Why Nvidia’s Favorite Cloud Startup Got $7.5 Billion From Blackstone, Others
OpenAI and its artificial intelligence rivals get all the headlines, but few venture-backed companies have benefited more from the AI boom than CoreWeave, a cloud provider. That's thanks to Nvidia, which allocated some of its precious AI server chips to CoreWeave rather than large clouds like Amazon Web Services, prompting startups and even Microsoft to collectively commit to spending billions of dollars to rent CoreWeave’s servers.
On Friday, CoreWeave said it raised $7.5 billion of debt from private equity giant Blackstone and others to buy more chips and expand its U.S. data centers. CoreWeave co-founder Brannin McBee, who's based in Montana and handles the company’s capital raises, said it hopes to roughly double its data center footprint this year to around 300 megawatts of capacity.
The Takeaway
• CoreWeave says large enterprises now make up most of its revenue
• CoreWeave’s valuation rose to $19 billion in a financing this spring
• The cloud provider could raise even more debt this year
Cloud providers seldom share such data, but CoreWeave’s disclosure implies its facilities could potentially run a few hundred thousand Nvidia H100 graphics processing units, according to someone with knowledge of GPU power requirements. While CoreWeave’s capacity is tiny compared to AWS or Microsoft Azure, the startup’s projected growth could put it within striking distance of Oracle when it comes to GPU cloud sales.
As a younger cloud entrant, McBee said CoreWeave has designed its GPU server clusters from the ground up, which gives it an advantage over AWS and others that have focused on traditional computing tasks such as hosting websites. “It's sort of like walking into Ford and asking them to produce a [Tesla] Model Y,” he said of AWS and others. (AWS didn't comment on the remark but said last month that its cloud sales accelerated in the first quarter, in part due to generative AI computing.)
The debt deal came just weeks after CoreWeave raised more than $1 billion in equity financing at a $19 billion valuation—up from $2 billion in a funding round a few months after ChatGPT launched and spiked demand for GPUs. CoreWeave's stock has been so hot that six months ago, early shareholders and employees sold $642 million worth of shares to new buyers—an almost unheard of sum for such a young business. The company, which previously catered to crypto miners, is based in New Jersey and employs 550 people.
While the jury is still out on how conversational AI startups will make money, cloud providers' path to revenue and profits is well established. In June last year, CoreWeave told investors that it expected to generate more than $500 million in revenue in 2023, up from about $25 million in 2022, and it projected $2.3 billion in 2024 revenue. (It based most of that projection on contractual commitments from customers.) A CoreWeave spokesperson said the company has been “profitable since day one,” without elaborating.
It isn’t clear what CoreWeave is using as collateral for its new loan—a company spokesperson declined to comment about that. GPU cloud providers have been increasingly borrowing against their GPU servers, which an investor previously called a “new asset class.” There’s risk in doing so, of course, as prices for the GPUs might fall over time as supply rises. And CoreWeave may feel pressure to keep up with the immense capital expenditures its larger rivals are planning.
In an interview, McBee said another debt deal could happen this year and talked about how CoreWeave got ahead of power constraints for data centers, why he believes the company is better than AWS at running GPUs, and how demand for its GPU servers has shifted to large enterprises.
This interview has been edited for length and clarity.
The Information: What does this funding announcement signify?
McBee: The scale at which we’re operating, especially relative to our peers—Amazon, Google, Microsoft, Oracle—this [round is] what brings us into that hyperscaler status. I think the differentiation is that we're an AI hyperscaler [in the same category as the world's biggest cloud providers]. That is evidenced not only by that skill of operation, but who our counterparties are. Our investors, our creditors, or our clients, or suppliers. All these pieces are required to position yourself as a hyperscaler. And that's what you're seeing come into place.
What are you going to spend the money on?
Just as you would expect, this is all going to support infrastructure builds. The [$1 billion] Series C round [of equity financing], that's more like continuing to bring world-class engineering talent into the business, supporting research…and also just to bring in tier one technology investors. [The debt round] is to support demand for our product.
What are the biggest bottlenecks around expanding your GPU capacity?
