MARA Holdings, Inc. (MARA) Earnings Call Transcript & Summary

So multibillion-dollar deals secured, and it sounds like several billion on the way with this group here. So you did touch on this, Sam, I want to kind of go a little deeper on to this. So CapEx intensity of AI data center builds certainly quite after. There's no secret there. John, maybe you can discuss the sources of funds, cost of funds and the cost per megawatt to build out these data centers.

Yes, sure. We -- our model is probably no different than others on the panel. We look at a project level financing that will be primarily debt, 80% of the cost being debt, high yield, attached to the asset and the remaining 20% through equity, most likely through the TopCo pushed down into the project. To give you a sense, just on a theoretical project, call it, 100 megawatts, call it $1.2 billion to $1.4 billion to build. So it's somewhere about $10 million to $12 million per megawatt. This depends on where you're building it. We tend to be in remote locations. So cost is higher. Russell's point about labor cost and access to certain critical folks raises the cost to some extent. And so when you do that 80-20 split, you're talking about a few hundred million dollars of equity that has to be invested in our first, let's say, 100 megawatts. But when you look at the returns on that, you're talking about upwards of $10 million to $15 million net NOI. I think we have a slide in one of our investor presentations that teases this out. The yield on cost is going to be in the high teens. And at some point, the cap rate is in the single digits. And so you get somewhere on 100 megawatts, $2.4 billion of asset value added to the company. So you compare that to our current valuation and asset base, the 6.3 gigawatts that we have is a very valuable asset if we can convert those assets to spinning data centers. Our average construction time is going to be much like anyone else here so you can map that out to what that looks like from a revenue and growth perspective for the company. What I'd like to do sometimes for fun is take that framework and then apply it to the 1.6 that we've got spinning and then apply it to the 6.3 to see what the potential value is. And then the rest is really about execution, making sure you put together a bankable lease can take it to market. So the high-yield folks like what they're going to get and feel secure in the asset -- and then, of course, you need to execute and actually deliver the data center.

Thank you, John. Anyone else have anything to add on CapEx or funding for these projects?

So I agree with everything that everybody has talked about. And 1 of the constraints, obviously, is labor. And a lot of these data center builds, the GCs use travelers. So guys that live in North Dakota that are spending 10, 12 months in West Texas to build the data center. We took a bit of a differentiated approach with our EPCM and the fact that they build the vast majority of the data center in a factory. So it becomes an assembly line process rather than a bespoke one-off deal where you've got a number of different trades trying to work together. And that has simplified the delivery for us, but it's also with a fixed price lump sum contract given us certainty. So the way we talked about it is our expectation is that $10 million, $11 million a megawatt complete RFS on the data center, and we expect similar to what John is talking about, to finance that at the project level through the debt markets. We're targeting right now high-yield investment type -- excuse me, high-yield investment bond opportunity. But CleanSpark has -- we've used our bitcoin as the means to prevent any equity dilution on the company for that build. So we went into the project, signed the lease on the very first day we did our equity contribution. So it is fully funded from our side of the table, and having that certainty of the space in the assembly line and the certainty on the supply chain really derisks that. So in our conversations with lenders that's really what they're focusing on is what are the potential risks that get in the way. So as you think about CapEx and you think about the finance on these, what you also have to consider is the liquidated damages if you fail to deliver on time. and that becomes an existential risk for some folks in this business because if you make promises and there are GPU purchases that can be many times the price of the data center build. Now you've got some real exposure for liability. So getting the certainty there and being able to laser focus in on what that build cost and the time frame looks like is a differentiator when it comes to financing these projects.

Great insight, Matt, Anyone else have anything to add here?

Just I'll pile on a little bit. I think similar to Matt's concerns regarding risk of delivery. It was 1 of the reasons why we chose to partner with Starwood we have such a big portfolio to do this ourselves, especially not being an expert in building data centers for hyperscaler demands. We want to increase certainty and reduce risk Starwood has built over 70 gigawatts of data center capacity for hyperscalers. They have a captive EPCM within the worldwide digital who's built a lot of these sites. And what we're finding is because of the structure of our model, our cash-on-cash returns are significantly greater than the traditional model because we leverage our site as a contribution on the equity stack. And if you use an 80-20 model the amount of additional capital we have to include over and above the value of our site in these joint ventures is fairly de minimis, which means that the cash-on-cash return is much greater. It also means we can do more sites in parallel simultaneously. -- and greater capacity without it having to all be credit provided by us. So we feel very optimistic about that. It's going to allow us to move very quickly as we really get started here, and we're super excited about it.

