CoreWeave, Inc. (CRWV) Earnings Call Transcript & Summary

Excellent. Thank you, everyone, for joining us this afternoon. My name is Keith Weiss. I run the U.S. software equity research franchise here at Morgan Stanley. And really thrilled to have an opportunity to talk to Brannin McBee, Co-Founder and CEO of CoreWeave.

So Brannin, maybe just to open up the conversation. Already, we've seen a growth algorithm from CoreWeave that I haven't seen in my career, right? And I mean, one of the things I love about research is getting to understand new companies and new opportunities and new businesses. And this is all new, right? And over the last couple of years and the last couple of quarters, you guys have described that demand that's already showing up in a huge backlog already showing up in growth rates that are really eye-popping as insatiable and relentless, which to me means that we're not going to see this come to a trickle out anytime soon. So can you talk to us about where you've seen this demand come from? How foundational is it? And how certain are you in sort of the durability of this demand, not just through 2026, but you guys have started talking about targets into 2030.

Yes. Yes. So it -- look, you're hearing this across the space, right? You're hearing it from our peers, you're hearing it from our clients, you're hearing it from our suppliers. The demand profile is truly overwhelming, insatiable. I would characterize 2026 is probably broadly sold out in terms of billable compute capacity that's available into the market. And it's robust, and we'll get into this throughout the conversation, but it's robust across several sectors, whereas I would say previously, like it was isolated to AI labs, right? That was really the starting cohort of where demand grew from like 2022 plus. And then for us, it hit our hyperscaler cloud clients, right? And they were coming us to support their product build-out. And now I would say we've seen this rapid advancement of enterprise demand. The enterprise cohort is absolutely there, whether you look at our numbers for that, you can look at some of the numbers floating around with Anthropic and market for just a true understanding of how quickly enterprise adoption is scaling right now, like it's truly fascinating. And within our guidance, we offered color of exiting 2026 at $17 billion to $19 billion, exiting 2027 at over $30 billion in ARR. To contextualize that a little bit further, we exited 2025 at $6.7 billion in ARR of demand, right? So it's just this massive step-ups in change in revenue. And within all that, the customer behavior is changing as well. There's 2 main points I'll hit on there. One is the customer is looking for longer duration contracts, right? As most people in here know, we signed multiyear take-or-pay agreements, right? And 24 months ago, those were, call it, 3-year contracts. 12 months ago, there were 4-year contracts. I would say now in our $66.8 billion of backlog that we have, that is 5-year weighted contracts, right, with some contracts in there extending up to 6 years. I struggle to see visibility like materially beyond that, but the customer profile is saying, we want this infrastructure for longer. And as a reminder, that's for like kind of single SKU exposure. They're coming in saying, we want Hopper for 5 years. We want Blackwell for 5 years. That's one aspect of customer demand. The other aspect that we're seeing that's so strong is on older generation infrastructure, right? So clients are coming in asking specifically for A100s. They're asking specifically for H100s, 200s. And of course, for Blackwell. Also, it's not a cadence of they come in asking for Blackwell, and they can't get it. So they're like, okay, I guess I'll take Hopper instead of it. And the driver of that is they've engineered their workloads. They have specific use cases for the specific pieces of infrastructure, right? And that to us, the main driver of that is inference, obviously. We'll chat about that more as well. But this all speaks to this like highly sustainable demand profile, not only for latest-generation compute, but the broad set of infrastructure that's being delivered in the market today.

Got it. When you talk about, it's sensational level of demand and there's other vendors talking about it as well. And you're right, it's not just CoreWeave talking about it, I fear that might overlook the advantages that CoreWeave has in the marketplace, right. And the question that I get from investors, a lot is, is there a differentiation, right? Is this just they're able to provide the capacity and therefore, they get the demand? Or is there some reason that the customers are coming specifically to CoreWeave? And from our work, there is. There is differentiation in terms of your ability to build out faster than anyone else to get the most recent technology out there faster than anyone else, but probably most importantly, to keep it up and running, more durably than anyone else. So can you talk to us about how you guys have built out those competitive advantages? How durable you feel they are? And how you're going to extend those even further with the software layer.

