AI companies rarely pay for GPUs and data centers with one source of money. They assemble a capital stack: operating cash flow, common or preferred equity, equity-linked securities, bonds, term loans, revolving facilities, GPU-backed loans, leases and customer commitments. The mix determines who bears risk, how quickly capacity can be deployed, whether existing owners are diluted and how much cash must be paid every month.
The central distinction is between funding that absorbs losses (equity), funding that requires scheduled repayment (debt), contracts that create fixed obligations without immediate ownership (leases), and customer commitments that make future infrastructure revenue more predictable. Large operators often combine all four.
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What an AI infrastructure capital stack contains
Compute infrastructure is unusually capital-intensive. A provider may need to reserve power, fit out a facility, buy thousands of accelerators and networking systems, and keep enough working capital for electricity and operations before customers pay. Because those assets have different useful lives and resale values, financing is layered rather than uniform.
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- Operating cash flow: money generated by an existing cloud, software or services business. It has no interest cost or dilution, but young AI companies often do not generate enough recurring cash to fund expansion.
- Equity: common shares, preferred shares, strategic investments, IPO proceeds and mandatory convertibles. Equity has no scheduled principal repayment, but it dilutes existing owners and can pressure valuation.
- Corporate debt: senior bonds, term loans and revolving credit. This can be unsecured for a highly rated issuer or secured by assets and contracts for an infrastructure-focused borrower.
- Asset-backed facilities: loans whose availability is tied to equipment value, contracted revenue or both. GPU-focused facilities commonly limit borrowing to a percentage or depreciable cost of eligible servers.
- Leases: contracts for buildings, power capacity or equipment. Leasing reduces the cash needed at deployment, while creating fixed payments and less residual ownership.
- Customer-backed commitments: multi-year, often take-or-pay contracts that support borrowing because lenders can underwrite expected cash flows.
The appropriate mix depends on asset life, collateral value, customer credit, interest rates, credit rating, construction timing and how much dilution founders and investors will accept.
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Operating cash flow: the cheapest source, when it exists
Cash generated by an established business can fund a portion of GPU purchases, facility deposits and construction. It avoids underwriting fees, covenants and dilution. It also gives management flexibility to slow or redirect spending if demand changes.
That source is limited for early-stage model developers and newly formed compute providers. Training and inference demand can require billions in equipment before revenue becomes recurring or profitable. Even profitable software companies may reserve operating cash for payroll, research and acquisitions, leaving infrastructure expansion to external capital.
When internal cash is used, analysts should distinguish cash flow from operations from proceeds of a financing transaction. A company may report a large cash balance after issuing shares or borrowing while still consuming cash in its operating business.
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Common and preferred stock
Common equity absorbs losses before creditors and has no maturity date. Preferred equity can add liquidation preferences, dividends or conversion rights. Both forms increase the company’s permanent capital, but new issuance reduces existing owners’ percentage ownership unless the value of the business grows enough to offset dilution.
Private companies may raise strategic equity from customers, technology partners or sovereign investors. Public companies can sell shares through an IPO, follow-on offering or at-the-market program. The trade-off is clearest when a company’s valuation is volatile: issuing stock after a price decline requires more shares for the same amount of cash.
Equity-linked securities
Mandatory convertible preferred securities begin as preferred instruments and convert into common stock under specified terms. They can defer immediate dilution or reduce the cash coupon compared with straight debt, but conversion ultimately expands the share count. An at-the-market program sells smaller amounts of common stock over time, providing flexibility but exposing the issuer to its prevailing market price.
Oracle’s February 1, 2026 expansion plan illustrates a balanced approach. It targeted gross proceeds of $45 billion to $50 billion, with approximately half from equity-linked or common equity and half from senior unsecured bonds. The plan included mandatory convertible preferred securities and an at-the-market program of up to $20 billion. Those were announced plans and forward-looking targets, not proof that every dollar had already been raised or spent.
Corporate bonds, term loans and revolving credit
Senior bonds
Investment-grade issuers can sell senior unsecured notes to a broad bond market. They pledge the company’s general credit rather than a particular GPU fleet, so proceeds can be used across construction, equipment and working capital. The cost is a fixed or floating coupon, maturity dates and restrictions in the bond documents. A downgrade can raise the cost of future borrowing even when existing fixed-rate notes remain unchanged.
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Term loans
Term loans provide a committed principal amount that is drawn at closing or in stages and repaid on a schedule or at maturity. Infrastructure borrowers may pledge subsidiaries, equipment, contracts or cash accounts. A loan can be repaid early with a refinancing or equity proceeds, but transaction fees and prepayment terms affect the economics.
CoreWeave’s filings provide issuer-specific examples: a $1.0 billion term loan raised in 2024 was repaid with IPO proceeds, and the company issued $2.0 billion of senior notes due in 2030. These transactions show how a provider can refinance short- or medium-term borrowing after accessing public equity markets; they do not establish terms for every AI company.