Yes. If I may add, we do something similar. We have access to power, infrastructure. And in some cases, we'll have power plants. But that land once it gets fully developed and you're ready to go vertical becomes much more valuable than what you pay for it, and that can be used as a contribution on the equity side. On the execution side, being a smaller Bitcoin infrastructure company, we were thinking about the risks with execution around these very complex data center projects and -- we approached it in 2 ways. One is on our initial project, we partnered with a development company that is a group of AWS folks who have experience developing, constructing and operating these facilities. That's allowed us to design and develop and market these sites in a way that customers would expect. And then this past quarter, we started building our own in-house capability, hiring the first major role to the company, a gentleman that is run and built over $10 billion worth of data center projects for Microsoft. I think you built their largest AI facility. -- and hiring is tea here over the last couple of months. So building out our own execution capability to deliver these sites to the end user customers at the level of quality and timing that they expect.

All right. Let's move on to a controversial topic to spice things up a little bit. Some headlines out there would suggest that we are in an AI infrastructure bubble. I'd be curious to get the group's thoughts on this, and I'll leave it open for whoever would like to start here.

I mean I think if you talk to the people who have a need for the compute, they would tell you there's no bubble. They just need a lot of compute and they don't have the ability to deliver on it. I think there are 2 things going on. One is, is there a bubble in the hyperscalers and this $1 trillion spend? Or is there a bubble in the AI compute world, 2 very different things you're looking at. AT&T recently announced that over 40% of their workloads are being done on open weight, open source models. They are not using frontier model providers for that. They expect that number to grow to 70% over the next 2 years. One of the biggest challenges today is cost per token. And about 60% of workloads done by AI today are fairly mundane. They can be done by open source model or an open weight model on de minimis amounts of infrastructure. So there is a huge need for inference the question is how much of it will happen in the hyperscaler cloud and with the Frontier model provider versus how much of it will happen in the enterprise and with the let's call them neo-clouds for now, but for the neo-clouds providing a full stack of software services that allow people to run and load whatever models they want to run in fully air gapped environments. One of the reasons we when after the Axion opportunity was, we wanted to have the capability to run fully airgap, fully sovereign increase at scale for enterprises because if you look at what it costs to run in AWS today with dedicated hardware, dedicated resources versus running in private cloud, it is a 10x higher cost. And companies are looking at AI as a cost item, right? It has become part of their OpEx budget. And if they are going to pay huge fees to the frontier model providers versus training their own models and paying once for a model and then running it proprietarily. You're going to see a lot more inference move towards either behind the firewall or near prem, on-prem inference providers who can allow people to run sovereign models. And I think that is going to be by far the biggest thing moving forward in this industry. And you'll still see a lot of revenue going into the frontier model providers, a lot of revenues still going to the cloud providers. But the first in cleaning of this, I think, is how Google reorganized their AI business. Who is it that runs Google's AI business today. It is the guy that operates their cloud business? It is not their AI team.

Yes, to echo Fred's comments, I certainly -- from CleanSpark's perspective, we certainly don't see it as a bubble. Russ and I had breakfast this morning, we were talking about the increase in rates for these long-term leases. And the -- how rapidly they're appreciating and what we really see is that there are 3 constraints. Capital. So money is flowing where there's the least amount of risk and the highest credit certainty energy availability and those energized megawatts to have conversations with hyperscalers that they're actually contemplating behind-the-meter investments and building their own power plants in order to support the data center, the need for compute that they have. gives you a pretty strong indication that this is certainly not a bubble. And then the last thing is delivery certainty. As we've entered the conversations for credit assessment of the project and working with the high-yield market. they talk about the fact that certainty of execution is now the predominant factor in determining not only the availability and the willingness for the high-yield market to provide that credit, but also drives the rates in a very strong way. So I see that if you have energized megawatts of power, and you have those -- those exist in areas that don't have strong NIMBYism. I mean, let's be honest, if we sat here a year ago, I don't think anybody on this panel would have assumed that the Governor of Texas would come out and put a moratorium on data centers for certainty of execution. This has become a political hot mess. And both sides of the aisle are mutually opposed to it. But now we find ourselves with the labor unions in agreement with President Trump that it's an absolute necessity to build these sites here for 2 reasons that number one, just like with Bitcoin mining. If you drive Bitcoin mining offshore, it will continue. It will just continue somewhere else, and that doesn't give certainty on block space for U.S. investors. But number two, these models that are being trained are being trained outside of the U.S. And so that presents an additional level of risk. So we really feel strongly that bringing the right package and the right assets in the right communities and doing an educational process in that is going to be a differentiator to solve for the bubble. In Texas, we worked with our EPCM provider for our Georgia site, and we did a roadshow. We set it up like a trade show with boots addressing everything from dark sky issues and water usage to ambient noise and impacts on utility rates. And if you can lead with education and facts rather than just hype in theory, it's a huge differentiator that we believe solves for a lot of that issue, but as to whether or not there's a bubble, hard note from my perspective.