Yes, I think very intentionally, right? And this all goes back to 2019 when we were really standing up our cloud business originally. And that cloud business was built around this concept of parallelizable workloads. And the fundamental idea that parallelizable workloads are different than serializable workloads has different infrastructure, different operational infrastructure requirements around it. So you have to build the thing for the thing, so to say. And if you don't, you're asking your clients to take compromises, right, compromises and stability, scale, ultimately performance, and so the product that we have in market today, I think, is widely recognized as the most performant solution for operating parallelizable compute at supercompute scale, right? These aren't supercomputers that are being delivered in the market, and they're widely complex to not only bring online, but also to stabilize, and it's the CoreWeave, like operational infrastructure suite that sits on top of it that allows for that to exist. And so who recognizes that? Third-party consultants recognize that right? I think, analysis does a phenomenal job, really benchmarking the different solutions that are out there in market for running this infrastructure end. We've been singular through two of their first two reporting cycles. Now it's our clients who keep coming back to us for the products that we have. They are choosing to work with CoreWeave over and over again. And that is diversifying within not only the AI lab cohort and the hyperscaler cloud cohort, but also within the enterprise cohort, right? These are the blue-chip enterprises that are coming into CoreWeave saying, these guys are running this infrastructure correctly. And it's a long-winded way of saying this infrastructure is not fungible, right? H100 at one of our -- at one cloud is not the same as the other. And within that set, we are the best operationally at this infrastructure. How do we keep that pace? I mean this is our business. This is what we invest in on a daily basis. We have incredibly tight engineering relationships up and down the supply chain. We're working incredibly closely with our suppliers, with our clients, with our data center operator partners to understand and deploy what is the most effective engineering solution to delivering this supercompute infrastructure at scale. At the end of the day, I was like a lot of proprietary information that comes into our business, right? Like we are solving the problems of the most intensive AI users in the world on a daily basis. And it allows for us to kind of skate to where the puck is going, right? An example that I really love, and I'll stop talking is when chain of thought models were introduced into the market. This was at a time where I think the broader buy-side, sell-side thesis was models going to be quantize. Everything is going get smaller. We're going to run lots of models on one GPU. Perhaps you don't even need data centers to run models in. But you give these engineers the most performant infrastructure out there, and then they started looking at it saying like, well, what have made the model bigger? And inference left the GPU and left the node, and you could use hundreds of GPUs to run inference on instead, leveraging a high-performance bandwidth capability between those GPUs. And you got chain of thought reasoning that was introduced to models. And it was like a complete paradigm shift in the way that the infrastructure was consumed. And that immediately led us to understanding memory is going to be a path that really matters, right? Like how much context can you hold in memory on the nodes and within the clusters. Where is a similar analogy today? I think, it's agentic workloads, right? Agentic workloads, we're seeing increasing pressure on peripheral demand. I would say like CPU demand is absolutely going to increase as Agentic workloads are scaling. We're seeing that pressure from clients. Storage is another component that's been really exciting for us across our client base. We disclosed in our Q4 earnings that we have a -- I believe it's a greater than 80% attach rate with our clients who we generate more than $1 million in revenue from for our storage product. And our storage product today is well into the -- well north of $100 million in ARR. That's a product that like didn't really exist not that long ago, right? Our ability to attach peripherals and for them to scale quickly and be quite attractive for us operationally and quite attractive for keeping customers on the CoreWeave platform, I think, is a really exciting opportunity for us.

Got it. And you talked about the tight relationship with your suppliers and one of those big suppliers and an investor is NVIDIA, you talked about expanded relationship with NVIDIA this quarter. Talking about a couple of ways that you're going to be working more closely together. There was a $2 billion incremental investment, which is interesting. But even more interesting is what you guys are doing together with software. So can you dig into that? What's the nature of that relationship? And how is software becoming a bigger part of the story at CoreWeave?

