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Underwrite an AI cloud provider as critical infrastructure, not as a simple software subscription. Before signing, verify that the company can survive the contract, that the GPUs are installed and usable, and that the agreement measures capacity with enforceable remedies. Treat forecasts, pipeline announcements and aggregate GPU counts as uncommitted until documentary evidence proves otherwise.
Your review should produce three outcomes: a financial-resilience file, a site-by-site capacity schedule, and a contract that distinguishes usable GPU hours from mere endpoint availability. The process below turns those outcomes into evidence you can compare across providers.
Start with three separate questions
“Can this provider pay its obligations?” “Does it actually control the GPUs and supporting infrastructure?” and “What happens if my reserved capacity is unavailable?” are different questions. A provider can be well funded but oversubscribed, or operate a large fleet while depending on a fragile lessor, colocation site or utility.
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- Delivered capacity: whether the specific GPU model, topology, location and hours you are buying are installed, powered, networked, tested and reserved.
- Contract protection: whether availability, metering, exclusions, reporting and remedies are objective enough to enforce.
Score every claim as filed or audited, contractually committed, installed and tested, or management forecast. A press release, sales deck or uncommitted pipeline estimate is not delivered capacity.
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Build a financial-stability file
Request the strongest evidence the provider can lawfully share. For a public company, begin with audited annual statements and recent regulatory filings. For a private company, ask for audited statements; if unavailable, obtain reviewed or management accounts together with bank, financing and guarantee evidence. Tie each figure to a date and reporting period.
Documents and disclosures to request
- Audited balance sheet, income statement and cash-flow statement for the latest two fiscal years, plus the most recent interim accounts.
- Cash, restricted cash, committed credit lines, borrowing-base availability and minimum-liquidity covenants.
- Debt and maturity schedule, interest rates, security interests, defaults, lease liabilities and equipment-finance obligations.
- Recent equity or debt financings, investor commitments, covenant waivers and any refinancing that must close during your term.
- Insurance certificates and limits for property, business interruption, cyber incidents and professional liability.
- Parent guarantees, letters of credit or other credit support offered for your contract.
- Material litigation, regulatory actions, tax disputes and customer termination or default history.
- Revenue and GPU-hour concentration by customer, site, GPU lessor and colocation operator.
Ask management to explain how much cash is available after deposits, prepayments, hardware purchases, power reservations and debt service. A profitable income statement does not prove short-term liquidity; a provider may need customer prepayments or new financing to keep building.
Map infrastructure financing, not only corporate solvency
For every dependency, identify the legal counterparty, contract term, renewal rights, termination triggers and fallback: GPU lessor, equipment lender, colocation operator, utility, network carrier, storage provider and facilities contractor. NVIDIA’s 2026 SEC filing warns that “The availability of land, power, shell, and capital is crucial to support the buildout of a full data center inclusive of NVIDIA AI infrastructure by our customers and partners.” That warning applies to any vendor whose promised capacity depends on a future build.
Also note the scale and duration of industry commitments. NVIDIA reported $279 billion of supply and capacity commitments as of July 26, 2026. This figure is NVIDIA’s own reported commitment, not proof that a particular cloud provider has secured your GPUs. Ask the provider to identify which purchase orders, leases or capacity reservations support your allocation.
Tests that reveal financing stress
- Request a 12- to 18-month liquidity forecast showing base, delayed-build and demand-downside cases.
- Ask what happens if a planned financing, hardware delivery or colocation expansion is late.
- Check whether customer deposits are segregated, refundable or immediately used for general working capital.
- Require notice of material defaults, covenant breaches, insolvency filings, ownership changes and loss of a critical supplier.
- Set a right to suspend additional prepayments or terminate for an uncured material financial event.
Verify the GPUs you are buying
Do not accept “10,000 GPUs” as a capacity answer. Require a site-by-site schedule tied to your order and updated before service start.
