them, and this is our main business, and this is what we're building, and we're building it at scale. To be there, you need to provide scalable, very efficient, very performant, cost-effective systems. That's what we're building.
Two thoughts on the capacity side of things. One, Nebius thinks about scaling capacity maybe slightly different from some of the other clouds or neo-clouds you might be compared against for this exact reason. Delivering a multi-tenant hosted cloud experience to the torso of the market requires a different type of capacity planning and scaling than you may see out of a large hyperscale deal on bare metal. So I'd be curious to hear a bit about capacity planning when you think about your core end customer and how you think about whether we need a 5-gigawatt facility or we need a 30-megawatt facility or both. Bring us inside the capacity planning of Nebius to build what we want to build.
You need to be very efficient and you need to start building from scratch from land. You need to understand everything from land permits and electricity permits up to how to build data centers, how to build racks, what software to run. If you outsource it, first of all, it will never be efficient. You pay margins to data center constructors, to rack builders, to other software companies. We build it through the whole stack. It's a full stack build which gives you economical efficiency but more importantly it gives you technical, engineering efficiency. It is optimized to the last bolt. It's optimized on all the layers. It works together as a system. This is what we built. Again, it should be built cheaply and optimally performant and it should be built in scale, should be big and very efficient.
You know, looking at the capacity today for Nebius, we have both owned locations as well as collocated locations. What I'm hearing from you sounds like the direction of travel is to own more of our infrastructure from the land all the way through to the software. If you extrapolate this over the next few years, what is the footprint of Nebius between owned and collocated, and what is the purpose of collocated for us today?