So that announcement in January, that more comprehensive relationship was all about accelerating growth, right? Accelerating our ability to grow at the pace of AI adoption. I think the software side of it is you're absolutely correct to highlight and it's this acknowledgment that the CoreWeave software stack is the best way to run this infrastructure. And for us, when we discussed it in our earnings was, this can lead to an opportunity for us to sell that software solution to other entities. So for entities who may want to have GPUs on their balance sheet, right? Or they might have data sovereignty priorities. And thus, they need to have ownership of all the infrastructure. That ability to take that into market, I think, is a very margin-accretive path for us to be able to go down.

Outstanding. All right. So insatiable demand, market-leading product and solution that you're bringing to the market. And it's created this tremendous backlog, $67 billion of revenue backlog as of the last quarter. Along with it comes a lot of CapEx. You guys have -- you got to build out the infrastructure to be able to support all this demand. You guided to $30 billion to $35 billion. I think one of the investor concerns is the financing of that on a go-forward basis. Can you talk to us about how you're planning on financing that level of investment in 2026 and then beyond?

Yes. So -- we break down -- I think that we've been kind of market leaders and thought leaders in how we finance this infrastructure. And starting with our original DDTLs I think, 3 years ago at this point. We have ParentCo and AssetCo is kind of how we break the business down to, right? And all of our assets sit at AssetCo. That $30 billion to $35 billion guide on CapEx, let's call it $32.5 million midpoint. That all sits at AssetCo. And AssetCo, we're able to bring these financing facilities into where, I would say, we have extreme levels of demand to participate in the paper. One aspect to highlight, and like you've probably seen headlines about an asset level raise that we were working on. And while I'm not going to talk explicitly about those headlines, that's something that we're very excited to announce in the market. This advancement of the structuring at the AssetCo, I think, it's all representative of not only our execution track record, but also the durability of our contracts and our data center agreements. It all says, yes, we love CoreWeave paper. Yes, we love the way that we're bringing into market. We want to underwrite more and more of it. So that backlog will get financed down at AssetCo with some participation from parent down into AssetCo. I think the other aspect of your question was a little bit driven by margin of the business, near-term margin. And look, like I spent the last 2 days at LevFin in Florida. And at the end of the day, CapEx requires an investment, right? CapEx requires investment period as it comes online, and we brought some slides onto our IR deck that I encourage everyone to go take a look at that breaks it down in more detail, but the net of it is we have a sort of 3-month investment period on bringing CapEx online. And once that CapEx is online, and stable, take it like month 3 to 60 in a contract, each contract each deployment really has a 25% contribution margin up to the parent, right? So for every dollar of revenue that's coming into these deployments, you have $0.25 going straight up to the parent or it's straight up to the holdco afterwards, right? So you take that one deployment and you now layer it with lots of deployments that are coming online over time, and you have this very robust sort of revenue stream going up to the parent. Now where are we today? Today, we're in this extreme growth period, right, where quarter-over-quarter growth. I think we grew our active power by nearly 30% quarter-over-quarter, Q3 to Q4. And when you're incurring the expenses of growing active power that quickly, it's, of course, going to weigh on ParentCo, right? Because you're in this like 3-month period where you have revenue starting to generate, but you're paying for the data center costs. You're paying for the beginning part of depreciation on the infrastructure during that ramp period. And so -- we have large blocks coming online and like it's a smaller amount of infrastructure or in other words, like such large percentage growth, it will weigh on near-term margins. And so all this is to say, it's an extremely intentional path that we have to growing our business and moving at the pace of AI demand, right? Like this is a phenomenal opportunity for growth. We're doing so in an incredibly risk controlled and risk-adjusted manner with highly accretive contracts that underpin the entire business.

Got it. So there are 2 real veins in there. On the financing side of the equation, your -- the people are looking to finance you are getting more convicted, not less convicted sort of in the underlying business financing costs, if we look at it from what we've seen over the past couple of years have come down from 12% to 9%. And there's an expectation that's going to continue to come down in terms of what it's going to cost to finance it. The other side of the equation, I think what scared investors on the most recent conference call was a forward operating margin forecast that was below what consensus had. But the other part of the equation of what was wrong with what consensus has was the CapEx number. We were well below what you were expecting. And there's just a natural like absorption period, right, that compresses margins in the near term as CapEx is ramping that quickly. That wasn't question.

I completely agree.