Revolving facilities
A revolving credit line lets a borrower draw, repay and redraw within a commitment. It is useful for equipment deposits, seasonal power bills and construction overruns because interest is generally charged only on amounts drawn. Lenders still impose borrowing-base tests, financial covenants, commitment fees and limits on additional debt.
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Asset-backed lenders advance against identifiable collateral rather than relying solely on a company’s overall valuation. For AI infrastructure, collateral can include GPU servers, networking equipment, data-center assets, subsidiary equity and the cash flows from contracted customers.
Delayed-draw term loans (DDTLs) are particularly suited to deployment in stages. A borrower signs a facility, then draws portions as sites are built and servers are delivered. Availability can be constrained by the depreciable cost of eligible GPU servers, with required collateral, maintenance tests and periodic amortization. If equipment is sold, replaced or falls outside eligibility rules, borrowing capacity can shrink.
CoreWeave’s July 2025 DDTL 3.0 facility offered up to $2.6 billion. Its stated pricing was daily compounded SOFR plus 4.00%, or an alternative base rate plus 3.00%. Proceeds were intended to support equipment and infrastructure for OpenAI services. The spread and reference rate are specific to that facility; they should not be treated as a market-wide quote.
Floating-rate debt transfers interest-rate risk to the borrower. A higher SOFR increases cash interest even if GPU utilization and customer pricing are unchanged. Lenders may also require restricted cash, minimum liquidity, insurance and limits on dividends or additional liens.
Leases: deploying capacity while taking on fixed payments
A company can lease a data-center building, powered shell, electrical capacity or equipment rather than buying the asset. The lessor supplies capital and retains residual ownership; the AI operator pays rent over an agreed term. Leasing can shorten deployment time and preserve cash for GPUs, but it creates contractual obligations that continue during weak utilization.
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Operating leases versus finance leases
An operating lease is economically similar to renting: the lessee uses the asset without obtaining most ownership risks and rewards. A finance lease is closer to borrowing to buy an asset, with interest and depreciation patterns. Modern accounting standards generally put both types on the balance sheet, but they appear in different liability and expense categories.
CoreWeave states that it leases all of its data centers and certain equipment, including arrangements accounted for as operating leases. At December 31, 2024, it reported $2.602 billion of operating-lease liabilities and $91.921 million of finance-lease liabilities. It also disclosed $15.0 billion of additional future undiscounted payments for leases that had not yet commenced. Those future leases were expected to begin between 2025 and 2026 and had estimated terms of five to sixteen years.
Readers should not add an uncommenced lease commitment to current debt or assume the full undiscounted amount equals present value. The timing, discount rate, commencement date and accounting classification determine the liability recorded today.
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Infrastructure lenders are more comfortable when a provider can show a signed, creditworthy customer commitment. Take-or-pay language requires payment for a reserved amount of capacity even if the customer’s actual usage is lower, subject to the contract’s conditions. A multi-year agreement can therefore support debt service, equipment purchases and lease payments.
The common sequence is:
- The provider signs a contract specifying capacity, term, pricing, delivery milestones and payment obligations.
- It assigns or pledges eligible contract cash flows, directly or through a subsidiary, to a lender.
- The lender approves a facility sized against contracted revenue, equipment cost and collateral requirements.
- The provider draws funds as customer requirements are built, rather than borrowing the entire amount on day one.
- Customer receipts service interest, amortization and operating costs; excess cash may be swept or released under the loan agreement.
CoreWeave reported $15.1 billion of remaining performance obligations at December 31, 2024 and said take-or-pay commitments support predictable cash flows used in financing. Remaining performance obligations are not the same as cash already collected: delivery, cancellation, customer credit and future spending still matter.
Customer-backed financing also creates concentration risk. If one customer delays deployment, renegotiates pricing or suffers financial distress, the provider may have debt sized to equipment that cannot be redeployed immediately.
Joint ventures and special-purpose project companies
Very large campuses can be financed through a joint venture or special-purpose vehicle (SPV). Equity investors contribute risk capital, while banks or private-credit funds lend to the project company. The SPV may own the land, power equipment and buildings, sign customer contracts and limit recourse to its sponsors.