I have ever contrarian perspective, and I think this is a better way to look at the question. I would say that whether it's a bubble or not is kind of a moot point because if you look at technology, development and infrastructure build-out for the last 50 years, every single major improvement in our capabilities as a humanity businesses, technology services on a global basis has been preceded by major investments like this. The last 1 was 30 years ago, where people were sort of scratching our head. What is this Internet thing? And let me tell you what happened. We built out the most advanced telecom infrastructure capability around the globe. We're all super connected. We then added to that mobile and content platforms and social connectivity software, which eventually delivered to us. What everybody is itching and looking at in their hand, where you essentially have a compute content bundle that gets delivered to you effectively for free. And that took billions of dollars of build-out to deliver that type of capability. AI is another one of those. It is the greatest general purpose technology we've developed in the last 30 years. And I can tell you, I've been a technologist for that time. And I've was trained to see these types of waves. This is another big tech wave. You can tell it's a major tech wave when you have infrastructure investments that hit the core elements of the base infrastructure in any given epoch, if you will. And this is the first time we're touching the energy infrastructure to power this technology. So like most of my colleagues are talking about hyperscalers are looking to build out energy. They're looking to solve the pain, which is speed to power, if you will. That's because the ultimate new bundle is going to be intelligence. We will now have the ability to have intelligence walk around in our pockets at the greatest level we've ever seen, and that's going to be made possible by multiple hundreds of billions of dollars per country. So that's trillions of dollars on a global basis that will be built out to deliver this technology. We cannot stop. As a country, if we stop doing this, we will fall behind because it's so powerful to technology that is now almost at a military level. So I think we were too where we built out roads to sort of protect the country in that sense. That's the power of this technology. And the reason the companies on stage here are so valuable is because we are part of helping to create that new technology infrastructure. So bubble or no bubble, you can only see it in hindsight, connect the dots, but I'm telling you the dots point to a new form of infrastructure that integrates energy, compute connectivity and telecom into one bundle to deliver tokens or otherwise known as intelligence framework or intelligence infrastructure.

You already have it. We are not in an AI infrastructure bubble, at least according to those -- Sam, did you have something to add here?

Yes. Just very briefly, obviously agree with that. I would say that there are 3 catalysts for the Industrial Revolution. The first 1 was electricity was changed industry than the Internet, it's change industry and now AI, which is going to change the industry. So that -- there's clearly no bubble. But just with respect to the over -- there's a lot of pushback on data center development. And I think there are many communities these days who are upset that some of us are perhaps taking farmland or building these on-site data centers in their communities where it just used to be greenfield. And that's one of the main reasons why white fiber is retrofitting. These are -- we're taking over basically facilities that are left for dead. And we have community days. So for example, in North Carolina, we had a community day where we explained that we're using 95% less water than the facility that was being used before we took it over, that we're creating a lot less noise than the facility that we're taking it over from. So this retrofit format really solves a lot of the tension that's happening for -- against -- which I think is probably not a great idea, doing greenfields are kind of -- you're going to get community pushback, especially if you're taking up farmland. So this retrofit format is a way to sale from that community pushback that we've been that we've been able to solve with our Community Day with the local communities where we're building these retrofitted data centers.