CapEx requires investment. And we're at the kind of the trough or Q1 is the trough of that margin profile for us. From here, it's expanding. Okay. So I think part of the reason why that touched the nerve, like with operating margins, is what we're hearing in the marketplace in terms of there's the demand that you're seeing, but you guys are also creating a tremendous amount of demand and not just you. It's all the hyperscalers are creating demand. And component costs are coming up. And memory costs are skyrocketing, and it's hard to get people actually build out these data center facilities. So can you talk to us about that side of the equation, like the degree of difficulty in executing to these build-outs and keeping the project like on time and under budget, if you will, right? How do you maintain that margin profile with these potential costs.

Yes. Supply chain. Supply chain is immensely difficult. I think, it's something we've been quite vocal about private public version of us like it is, these are utterly enormous engineering projects that are being brought online. And I'd encourage, if you ever have an opportunity to go to one of these sites, like please go visit them. And I think you'll begin to get an understanding of just how hard it is to bring these things online.

But they should be invited because there's a lot of security at these data centers.

Yes. We thought -- there is -- and I think that, that's been underappreciated by the market, right, like we're throwing on terms like 1 gigawatt, 5 gigawatts, 10 gigawatts, like it's just a number on a spreadsheet, but the reality is like it is thousands and tens of thousands of people to deliver infrastructure at that scale. And I think if we were to ask like, where is the bottleneck in the market today. I would differentiate between power and active power, I mean, power and data centers, right? It's less about electrons, right? We observed that the electron availability on U.S. grid is there, but it's how do you deliver those electrons into the racks, into the servers, whether it's the physical infrastructure that sit on the site, like transformers, backup gen, back or battery, everything along those lines, or it's just the people, right? Like electrical engineers are an incredibly critical part of delivering these sites. You can't really make more electrical engineers very quickly, right? That is a skilled trade that takes years to bring a workforce online for it. So I think that, that is where the bottleneck of growth is in the near term. Where do we sit within those profiles, we predominantly lease our data center capacity. We're doing a little bit of self-development ourselves, but predominantly, we're, I think at 43 active sites in operation, right? It sounds that we just have like 1 or 2 sites that we're looking at that like dictate the success or failure of our business. We have 43 that we've already delivered. We know how to do this. We've done it for years. We know how to navigate the complexities in supply chain. As I'm sure everyone recalls in Q3, we disclosed that we got surprised, right, by 1 site. And we bring a lot of conservatism into our forecasting. We know how our operators work, but everyone gets hit by supply chain problems, right? Like it is just incredibly hard. So that one site, we worked closely with that operator to get it back on track. We're happy to say, as we disclosed in our earnings, that site is firmly back on track. And I think we actually delivered relative to our expectations a little bit early on that site. But we're only able to do that because we have all this experience of executing on sites. So will it remain challenging? Absolutely. Do we build a lot of conservatism already into that supply chain? Yes. But it is a -- I think going to see these sites in person is -- brings a lot of context to them.

Yes, definitely. Maybe just double-click on that. I'm not a hardware guy, but I know some hardware guys. And when memory prices are up 4x, 5x, it seems like a pretty bad day for Dell, right? It seems like a pretty bad day for HP. Is it a bad day for CoreWeave in that same way, -- like -- or are you able to -- is it too small of a part of your bill of materials? Or are you able to pass on those higher costs to your end customers?

It's a very small component of the actual node costs, right? Overwhelmingly, it's on the GPU side relative to memory. For us, I would say, we're far more focused on supply chain, right? Like ensuring that we can get the components because you're absolutely correct, like as component costs increase, that just gets passed on to the end consumer, ultimately, right? Same with like electricity costs. If electricity costs were increasing on new sites that we're entering into contracts with, that gets passed on to the end consumer. And I think the end consumer is very comfortable with like regional pricing, for example, but for us, it's entirely supply chain and ensuring we get the components to deliver the infrastructure to our clients. So going back to my example earlier on chain of thought being introduced to the models, it was Q1 of last year where we really saw that there was going to be this increasing focus on memory, right, within the LLM space. And that was driven by how close our relationship is with our clients on an engineering level, to understand what matters to them, where the technology is going. It gives us this really unique lens to understand how the demands of the market are going to evolve. And so memory was not that much of a surprise to us, right? Moving in, we see peripheral demand in general increasing. I mean I think that's only exciting for our business because those are all products that we're able to offer in to our clients to bring them more robust like full cloud experience.

