For the past few weeks, I have watched people in an investment group I belong to make very good money from two companies: CoreWeave and Nebius. They have become familiar names in the daily conversation, often mentioned alongside NVIDIA. Someone buys CoreWeave on weakness, someone else thinks Nebius still has room to run, profits get taken, positions are reopened, and inevitably somebody wishes they had held for one more day.
What began to bother me was that I wasn’t sure we understood the businesses nearly as well as we understood their share prices.
A few days before their Q2 earnings, I attended a CoreWeave recruitment event where one of the engineers made a passing remark that stayed with me. CoreWeave, he observed, was a much bigger business than Nebius, yet the market seemed to regard Nebius much more highly. I don’t know precisely what measure he had in mind, and it was an aside rather than a financial argument, but it captured a tension I had already been trying to understand: why had Nebius earned a place alongside CoreWeave so quickly, and were we even right to think of them as versions of the same thing?
Their back-to-back earnings this week gave me a good reason to find out. CoreWeave reported on Tuesday, producing $2.58 billion of quarterly revenue and ending June with $104 billion of contracted backlog. Nebius followed on Wednesday with $582.3 million of revenue, up 454 percent year over year.¹ Both were growing at extraordinary rates.
The easy conclusion was that the neocloud trade remained alive and well. AI needs extraordinary amounts of compute, CoreWeave and Nebius provide it, NVIDIA supplies the machines, and customers are still prepared to pay handsomely for access.
But the more I looked into how these two companies became important, the less satisfying that explanation became. Their real story begins with something stranger: the largest technology companies in history built some of the largest clouds in history, then discovered they still could not produce AI infrastructure quickly enough. Microsoft needed capacity outside Azure. Meta needed more than it could bring online quickly enough itself. Frontier AI labs wanted enormous clusters now rather than several years from now. The companies driving the AI boom had created demand faster than they could build the machinery required to satisfy it.
That gap created the opportunity, and CoreWeave and Nebius stepped through it from opposite directions.
CoreWeave came from an unlikely place for an AI infrastructure company. Michael Intrator, Brian Venturo and Brannin McBee came from commodities and finance. They began accumulating GPUs for Ethereum mining before finding increasingly valuable uses for those machines in rendering, machine learning and eventually AI. By the time CoreWeave listed on Nasdaq on 28 March 2025, the crypto operation had become one of the fastest-growing infrastructure companies of the AI era.²
Their background matters because CoreWeave’s early advantage was never simply that it owned GPUs. Intrator has spoken about the company’s financial DNA, and that heritage is visible in the business they built: acquiring scarce equipment, financing enormous deployments and securing long-term customer commitments against the infrastructure. When GPUs suddenly became strategic assets, CoreWeave already knew how to treat scarcity as a market. Its $104 billion backlog is evidence of how effectively it has done that, rather than the source of the advantage itself.¹
Nebius arrived from almost the opposite direction. For anyone unfamiliar with Yandex, the easiest mental model is Russia’s answer to Google. Arkady Volozh co-founded a search company that grew into maps, cloud computing, machine learning, ecommerce and autonomous vehicles. Russia’s invasion of Ukraine eventually led to the separation and sale of Yandex’s Russian businesses. The Amsterdam-based parent was rebuilt as Nebius Group and, having originally traded as Yandex on Nasdaq from 2011, returned to the market as NBIS on 21 October 2024.³
The separation left Volozh with something unusual: Nebius was a new company without having to begin like a startup. It inherited an experienced engineering organisation, billions of dollars to deploy, public-market access and years of knowledge accumulated from building large distributed systems. But good engineers alone do not explain why Nebius suddenly mattered. The turning point was Microsoft.
In September 2025, Microsoft agreed to buy $17.4 billion of AI infrastructure services from Nebius over five years, with additional capacity capable of taking the commitment to roughly $19.4 billion.⁴ Microsoft already operated one of the largest clouds on Earth, yet its need for AI capacity was sufficient to make an enormous commitment to a company that had existed under its new name for less than a year.
The money was important, but the customer was more important. Microsoft effectively answered the question hanging over Nebius: could this rebuilt company operate AI infrastructure at the scale demanded by one of the world’s most sophisticated technology organisations? Meta later provided another large validation.
That, I think, explains how Nebius earned a place alongside CoreWeave so quickly. It did not simply reproduce CoreWeave’s playbook. Volozh began with an unusually mature engineering organisation and then compressed years of credibility-building by winning customers whose own technological sophistication validated the platform.
The two companies had found different ways into the same shortage. CoreWeave was unusually good at capitalising scarcity; Nebius was unusually good at engineering complexity and turning it into hyperscaler trust. For a while, those were exceptionally valuable places to be.
Then, two days before CoreWeave reported earnings, NVIDIA made an announcement that changed the meaning of one of those advantages.