Mike, could I add a quick note I wanted to add on to something that Fred touched on earlier about the enterprise client and with the question being, are we in a bubble. The answer for Big Digital is now as well. I have -- I spent 20 years in health care. Just 1 small sector of this great economy we have in the U.S. And in the last 2 months, I've had the opportunity to sit down with 2 founding CEOs of health care-focused and drill down to long-term care focused software companies, building AI models to serve that sector. And I heard the same thing from both of them. we have the product, we have the client. Our biggest fear as we scale up and out is that we can't secure the level of compute that we'll need going forward. And if I could leave anything with the investors in this room is we're always thinking about the big 5, right? We're not thinking about the tens of thousands of enterprise-level companies out there that need the same level of compute and they need it secured and available so that they can grow their businesses. And so that's something that we are at Big Digital and very focused on is the enterprise level clients more specifically with my background in health care, I'm very focused on how can I serve the health care client. But I would say the current narrative whomever was made up by, I'm sure they had their agenda, but it's completely false. -- let me tell you, there is a bubble. Let me tell you where it's at. So there's about 5 gigawatts of rack space being delivered every year, and there's about 15 gigawatts of chip demand every year. But in Texas, what the governor did was reasonable because there was 474 gigawatts of request in for data centers. We don't have enough foundry silicon foundries on the planet to use that much space. And that's what's scaring everybody. It's because there's 5x the request in Texas that the whole grid commits to. So the issue is not the guys that were rack space or the guys living the chips -- it's every farmer in rancher in Texas or Oklahoma or any state that has a transmission line or a gas line running through their site that says, "I'm going to put a data center there. we get people telling us, "I've got a 3 gigawatt site, the next cobest says, I got 3 gigawatts stand the goose says, "I have 3 gigawatt site. Well, they're all counting the same gas line and they're all count the same gas. And that's the issue that the Governor's office in ERCOT had in Texas. It was how many of these data center requests are actually real. So there really is 15 gigawatts a year of demand, and we really are -- we're not able to fulfill it. And it's going to go on for as long as we can. What there's not is nearly 500 gigawatts of demand in Texas alone. And that's where I think -- I actually don't think it was a bad thing the governor said, "Hey, wait a minute, how much of this is real. Who has a substation, who has a PPA, who has power, who has your behind the meter plan together." And I think it's reason for any state to ask that question because all of these are not real. We saw the same thing in Bitcoin mining, some -- I know some of you guys were there. Texas ERCOT told us -- and by the way, Core Scientific is 1 of the largest users of power. We talked to ERCOT multiple times a day, all the time. ERCOT told us there was 20 gigawatts of Bitcoin mining demand in Texas. There wasn't. And there's like a bit of that. What it was, was the same guys chasing the same -- everyone wanted to sell me some stuff, they want to sell freshest, -- they want to sell mats.sthe same as people just brokering these deals or putting deals together. So that actually is a bubble. There's not tens of thousands of gigawatts of demand in every single state in the country. So I think what needs to happen is some regulations on, hey, what's real and what's not real. I think that's an unbelievably reasonable request for anybody to make. I agree with that. Just to level set, it takes 5 to 6 years to build a new gas-fired facility. And while solar and wind or grade, it's intermittent. And until we manage the orchestration issue. So if the U.S. Sun Duke did the study last year, the U.S. has 72 gigawatts of power available to it based on current generation today. you want to add anything to that? -- it all takes a couple to 6, 7 years and billions and billions of dollars to do it.

Yes, there's a dislocation. All right. Last question. We do have 3 of the largest publicly traded bitcoin mics on the stage here. So I'd be remiss to not ask a question about Bitcoin and Mining. So specifically for MARA, CleanSpark in bid tier if either of you had something and, specifically, how do you plan to leverage your mining assets in Bitcoin Holdings to really fit into your longer-term strategy as you continue to execute on the AI data center side?

Well, Bitcoin was obviously higher a year ago, and it was obviously lower a month ago. And so we've developed an institutional-grade trading desk to manage our Bitcoin. We have -- if you go to Bitcoin Treasuries, I think we're 8 or 9 on that list. Fred, I think it's but we have over $1 billion in Bitcoin, and we have $400 million in largely untapped going back lines of credit and we have an institutional grade trading desk to help generate yield on that $1 billion plus a bitcoin that we hold. So we see it really as a capital tool. Additionally, we've prevailed on land and power sites because of Bitcoin. In Cheyenne, Wyoming, as an example, 110 megawatts from Black Hills Energy, they put out an RFP to acquire that, and there were 2 bidders, One was a $1 trillion hyperscaler and the other was CleanSpark. And we prevailed not because we have a better balance sheet or were more handsome but because of the fact that we were able to deploy immersion cooled.

From our perspective at Saluna in this topic, Bitcoin is a core part of our business, we're not 1 of the largest big coin miners, we're not a bitcoin miner at all. We're 1 of the largest bitcoin hosting companies that host some of the largest miners -- and that business approach allows us massive amounts of flexibility, especially as it relates to partnering with these large power plant owners. They have a problem, they have wasted energy that they need to monetize very quickly to return these projects to profitability. So we can deploy Bitcoin mining to some of these sites, especially the smaller ones, we can continue to grow our hosting business, build a relationship with these power asset companies, which allows us to then monetize that asset while we're developing the AI project, which tends to take longer and also show them a quick win for monetizing that power asset, which unlocks for us a lot more projects that are even bigger. That's how our pipeline has grown so significantly over the last few quarters because we've developed this very strategic approach to monetizing their power fast and then opening up the door to a longer relationship where we can build much larger scaled operations on the AI side. So Bitcoin has become a very strategic platform for us as we transition into.

All right. With that, that will conclude our panel discussion for today. Thank you all for attending.