Ladies and gentlemen, welcome to the Nebius fireside chat. I'm a little congested, maybe it's messing with my head. How's everybody doing today? In five minutes, we are going to be listening to Nebius's fireside chat with the CEO and the Chief Revenue Officer, which should be very clarifying for future guidance. Contracted power, the most recent 1.2 gigawatt US site. Potentially we end up seeing some more talk about active power and when they can get things up, customers that are coming in, how much that's prepaid for, all the good things that Nebius shareholders are looking for.
So, like I said, that's going to start in 5 minutes. I'm also going to be able to bring up both the price and the stock. Okay, so looking something like this for the most part. I don't have the call playing just yet because obviously you can see it hasn't started yet, but whenever it does get started, this is at the Morgan Stanley Technology, Media and Telecom conference. Later on, we'll also be listening to a few others. Okay, so we have Nvidia at 1:00, which we'll also be streaming on the main livestream. And then we're going to have Robin Hood's event later on as well.
MD Jared Isaacman can't get enough. You're so right, my friend. Buying even more shares of Shift 4 is exactly what we want to see. Okay, that said, Nebius is up 8.7%. They're not the only name in this space that's up a ton. I like you see Cipher Digital here up 8.8% or previously Cipher Mining. Let's check where I is up 11%. Nvidia is also up 1.4%. So we're having a lot of movement in not only the general markets. SPY up 6. QQQ's a little bit higher than that, 1.3%, driven by a lot of the names that we just ended up talking about like Nvidia for example. Let's have a look at the Mag 7 really quickly. Max 7, Amazon up 3.4%, Tesla 3.4%, Meta up 2.2%, Nvidia up 1.4, Google flat on the day, Apple flat on the day, Microsoft practically flat on the day as well. All right. Maybe I can even expand this so then you guys can see the chart here. Let's see. Because I don't think we're worried about looking at the screen that's not going to move. If it's a video conference, which I already know it's not, but if it is, we can always switch over. All right, so that's what we have. Let me just double check, make sure we have... Okay, so it is about to start. I still hear music, though. And then whenever we're good to go, I'll transition. You guys will be able to hear everything.
Good morning. Good morning. Good morning. Huge day for Nebius shareholders. Always very exciting. They do not do a ton of fireside chats. Maybe about one a quarter, I would say. Aside from the general earnings calls that we get. So, this is going to be hopefully really enlightening. Okay. That being said, Wix, another company that we need to talk about. This company is up 14% back above the $84 mark. And they just had earnings this morning. Very, very exciting. I knew I should have bought before earnings. Like I knew that people were going to be happy and excited about what they were going to put up. But hey, you win some, you lose some, or you let some pass by, I guess, is the real... Oh, is it starting? Okay, hold on. Let's switch over. Okay, no, they're not starting. Never mind. Just switching the song. I know you guys can't hear music, but I promise you, you will. Yeah, I just have to switch that over whenever it does come to that. Okay, so aside from that, we have a lot to be talking about later on, including the Nvidia fireside chat, which we're also going to see today. That's at 1:00. And then I don't know if there's any really large ones after that. AMD was yesterday. What else? AMD, Vertex, Mastercard.
Oh, okay. They're here. For important disclosures, please see the Morgan Stanley Research Disclosure website at www.morganstanley.com/researchdisclosures. And if you have any questions, please reach out to your sales representative. My name is Josh Bear, software analyst here at Morgan Stanley. We are thrilled to have the Nebius leadership team here today or part of it, Arkady Volozh and Mark Berditzki. Thank you so much for joining us.
Thank you, Josh. Thank you.
Maybe to start it off, Arkady, for those newer to the Nebius story, could you walk us through some of the history and what you're trying to build?
Well, that's not the first project of our team. We have some history. The team of engineers who started this company 18 months ago, the previous 25 years was running one of the largest IT companies in Europe. Infrastructure-wise it was 200 megawatt of different data centers equipment. We were the largest Nvidia partner outside of US and China, so we had some experience. And then a lot of geopolitical events happened and several hundred engineers actually went to Europe and we decided to start a new company. We left in 2022 and then several months later this ChatGPT moment happened and we realized that probably there is something for us to do here because we know the area very well. We were in machine learning, not even AI yet, for many years. We know how to run such systems and we were one of the big tier companies ourselves. And we realized that there is a space in this new era, there will be a lot of... all the big tech companies, all the big tech systems will go there, but also there will be a lot of independent companies and enterprise market which will go into this area. They all will need experienced infrastructure, people who can provide them with experienced infrastructure and who actually can make them competitive to the big tech companies. And we thought that this is probably an area where we could be useful.