Minimum fields for a capacity schedule
| Field | What to record |
|---|---|
| GPU identity | Model, generation, memory, firmware baseline and quantity |
| Host configuration | GPU count per node, CPU, memory, local storage and node type |
| Interconnect | Topology, fabric type, bandwidth, oversubscription and failure domains |
| Location | Country, facility, room or cluster identifier and time zone |
| Tenancy | Dedicated, reserved shared, or serverless; isolation method |
| Commitment | Committed system hours, start date, ramp schedule and maintenance reserve |
| Dependencies | Power allocation, cooling, network carriers, storage tiers and control plane |
| Substitution | Permitted GPU, topology, region or performance substitutions and approval process |
Have the provider identify the evidence behind each row: purchase order, lease, colocation reservation, utility allocation, rack assignment, installation record and acceptance test. Ask for serial-number or asset identifiers where security and confidentiality permit.
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Prove installation and readiness
- Obtain a delivery or lease document showing that the provider controls the specified hardware.
- Request rack, power and cooling allocation for the exact cluster, including redundancy assumptions.
- Review acceptance-test results for GPU health, fabric connectivity, storage throughput and node failure recovery.
- Confirm that the cluster is connected to the promised network and storage services in the contract’s region.
- Run a customer-observed validation job on representative nodes before the committed start date.
- Record the baseline inventory, topology and performance envelope as an attachment to the order.
Capacity is not ready when hardware is merely ordered or sitting in a warehouse. It is ready when the contracted configuration can accept your workload and the provider can show how it will remain available during maintenance and component failures.
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A credible operator can explain how it prevents oversubscription and how it reacts when demand rises. NVIDIA’s Requirements for AI Clouds, v2.4 (2026) calls for a capacity-planning process covering GPU, compute and supporting resources, with utilization monitored and forecast against available capacity. Ask to see the process, not just a utilization chart.
Questions to ask operations
- How are reservations separated from sellable but uncommitted inventory?
- What utilization threshold triggers procurement, throttling or a sales freeze?
- How are CPU, memory, network fabric, storage I/O and power tracked alongside GPUs?
- What capacity is held in maintenance reserve, and can it be used for other customers?
- How are noisy-neighbor effects, failed nodes and fabric partitions detected?
- How far ahead are demand forecasts reviewed, and who can approve additional commitments?
Require tenant-visible inventory and telemetry. At minimum, you should see allocated nodes, usable GPU hours, interruptions, maintenance, queue time and incident timestamps. NVIDIA’s requirements specify monthly metering accuracy of ±0.5% for shared or serverless capacity and ±0.1% for dedicated capacity (NVIDIA, 2026). Use those figures as a negotiation benchmark, or set stricter tolerances for workloads where billing variance is material.
Translate capacity into commercial exposure
Convert the technical schedule into the quantity you will actually pay for. State the number of committed system hours, the ramp by date, the price for each capacity type and the treatment of unused hours. Separate dedicated reservations from shared or serverless usage so a provider cannot satisfy a dedicated promise with lower-priority inventory. If a ramp is staged, identify the exact acceptance event for each stage and the fee that applies before and after acceptance.
Model the cash exposure under normal delivery and failure cases. Include deposits, prepaid minimums, hardware or power reservation charges, usage overages, maintenance credits, data-egress charges and any early-termination or transition fees. The contract should say whether an unavailable hour is refunded, credited against a future invoice or replaced with equivalent capacity. Credits that expire quickly or apply only to a small recurring fee may not compensate for a missed training window.
Ask for a sample monthly invoice and the underlying usage record. Reconcile node-hours, interruptions, maintenance and substitutions to the agreed telemetry source. Require correction of overbilling within a defined period and preserve your right to dispute an invoice without losing access to undisputed capacity.
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Set evidence and governance gates
Use a shared diligence register with one row for every material assertion: GPU count, site, power allocation, financing source, availability target, metering tolerance and fallback. Record the document name, issue date, responsible provider executive, your reviewer and the evidence grade. A forecast can remain in the register, but it should block a firm reservation until it becomes contractually committed or installed and tested.