On 10 August, NVIDIA brought Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR together around independent financing platforms intended to mobilise more than $500 billion of third-party capital for AI infrastructure. NVIDIA described the ambition explicitly: turn NVIDIA compute and full-stack AI infrastructure into an investable asset class for global capital.⁵
The obvious reading is bullish: more money means more AI factories can be built. For CoreWeave, however, there is another implication. Part of its unusual capability was learning how to finance a strange new asset before traditional capital markets properly understood it. CoreWeave knew how to combine GPUs, large customer commitments and future cash flows into infrastructure that lenders were prepared to fund. NVIDIA is now helping make that playbook institutional.
That does not erase CoreWeave’s advantage. Financing is only one part of its capability, and years of operating experience cannot be recreated by signing an agreement with a private-credit fund. But if enormous pools of capital become comfortable financing AI infrastructure, one part of what made CoreWeave unusual becomes easier for other companies to reproduce.
Seen from that perspective, one of CoreWeave’s quieter moves becomes more interesting. SUNK Anywhere extends CoreWeave’s operating technology beyond infrastructure CoreWeave itself owns.⁶ The significance is not that CoreWeave has suddenly become a software company; it hasn’t. The interesting possibility is that the expertise it accumulated running enormous AI systems could begin generating value on machines somebody else financed. If that happens, part of CoreWeave’s value begins escaping its balance sheet.
Nebius is approaching the same changing market from another direction. Its infrastructure buildout remains enormous, but Volozh is building above it at the same time. Token Factory moves Nebius into inference, while its asset-light model allows outside investors to finance more of the physical infrastructure while Nebius retains more of the architecture, operating platform and customer relationship.
Its latest results offer a glimpse of what that could become. Nebius AI Cloud revenue reached $575 million in Q2, ARR reached $3 billion, and the company expects more than $9 billion in customer prepayments during 2026.¹ The important point is not any individual number. It is that Volozh appears to be assembling more than a collection of GPU clusters. Large customers can anchor the infrastructure underneath while Nebius builds services and customer relationships above it. That remains an ambition rather than a completed transformation.
Then SpaceX made the changing market much harder to ignore.
SpaceX built its enormous Colossus infrastructure around xAI’s own ambitions, but it has since discovered that the same machines are exceptionally valuable to companies competing in the AI race. Anthropic agreed to pay SpaceX $1.25 billion per month for compute capacity across Colossus and Colossus II. Google then agreed to pay $920 million per month from October 2026 through June 2029 for access to roughly 110,000 NVIDIA GPUs and associated infrastructure.⁷
At their stated full monthly rates, those two agreements represent about $26 billion a year. That is the number that changes the scene, because SpaceX did not spend years trying to become another cloud provider. It built enormous computing capacity because xAI needed it, then discovered that Anthropic and Google would pay extraordinary amounts to use it too.
The relationships are even more revealing than the revenue. Anthropic competes with xAI at the model layer while buying infrastructure from the same corporate group that develops Grok. Google designs its own TPUs and operates one of the world’s largest clouds, yet it is still willing to rent enormous amounts of NVIDIA capacity from SpaceX when it needs more compute quickly.
Meta may be moving in the same direction. It is developing plans to sell excess AI computing capacity externally and has held early discussions about leasing compute to Anthropic in a potential deal worth as much as $10 billion over two years.⁸ These plans may change, and the Anthropic discussions may never produce a deal, but the direction is notable.
None of that proves SpaceX or Meta will eclipse CoreWeave and Nebius. What it demonstrates is more interesting: the line between an AI infrastructure customer and an AI infrastructure supplier is beginning to blur.
A company can build compute for itself, buy additional capacity elsewhere when it is short, and sell capacity when somebody else values it more highly. At that point, the market begins to look less like the public cloud we know and more like an industrial capacity market.
The electricity analogy is useful here. A large participant can be both producer and consumer. Capacity can be contracted years ahead or sold when somebody urgently needs it. The company owning the generating asset does not necessarily capture all the value around it. If AI compute continues moving in that direction, SpaceX does not have to become the next AWS to matter to CoreWeave or Nebius. It only has to prove that large captive AI estates can become merchant supply when the economics make sense.
At roughly $26 billion of annualised revenue from the disclosed Anthropic and Google agreements alone, that possibility is no longer theoretical.
The shortage that created CoreWeave and elevated Nebius has not disappeared; their latest results tell us precisely the opposite. What is changing is how many organisations are learning how to supply it. NVIDIA is attempting to make infrastructure financing easier, SpaceX has already turned captive compute into a multibillion-dollar external business, and Meta is exploring a similar direction.
This is also why the fact that CoreWeave and Nebius are positioning around physical AI deserves attention, although their motives should not be invented for them. Physical AI is easier to understand if we look at how the work we give AI has been changing.
The first generative-AI wave mostly answered: we asked a model a question and it produced a response. Agentic AI changed the unit of work from answering to doing: give an agent one objective and it can perform many searches, model calls, tool uses and decisions before returning with the result.