We started with the company just on summer '24. When we started we had just one data center with us, that's all we had, 25 megawatts. We managed to sell our assets for several, two and a half billion dollars. It was a much bigger company but whatever, we managed to sell it, it was nice to start with. So we started with 35 megawatt 18 months ago. Today we're running 10 times of that almost. We publicly announced that we will be running another five times on that. It will be almost a gigawatt of active power this year, 800 to 1 gigawatt. And we also announced that we're building much more now. We have a pipeline already reserved for 2 gigawatt and it will be probably closer to 3 gigawatt this year. But what we're building is not just gigawatts. We're building a real platform for AI developers. A real full stack cloud. We build the basic layers starting from the ground, land, power, shell. We build our design and build our own data centers. We fill them with our own design racks. So on the first layer we are like companies, I don't know, Iron, Applied Digital, others who build the data centers, we have it internally. Then we build the racks, it's like let's say Super Micro, Dell, they build the racks, we build our own racks. Then we integrate everything and provide the basic layer, bare metal layer, it's called, to big players and whoever wants it. And on top of it we have product which is our own multi-tenant cloud. This is the same kind of cloud as the hyperscalers have, you know, the big names, AWS, Azure, GCP, these are examples of multi-tenant cloud. We have this full stack, we recreated the full stack. Again, we didn't inherit any IP rights, we had to recreate it from scratch and that's why this all cloud is very modern, very fresh with no incumbency. And this is our new stack. This is a new cloud with a lot of services on top of it. It's not just multi-tenant cloud which means basic cloud services, multi-tenancy, billing, security, storage, managed databases, it's all there. But on top of it there's a lot of services specific for AI builders like our Token Factory, it's an inferencing platform, or agentic search services which people who build AI need. Or just recently we announced human experts in the loop there. Human experts who actually perform tasks given to them by agents. It's agents running humans today. So that's examples of services which are on our platform. And on top of it we have a sales machine of course, go to market, which is verticalized in geographies, verticalized in industries like pharmacy, robotics, retail, whatever. So this is a full stack from ground to racks to cloud to services and the sales machine on top. This is the full stack cloud and we build it in like two dimensions: functionality and scale. And in scale as I said it's gigawatt scale. We are, if you compare us to the big hyperscalers, we're probably the smallest today but we are the same. Like our cloud today provides hundreds of thousands of GPUs. How many GPUs each of the hyperscalers provides? It's not millions, it's also hundreds of thousands, maybe more hundreds, but the same class. So we are in the class of, by scale, a full scale cloud with hundreds of thousands of GPUs and that will go to millions eventually when the gigawatts start materializing. So it's full stack on full scale.
That's a great, great overview and such an interesting story for a relatively new company to start with a lot of cash, hundreds of engineers with a longer history of expertise to move fast and build this full stack cloud. Mark, want to bring you into the conversation if you could talk a little bit about some of the different customer segments that you're prioritizing and really what gives you confidence in addressing those different groups.
Certainly. As you all should have heard, Arkady just laid out a very bold and broad vision in terms of the tech stack that we're delivering and the intent to actually meet the hyperscalers competitively. As a complement, we are also implementing a very broad distribution strategy. Today we have the privilege of servicing thousands of developers that come to us to build on our platform as well as having contracted with hundreds of customers. It ranges from individual AI researchers all the way up to some of the biggest companies in the world like Microsoft that could spend billions of dollars on our platform. You could say that because of our AI builder orientation we have a right to win with AI startups. So this has been a big part of our success in the recent past. We do that, as Arkady mentioned, by meeting them where they are with the technical capabilities that the AI builder is looking for. That same readiness has actually won us opportunities with major software vendors that are embedding AI in their offerings. So companies like Shopify and Cloudflare. And then even more recently we started to see opportunities with the enterprise. We believe in the fullness of time enterprise will represent the majority of the TAM. Today it's relatively narrow. So we have a very focused, workload-specific set of initiatives where we're pursuing specific verticals including healthcare, life sciences, physical AI, media and entertainment, retail, and financial services.
Excellent. Arkady, you laid out a pretty ambitious plan as far as capacity. Can you talk a little bit more about that expansion? I think yesterday you announced your approval for the first gigawatt site. What needs to occur to reach those goals of 3 gigawatt and beyond?