Got it. And then on the other side of the equation on power, it's -- there's been a lot of concern about access to power and availability. On the most recent conference call, you guys talked about a goal of getting an incremental like 5 gigawatts of power by 2030, how comfortable are you on the ability to find that, the ability to source that is there regional difficulties? Is there global difficulties? Or are you guys pretty comfortable that, now we've got a pretty clear line of sight to being able to bring on an additional.

Yes, I think that power is out there. It's again going to be more navigating the supply chain on the data center side. But I believe our data center partners are very focused on bringing online these larger and larger deployments. I think super important for us in there is, we are only procuring that capacity as demand is there for it, right? And the way that we approach demand in our general capacity procurement in general is maintaining conversations with our largest clients, and it's more of a cadence of us asking them what they're looking for on what time frames in what regions and that informs us to go back out into the market to find the sites, whether it's 250 megs, 500 megs gig of deployment. That conversation cadence probably sits 12 to 18 months in advance. And while we won't sign an agreement with them as we're signing the contract for the data center, like we've soft-circled our clients of like, all right, this client wants 250 megs in Q3 of '27. Let's go procure that site, and then we enter negotiations for passing that site through them for billable GPU hours.

Okay. And then when you think about -- you started to build out some of your own powered shells and started to do some of that development yourself. But the majority of what you're doing is vis-a-vis your partners and having a lease against that. How are you thinking about that dynamic going forward and the balance? How important it is to own both parts of the equation? Or does the lease get most of it done or enough of it done?

So I would say the important part of it is getting access to the active power, getting -- we referred to active power is something that we can step into and start delivering infrastructure out of, right. And what we care about most is getting access to that active power on a time line that our clients want. Because from there, I think we have the best execution in the industry of delivering stabilized supercomputers once it's been given to us, right? It's measured in weeks. I think, it would -- we would probably say like 4 to 6 weeks, somewhere in there on a deployment level perspective. What will that mix be? We're already so engaged in the engineering side of these sites, right? It's not like there's just blueprints out there like, oh, here's how you go build a next-gen AI data center, right? Like we're heavily involved on the engineering side and the deployment side that we're kind of already there. And I think we really benefit from continuing to build out that internal competency of build ourselves. So we will remain opportunistic in the build versus lease approach. I think we'll have a healthy mix. I think we'll likely be bringing online some more self-development in there, especially in the context of 5 gigawatts, I think we benefit from being a strong component of that. But we're not going to offer like an explicit guidance because it will ultimately be all informed by customer demand, what the customer is looking for, and then we'll prioritize around it accordingly.

Got it. You mentioned the investor deck that you guys updated on Monday, and I would definitely tell everyone to look at it. There's a lot of really good data in that investor deck. You talked about the 25% contribution margins in a 5-year contract in months 4 through 60. I can't do that math in my head. It's probably more than that, it's more than 60. I really messed up that math. You know exactly what that 3-year through year 5 -- through 5 years.

Months 3 through 60, 25% contribution margin.

The entirety of the contract, I think you guys talked about like a 15% free cash flow margin. And that in and itself against a $67 billion backlog, super interesting. What's even more interesting is if you could continue to monetize that asset in year 6, 7 and 8. And I think that brings us back to one of the big debates around GPUs in the GPU economy is the useful life. What is the useful life of that GPU? Should we still be thinking 6 years? Should it be longer? Should it be shorter?