A lot of it is on the power side. It's something that we've fortunately gotten way ahead of. We started securing the capacity we need to execute on our growth plans beginning in Q1 of last year. I have all the data center capacity I need to hit my 2025 [revenue goal]. I would not be able to secure that data center capacity today if I tried to. It's just simply not there.
[Power] is the bottleneck for the broader market right now. And it's one of our most coveted strategic assets. We were able to identify this impending issue in the market and go out and secure the data center capacity that was needed to hit our growth profile.
How many megawatts of data center capacity do you plan to have by the end of 2024, if you expand to your goal of 28 data centers?
Over 300 megawatts.
And next year?
We have the power, we have the data center space secured. It's well in excess of double that amount [of wattage].
I keep hearing that Nvidia's H100 chips perform differently in different clouds. Why do you claim H100s perform better on CoreWeave than, say, Amazon Web Services?
The difference is the engineering solution that delivers that H100 to the client. In other words, it's really the software.
We built our entire software solution around supporting this AI infrastructure, whereas our competition built their software solution around hosting websites and storing data lakes. And it's a very different outcome.
It's sort of like walking into Ford and asking them to produce a [Tesla] Model Y. They can't produce a Model Y because it's a different mechanism to produce those vehicles. So they produce some other electric vehicle that looks like a Model Y, but it is still very different and it has a different performance level. It's not that our competition can't produce something with four wheels on it that's it's electric.
And if you take the analogy a bit further, you couldn't go into Ford and say, “Just turn one of your manufacturing facilities into a Model Y facility,” right? It's the whole supply chain, the whole business. That's the same challenge that our competition faces. They can't just turn one data center into how CoreWeave does it. It's a comprehensive product that we have built from a no-engineering-compromises stance.
Editor’s note: In a recent blog post, Brian Venturo, CoreWeave’s chief strategy officer, said software was CoreWeave’s “secret weapon” to maximize the performance of GPU servers, including by regularly checking their “health” and allowing customers to quickly spin-up servers and automatically increase the number of servers they use. CoreWeave also uses Nvidia’s Infiniband networking cables to stitch together its GPU servers, whereas other cloud providers use their own homegrown networking or are moving in that direction.
Where's demand coming from?
Last year, 90% of our workloads were for training [new AI models], and our pipeline was primarily AI startups and revenue was predominantly AI startups. Today, I'd say 70% is training [models] this year as we move toward inference [running AI models to handle customer queries], and our revenue is dominated by enterprise and our pipeline is dominated by enterprise. I think that's just a function of your typical technology adoption curve profile. Early adopters are going to be startups, and what we're observing is enterprises moving into the space. It's Fortune 500, Fortune 100 companies, it's technology, it's finance. It's increasingly becoming synthetic biology [firms].
Why do you think CoreWeave has been able to raise so much money, relative to its competitors?
The capital is aggregating to us because of our product differentiation. If a GPU was a GPU across the whole GPU startup space, everyone would be getting this volume.
But they're not. And I think that's a little bit of a testament to not only our product, but who our clients are, and our ability to navigate the financial markets. It is not easy to sit down at the table with the types of counterparties we are working with. They're extremely sophisticated. They are world-class investors. Being able to close transactions of this size, it speaks to who we are as a business.
Are you expecting there to be consolidation in the GPU cloud sector?
I wouldn't say that we have any specific plans for M&A consolidation with the GPU cloud space. There's always opportunities within the software side [for acquisitions], I would say.
Editor’s note: Nvidia has made several such software acquisitions this year, including Run:ai. Those acquisitions could boost the efficiency of Nvidia’s own GPU cloud server rental service, which runs in data centers operated by AWS and other large clouds.
How's the relationship with Nvidia going?
They're a phenomenal supplier. They have a great product and market. [Customers] are all asking for Nvidia; no one's asking for anything else. And this is inclusive of like one- to two-year forward-looking plans. We continue to appreciate the relationship we have there and love being able to bring their infrastructure to consumers.
When will you get Nvidia's new chip, the GB200?
There's immense demand for GB200. We would expect to have availability in early 2025.