Yeah, as I said, we started with just one data center which was built outside of our core market in Finland. That was our first. Then we started quickly leasing data centers because to save time, you have no time to build, you need to lease. The first year we were leasing everything we could and we launched locations in France, in the UK, in Iceland, in the US of course, and in Israel. That was our first year. And today we mostly build ourselves and this year we are launching sites which belong to us, which we build from scratch and these are much bigger sites. This was the first example, Independence, Missouri. It's 800 megawatt expandable to 1.2, 2 gigawatt. Just got approval from the local communities. We have more sites coming like that. We continue building in Europe. Majority of what we build now is in US but we build not only in Europe and US. We are now opening our offices in Middle East. I don't know if we can mention this today, but yes, that was our plan last week. Singapore and Korea, Japan there as well. But what we build today is sites, big. We happen to build the largest, currently the largest sites in Europe. For us it's not so big. It's 240 megawatt in France but for today it's the largest in Europe. In US we're building much more. It's hundreds of megawatts going to gigawatt sites. This is the type of sites we're looking for and we have dozens of them. Today we have like 16 something locations announced. Again it's a pipeline. It's like 10, 20 is already announced and it's in I don't know a dozen of different markets. It will be more, it will be a network of data centers. Having your own platform allows you to use your own big site but also integrate anything you can find. If you found 20, 40 megawatt data center somewhere, just plug it in. It works. It immediately gets the software platform on top of it. All the sales machine works for it. And for the customers it's just a cloud. So it allows us to connect small sites, but we're building much bigger sites.
To clarify, at last earnings you had line of sight or a target to 3 gigawatt. Does the announcement from yesterday, is that incremental to that three or is that a step toward that progress of hitting that target?
This is actually an example of what we... I think Independence was included into our announcement because the contract there was closed, means everything was signed and binding before approval by the authorities. It's another step, approval. There will be more steps always. It's a long process and again, it goes in dozens of different locations. If one of the locations delayed, fine, we have others going. That's how we derisk ourselves. This stage yesterday was just passing a very important stage of local approvals. So it was included into 2 gigawatt but there will be more coming and we said that we probably will be able to announce at least 3 gigawatt this year but it's a pipeline. It's the table which our guys have hundreds of lines there with sites, potential sites. Of course the bottom 100 will never materialize but the top 100 of sites eventually dozens of them will come to life.
That's helpful. Mark, so we've been talking about the scale of what you're building. How does the demand, what does the demand look like? And what gives you confidence that there'll be demand to align with this buildout?
Well, I'm sure that over the last couple days, you've heard from a lot of executives that demand is extraordinary right now. Demand far exceeds our supply. The opportunity for us is actually to optimize our model to be able to build a high margin, durable, long-term business. You know, to take our abilities to generate expanding pipelines and drive the future capacity decisions that Arkady just mentioned a moment ago is the vision. Today we have so much demand that we have to actually prioritize. So we're taking the initiative to shift away from a transactional mindset to a value-based and solution selling approach. Our sellers spend time with customers learning about near-term and long-term requirements, understanding how our capabilities tie to their business opportunities. We use that in order to be able to prioritize customers that actually align against our business model. And as a result, we are now driving sale of future capacity at an increasing rate. We're also delivering longer contract terms. As a matter of fact, the last quarter we shared that quarter-on-quarter the number of year-long contracts doubled. We also saw a 50% expansion in ASP and we saw prices go up even on older generation GPUs. That's important. Now we're also, and we haven't shared this yet but we've added it to our set of priorities, we're now securing upfront payment from customers up to and including in some cases customers paying 100% upfront. So based on this principles-based approach, we're able to prioritize the kinds of customers, the kinds of deals that we're looking for that support the overall business model that we're going for. Now you asked about demand. What really excites me about demand right now is actually how we grow with our customers. Customers that have landed on our platform to start with a small project and then expand with us over time. Some customers are doubling quarter-on-quarter. They're expanding the use cases that they have on our platform. But what really gets exciting is when they actually move to revenue generation and then we're actually winning and growing with them at the same time. And that is a durable opportunity for us that actually will extend into the future.
So when you're talking about securing upfront payment, you're not just talking about Microsoft and Meta, you're talking about the broader customer base.
Great. And to your point on sort of growing with customers over time, I think that ties pretty closely to training versus inference. What are you seeing as far as the mix on your platform and how does that evolve going forward?
Well, first of all, I think we all know this, but I want to say it anyways. For AI to deliver on the commercial vision, inferencing needs to outstrip training, period. Inferencing at the end of the day is the commercial realization of the functionality somebody's delivering. Inferencing is growing faster than training on our platform. And we're seeing it along three key vectors. Customers that are using our platform to do their own inferencing, customers that are actually inferencing platforms that have been built on Nebius, and then our own inferencing solution, Token Factory. Interesting vector of demand, I think some of this has been reported in the technical press, is the fact that we're now also seeing software vendors who have built functionality on the foundational models that are looking for improved performance, quality and cost that are now diversifying their models and utilizing open-source or even training their own models. And that's opened up opportunity for us to sell our inferencing solution in the software vendor sector. We believe this line of demand is going to continue in the enterprise and be a key way that we're going to potentially be able to service enterprise requirements.
Excellent. Arkady, you have some really large customer contracts and customers, but you also have this very clear focus on the broader AI stack for general customers and a broader tail. So, how do you balance the two? Particularly thinking about the buildout of dedicated large GPU clusters versus servicing this broader market opportunity.