Physical AI puts that intelligence into an unpredictable world. A warehouse robot cannot be programmed for every object, obstruction or unexpected event it will encounter, nor can we teach it every lesson by allowing it to fail repeatedly in a real warehouse. Much of that learning can therefore move into simulation.
This is where world models become easier to grasp. Think of them as flight simulators for machines: before a robot encounters one difficult situation in reality, it can experience enormous numbers of variations of that situation virtually.
The progression is simple: generative AI answers; agentic AI does; physical AI gives that intelligence eyes, a body and a world in which to operate.
Physical AI does not automatically make every workload larger than every agentic workload. What it can create is another large class of computational work: simulation, synthetic environments, training, perception and repeated learning from experience. Nebius, for example, explicitly describes large-scale simulation, synthetic data and accelerated compute as core requirements for physical AI and is building its Physical AI Living Lab with NVIDIA around those workloads.⁹
For investors watching the next three months, however, physical AI matters less as a prediction about robots than as one possible source of demand for everything now being built. On one side, NVIDIA, institutional capital, SpaceX and potentially Meta are expanding our ability to supply AI compute. On the other, agents and potentially physical AI are expanding the ways we can consume it.
The question is which side moves faster.
That is what I would carry into the next CoreWeave and Nebius earnings calls. I am not primarily interested in whether they sell more compute; their latest earnings have already shown us that demand remains extraordinary. I want to know whether our ability to manufacture AI capacity is beginning to catch up with our ability to find valuable uses for it.
If customers continue competing aggressively for new capacity even as more providers and more capital enter the market, CoreWeave and Nebius remain close to one of the defining constraints of the AI boom. If those scarcity economics begin weakening, the question changes. CoreWeave then has to prove that what it learned operating the machines is valuable even when somebody else owns them. Nebius has to prove that what it is building above the machines becomes valuable enough that raw capacity is merely the foundation.
Those are not facts about their futures. They are the hypotheses their current strategies invite us to test.
I began looking at CoreWeave and Nebius because people around me were making money from two AI infrastructure stocks. I found two companies that became important because the largest technology companies in the world could not build something quickly enough. CoreWeave exploited that opening through an extraordinary financing and operating capability. Nebius arrived later but used inherited engineering depth and hyperscaler validation to establish itself remarkably quickly.
Their Q2 earnings tell us that the opening remains enormously valuable. Everything happening around them tells us that more people have now seen it.
The shortage has not disappeared. The ability to solve it is spreading.
That is why the next three months are not primarily a test of whether AI demand remains strong. They are a test of whether CoreWeave and Nebius can move their advantage somewhere competitors cannot easily follow.
The first winners of the AI infrastructure boom supplied something everybody desperately needed and very few could provide. The next winners have to answer a harder question:
What do you still own when the thing that made you special is no longer scarce?
Sources
1. CoreWeave and Nebius, Q2 2026 results
CoreWeave, Second Quarter 2026 Results
https://investors.coreweave.com/news/news-details/2026/CoreWeave-Reports-Strong-Second-Quarter-2026-Results/default.aspx
Nebius Group, Q2 2026 Shareholder Letter
https://assets.nebius.com/assets/a6ecfd85-a6cb-4967-8ef7-9a25bd261f9c/SHLQ226.pdf
2. CoreWeave history and Nasdaq listing
CoreWeave Investor Relations
https://investors.coreweave.com/
3. Yandex separation and the creation of Nebius
Nebius Investor Hub
https://nebius.com/investor-hub
4. Microsoft and Nebius
Nebius SEC filing covering Microsoft’s $17.4 billion commitment and additional capacity potentially taking the agreement to approximately $19.4 billion.
https://www.sec.gov/Archives/edgar/data/1513845/000110465925088312/tm2525580d1_6k.htm
5. NVIDIA’s $500 billion AI infrastructure financing initiative
6. CoreWeave SUNK Anywhere
7. SpaceX compute agreements with Anthropic and Google
Reuters, Anthropic agrees to pay SpaceX $1.25 billion monthly for compute
https://www.reuters.com/business/anthropic-nears-first-quarterly-profit-agrees-pay-spacex-125-billion-monthly-2026-05-21/
Reuters, SpaceX lands Google AI compute deal after Anthropic pact
https://www.reuters.com/business/media-telecom/spacex-signs-cloud-deal-with-google-2026-06-05/
8. Meta’s emerging external compute business
Reuters, Meta building cloud business to sell excess AI capacity
https://www.reuters.com/business/meta-sell-excess-ai-computing-capacity-via-cloud-business-bloomberg-news-reports-2026-07-01/
Reuters, Meta, Anthropic in talks for potential $10 billion compute lease deal
https://www.reuters.com/technology/meta-talks-10-billion-anthropic-compute-deal-nyt-reports-2026-07-17/
9. Nebius and physical AI
Nebius, Physical AI Living Lab
https://nebius.com/newsroom/nebius-launches-physical-ai-living-lab-for-uk-and-european-robotics-startups-built-with-nvidia-technologies