Six years. I think we've been very consistent about that. We're aligned with our peer set on 6 years. I think that is the absolute right number to be using for depreciation today. It's kind of funny in our analyst bring down the call after earnings. We went through 45 minutes a group call of questions about model business, et cetera. It was the first time that no one asked about useful life. And this has been a persistent question for years. So like what is useful life, and I took a little bit of a sign that I think people are really coming around understanding that 6 years useful life is the correct number to be using. And there could be a little reality that useful lives may extend beyond 6 years. And we -- the oldest infrastructure that we really have at scale from like an empirical data perspective is A100s, right? A100s are 2020 SKU. So that's putting it like right at 6 years right now. And we disclosed in earnings that in 2025, A100 pricing for us actually increased, right? It held its pricing power. H100s were within 10% of where it was at the start of the year, right? And I don't look at those as like a relative metric between each other. I look at those both as -- these are immensely strong demand signals that this older gen infrastructure, I think some portions of the market thought just went to 0 value after 2 years or something, is really not. And it's driven by this fact that there are use cases specific to the infrastructure, right? And I think, it's driven by inference, so heavily inference mean inference is just exploding and the monetization of inference, I think that very real revenue and return on revenue is being driven off of that. we're signing 5-year contracts for committed take-or-pay use on the compute. 1 year of life that would need to be extended on the end of that, I think overwhelmingly, we are seeing the empirical support. At 6 years, we would see no reason to change that in the near term, but we're quite excited about the prospect, especially from a margin perspective of useful life beyond 6 years. And I think that, that is a reality that we're about to enter for our business.

Got it. So NVIDIA has been dominating the GPU market, and the accelerator market for some time. And you guys have been very much an NVIDIA fleet there's more silicon coming into the marketplace. And there's a lot of buzz around GPUs right now. Is there any chance that we're going to see CoreWeave with other silicone anytime soon? And why or why not?

Yes. It's a question we've had for a while. And our answer has very consistently been we are client-led in what we build, right? We're not purchasing compute, building it and hoping people come and use it right? The path we take instead, which I think is a much more risk-adjusted path is -- we wait for the client to come in and say, "This is what we are looking for you to build." and this is how we enter CapEx and why our CapEx is so derisked when we enter it that way. The client, and it could be a little self-selecting just because we are so well known as an NVIDIA shop, but the client is asking only for NVIDIA, like we aren't getting requests for other types of silicon and make a mistake like we can run anything, right? We're hardware agnostic as what we operate. And I think a really good example of that is this transition we went from Hopper into Grace Blackwell. For all intents and purposes, that is different infrastructure, right? It is an entirely different way to build and deliver compute once you get into an NBL 72 configuration versus just 42U air-cooled rack. Our software just adopted right along with that, and we were first to market, bringing H100 available to clients, J200. We're first to market with GB-200s,GB-300s that's all because of this software solution that's able to operate really any type of infrastructure underneath it, but again, we just don't get demand for anything but that NVIDIA infrastructure right now. We think it's the most performing platform that's out there.

Got it. One last topic I want to hit with you. We talked a little bit about the software, the enablement software that enables you guys to run these GPUs so effectively. But you've also built out a whole another layer of software on top to expand the capabilities of what you could do. And a lot of it through acquisitions, there's Weights & Biases, OpenPipe, Monolith, Marino, how should we think about the software strategy for that layer within CoreWeave? And is it something that becomes material to the story? It's hard because you guys have built up such a backlog of the GPUs.

Yes. It's something we have a playbook that we've all seen, right? The playbook of how do you build the cloud to run the Internet and host websites store data lakes. And the first step in that playbook was get the infrastructure right, get the foundation correct, allow for people to run their workloads on you efficiently and build a purpose-built platform for the highest performance possible. And then what do they do next. They started building apps on top of it. They started adding peripherals on top of it. And I think that's the exact same cadence that you see us in right now. Like we are the best operator of GPU supercomputer on the planet. I think that is an overwhelming agreement that's with our suppliers, our clients, the broad market. Next step in that process is build app layers on top of it, add peripheral infrastructure around it. And you're seeing us go through that in real time. Absolutely correct. It's hard to say how all that scales. But I look back to our storage product, which is well north of $100 million in ARR that has that 80% attach rate with over 1 million clients, that product like came into existence out of nowhere. That scaled so quickly for us. So I think that speaks to how the velocity at which our clients are able to adopt these peripheral components, these software components that we're bringing around our core products, that's a really exciting thing for us.

Outstanding. It's been a rocket ship of the story. Congratulations on the success, and thank you for coming and sharing with us at the Morgan Stanley TMT conference.

Thank you so much. Appreciate it.