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An Axios report in 2025 described Stargate as a planned $500 billion U.S. AI-infrastructure investment, with an initial $100 billion and a portion expected to come from third-party debt. SoftBank, OpenAI, Oracle and MGX were identified as equity participants. Those figures describe a reported project plan, not audited funding or completed construction.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How the financing choices compare
| Instrument | Upfront cash need | Owner dilution | Repayment and rate exposure | Collateral or covenant burden | Best fit |
|---|---|---|---|---|---|
| Operating cash flow | Uses cash already generated | None | No financing repayment | Operational constraints rather than lender covenants | Incremental purchases by an established, cash-generating business |
| Common equity | Low transaction funding friction once markets are open | Highest direct dilution | No scheduled principal | Investor and disclosure requirements | Early-stage growth or projects with uncertain utilization |
| Preferred or mandatory convertible equity | Raises substantial capital without straight-debt maturity | Potential or eventual dilution; may include preferences | May include dividends or conversion terms | Security-specific protective provisions | Large expansion when debt capacity is limited |
| Senior unsecured bonds | Large single issuance | None at issuance | Coupon and refinancing at maturity | Primarily issuer-level covenants; depends on rating | Scaled issuers with diversified cash flow and market access |
| Secured term loan or DDTL | Drawn in stages or at closing | None | Floating or fixed interest plus amortization | Liens, borrowing-base tests, restricted cash and financial covenants | Equipment and contracts that can be pledged |
| Operating lease | Lower initial purchase outlay | None | Fixed rent over the lease term | Lease covenants and termination obligations | Buildings, power capacity and equipment needed quickly |
| Finance lease | Spreads purchase cost over time | None | Principal-like and interest-like payments | Asset-specific rights and restrictions | Equipment likely to be used for most of its economic life |
| Customer-backed or project finance | Draws aligned with deployment milestones | Depends on sponsor equity | Debt service depends on contract receipts | Contract assignment, reserves, completion tests and customer concentration | Facilities with long-term, creditworthy demand |
Scale examples and what the numbers do—and do not—mean
| Company or project | Reported figure | Interpretation |
|---|---|---|
| CoreWeave, 2024 | $12.9 billion of debt commitments | Total commitments are not identical to amounts drawn or outstanding. |
| CoreWeave, 2024 | 32 data centers, more than 250,000 GPUs, over 360 MW of active power and approximately 1.3 GW of contracted power | Shows the scale of assets and contracted capacity underpinning financing discussions. |
| CoreWeave, 2025 | More than $25 billion raised through equity financing and debt capital commitments | Combines equity financing with debt commitments; it is not a measure of cash spent. |
| CoreWeave, 2025 | Up to $2.6 billion under DDTL 3.0 | A facility maximum; actual draws depend on eligibility and deployment. |
| Oracle, 2026 | $45 billion–$50 billion planned gross proceeds | A forward-looking OCI expansion target using a balanced debt-and-equity approach. |
| Stargate, 2025 report | $500 billion planned investment, including an initial $100 billion | A reported plan involving expected third-party debt, not completed or audited funding. |
Risks that can undermine an apparently well-funded buildout
Utilization and customer-credit risk
Debt and leases require payment when servers are idle. If demand falls, a provider may be unable to cover fixed obligations from usage revenue. Customer defaults or contract cancellations can also reduce the cash flows pledged to lenders.
GPU obsolescence and collateral values
Accelerators can lose resale value when a newer generation delivers better performance per watt. A lender that financed equipment at a high original cost may reduce the borrowing base or require additional equity if collateral values decline.
Interest-rate and refinancing risk
Floating-rate facilities reprice during the loan term. Fixed-rate bonds avoid that immediate exposure but create a maturity wall: the issuer must refinance or repay a large principal amount when notes mature. Credit deterioration can make replacement financing more expensive or unavailable.
Lease and construction commitments
Signed leases and power reservations can remain payable even if a site opens late. Uncommenced commitments should be tracked separately from liabilities already recorded, with commencement dates and termination rights monitored by management.
Accounting and disclosure traps
Compare drawn debt with total facility capacity, operating-lease liabilities with finance-lease liabilities, and face value with discounted present value. Read covenant definitions: “adjusted EBITDA,” unrestricted cash and permitted liens can differ materially between agreements.
A practical framework for evaluating an AI infrastructure financing plan
- Map the assets. Separate GPUs, networking equipment, buildings, power systems and software. Estimate useful life, resale value and replacement cycle for each.
- Match funding tenor to asset life. Short-lived equipment should not be financed with an inflexible maturity that arrives after utilization ramps slowly; long-lived buildings may support longer project debt.
- Identify contracted revenue. Review customer credit, take-or-pay provisions, escalation clauses, termination rights and delivery milestones.
- Stress-test utilization. Model lower occupancy, delayed deployments, power-price increases and GPU resale discounts.
- Measure fixed obligations. Add interest, scheduled principal, lease payments, power commitments and minimum purchase obligations, then compare them with conservative cash flow.
- Check flexibility. Examine prepayment penalties, borrowing-base resets, collateral releases, change-of-control clauses and restrictions on additional financing.
- Separate announcements from execution. Confirm what has been raised, drawn, delivered and placed into service; do not treat a headline commitment as cash on hand.
The bottom line
AI companies finance compute by matching each obligation to a source of capital that can bear its risk. Equity absorbs uncertainty and supports early expansion; bonds and loans provide scale but demand repayment; leases trade ownership for predictable payments; and customer contracts can unlock asset-backed borrowing. The strongest plans combine these tools while preserving liquidity for a period when GPUs may be underused, rates may be higher and customers may delay commitments.
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