TL;DR · 30-second read
The Short Version
Two companies that rent out powerful computers for artificial intelligence recently borrowed money, and one is paying far more for it.
CoreWeave took a $2.6 billion loan that costs 5.5 percentage points above a standard benchmark interest rate. Its rival Nebius borrowed $775 million at just 2.5 points above that same benchmark.
The difference comes down to what backs each loan. Nebius tied its loan to one financially strong customer’s contract, while CoreWeave’s covers many customers. If demand for artificial intelligence cools, cheaper borrowing could become a real advantage.
Dealroom reported that CoreWeave closed a $2.6 billion delayed-draw term loan in August, priced at Term SOFR plus 5.50% and maturing in September 2031, with $1.2 billion drawn so far. That margin is three percentage points above the SOFR plus 2.50% Nebius Group secured on a $775 million facility in July. Nebius has described that facility as backed by deployed GPU infrastructure and cash flows from an investment-grade customer.
Separately, Nebius closed $5.75 billion of convertible notes in August. In a Form 6-K filed September 8, it announced that Palantir had named it a preferred sovereign AI infrastructure partner.
Executive Summary
Two of the best-known neoclouds, the specialist providers that rent GPU computing for artificial intelligence, have borrowed against their buildouts within weeks of each other on very different terms. CoreWeave’s $2.6 billion facility carries a 5.50% margin over the Secured Overnight Financing Rate (SOFR), the US benchmark for floating-rate loans. Nebius’s smaller $775 million facility carries 2.50%.
The gap does not show lenders favoring one company’s AI prospects over the other’s. It shows lenders pricing the specific collateral and customer contracts behind each loan. Nebius’s loan sits on a single contracted deployment with an investment-grade customer, meaning one with a strong credit rating. CoreWeave’s loan finances committed deployments across a broader customer pool and gives the company more flexibility, and it pays more for that flexibility.
This matters beyond the two companies. AI infrastructure is being built largely with borrowed money. When credit markets start pricing each buildout on its own contracts and collateral, the cost of capital becomes a competitive variable, and it could separate winners from strugglers if GPU rental prices or utilisation weaken.
Same Industry, Very Different Price of Money
Floating-rate corporate loans charge a benchmark rate plus a fixed margin, or spread. The benchmark here is SOFR, which tracks the cost of overnight borrowing secured by US Treasuries. Because both CoreWeave and Nebius pay SOFR, the spread is the part that reflects how lenders view the risk. CoreWeave’s 5.50% is 2.2 times Nebius’s 2.50%, a gap of three percentage points. Describing it as ‘triple’ is loose shorthand. Once the shared benchmark is added back, the difference in all-in borrowing cost is proportionally smaller, though still substantial.
The structure also matters. A delayed-draw term loan lets the borrower tap committed funds in stages as spending arrives, which suits GPU deployments that come online in phases. CoreWeave has drawn $1.2 billion of its $2.6 billion. As simple arithmetic before fees, three extra percentage points on the drawn balance comes to roughly $36 million a year. On the full facility it would be roughly $78 million a year.
Collateral and Contracts, Not Confidence, Set the Spread
Nebius’s facility resembles project finance. It is secured by hardware already deployed and by cash flows from an investment-grade customer, and Nebius said it covers more than 100% of that deployment’s capital expenditure. Lenders are underwriting a known asset with a known payer, which is why the margin is low. The model works best if Nebius can repeat it, and the company points to more than $40 billion of additional customer commitments as the pipeline for doing so.
CoreWeave’s loan spreads risk across a broader set of committed deployments and runs to September 2031. That breadth gives CoreWeave room to serve shorter contracts and higher-margin enterprise work that a single-customer structure would not accommodate. The trade-off is a higher hurdle rate, the minimum return each financed GPU must earn before it adds value for shareholders. Neither structure is inherently better. One buys cheap money through narrow contracts, and the other pays for flexibility.
Capital Hunger on Both Sides of the Comparison
Neither company is borrowing from a position of surplus. Nebius’s $5.75 billion convertible note sale in August dwarfs its $775 million facility. Convertible notes are debt that investors can later swap for shares, so they carry potential dilution. Nebius is also adding demand-side relationships. Its September 8 filing describes Palantir naming Nebius its preferred sovereign AI infrastructure partner and the two working to deploy new capacity, including modular data centers at sites where power is already available. That filing disclosed no financial terms, contracted capacity or timeline.
Investor positioning is mixed. CoreWeave’s hedge fund holder count rose to 71 in the second quarter of 2026 from 63, even as Magnetar Capital trimmed its stake 24% to 52,062,927 shares. Nebius’s count rose to 86 from 60, while Orbis Investment Management cut 22% to 6,494,719 shares. On August 31, 17.89% of Nebius’s float was sold short. With billions of convertible debt outstanding, part of that short interest likely comes from convertible holders hedging their positions rather than outright bets against the company.
Why the Pricing Gap Could Matter More If Demand Cools
While AI compute is scarce and rental prices hold, a three-point spread difference is easily absorbed. The risk appears when utilisation or pricing slips, a concern that resurfaced after September 14. Expensive debt then consumes a larger share of revenue, and strong top-line growth can coexist with weak returns to shareholders.
The likely beneficiaries are providers that can attach financing to long contracts with highly rated customers, and the lenders who have learned to tell those deals apart. Providers relying on broader, flexible facilities are not disadvantaged today, but they carry more exposure to a downturn. If lenders keep pricing buildouts deal by deal, a lower cost of capital becomes a durable advantage that is hard for rivals to copy quickly.
Background
CoreWeave and Nebius are leading examples of neoclouds, companies that build and rent out GPU computing capacity for training and running artificial intelligence models. CoreWeave, which listed on Nasdaq in 2025, is US-based. Nebius Group, listed on Nasdaq as NBIS and headquartered in Amsterdam, is led by founder and CEO Arkady Volozh and was formed from the international businesses of the former Yandex N.V.
Both companies need large amounts of capital, because GPUs, power and data center space must be paid for well before customers’ rental payments arrive. That has made debt markets central to the sector, and lenders have increasingly looked at the specific contracts and collateral behind each deal rather than lending against the AI growth story as a whole. Source: CoreWeave draws $2.6B AI loan at SOFR +5.5%, triple Nebius’s rate (Dealroom), comparing CoreWeave’s August term loan with Nebius’s July facility. Primary sources: Nebius Group N.V. Form 6-K filed 2026-09-08; Exhibit 99.1 to 6-K filed 2026-09-08: Palantir and Nebius partner to deliver a complete sovereign AI stack to Palantir customers.Sources