Make the baseline a controlled contract exhibit. Version the inventory, topology diagram, performance results, committed hours and maintenance reserve. Require written change control for a new site, lessor, utility, interconnect or operating partner. A change that affects region, security boundary, performance or insolvency exposure should trigger your approval right, not merely a notification.
After launch, review the same evidence monthly. Obtain capacity-availability calculations, service-availability calculations, utilization and forecast reports, incident timelines, maintenance notices, metering corrections and open remediation items. Compare the provider’s forecast with delivered hours and investigate recurring variance. This cadence turns a one-time diligence exercise into an early-warning system.
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Write measurable availability and capacity terms
Separate service availability from capacity availability. Service availability describes whether the control plane, API or endpoint is usable. Capacity availability describes whether the usable contracted GPU hours were actually delivered.
Define the calculation
NVIDIA’s DGX Cloud SLA defines capacity availability as delivered system hours divided by committed system hours, with a 95% target. It separately sets a 99% service-availability target per calendar month. NVIDIA states that it measures capacity availability over one calendar month and tracks it every 60 minutes. These are examples to adapt, not automatic protection for your contract.
| Term | Contract language to specify |
|---|---|
| Committed system hour | One hour in which the named GPU system, topology and region must be usable by your tenant |
| Delivered hour | An hour meeting health, performance and access thresholds, not merely an hour when the API responds |
| Measurement interval | For example, 60-minute samples, with the clock, time zone and rounding rule stated |
| Exclusions | Planned maintenance, customer-caused incidents and force majeure, each narrowly defined and notified in advance |
| Source of truth | Provider telemetry retained for a stated period, with customer access and audit rights |
| Metering accuracy | Separate tolerances for dedicated and shared capacity; define correction of overbilling |
Set incident and remedy mechanics
- Classify severity by business impact, not only by internal component.
- Specify acknowledgement, mitigation, restoration and root-cause-report deadlines.
- Require advance notice for maintenance and identify the capacity reserve available during it.
- Set automatic service credits or fee reductions when targets are missed; do not make the customer prove the provider’s telemetry error.
- Add graduated remedies for repeated misses: capacity step-down, termination without an early-exit fee, refund of prepaid unused amounts and reasonable exit assistance.
- Define the claim window, evidence required and payment timing.
NVIDIA’s SLA describes commercially reasonable efforts toward resolution of critical incidents within 24 hours while noting that this is a target that may not always be achieved. If your workload has a hard recovery deadline, convert “commercially reasonable efforts” into a specific restoration objective and a remedy linked to the impact.
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Control substitutions, exclusions and exit risk
A provider may reserve a different GPU generation, topology or region unless the order prevents it. State whether substitution is prohibited, requires your written approval, or is allowed only when a defined performance test passes.
Substitution terms should cover
- GPU generation, memory, precision modes and software-driver compatibility.
- Node count, interconnect topology, collective-communication bandwidth and network oversubscription.
- Region, data-residency location and applicable security boundary.
- Performance acceptance tests and your right to reject a failed substitute.
- Pricing changes when the substitute has lower or higher capability.
Include security controls, data export formats, deletion certificates, image and container portability, log access and assistance migrating jobs. A low headline price is not protection if leaving requires weeks of engineering work or an unexpected data-egress bill.
Compare providers on evidence, not marketing totals
Use one scorecard for every bidder. Record the evidence date, owner and confidence level for each answer.
| Comparison axis | Evidence to collect |
|---|---|
| Financial transparency and liquidity | Audited accounts, cash, debt maturities, financing dependencies and guarantees |
| Installed versus promised GPUs | Asset or lease proof, rack assignment, acceptance tests and start-date inventory |
| Measurement and metering | Availability formula, telemetry access, retention, audit rights and accuracy tolerance |
| GPU and fabric performance | Model, memory, topology, network and storage test results |
| Power and facilities | Utility allocation, cooling design, colocation contract and redundancy evidence |
| Geographic resilience | Independent sites, failover capacity, data-residency limits and partnership structure |
| SLA remedies | Exclusions, credits, termination, refunds and repeated-miss provisions |
| Support response | Severity definitions, staffing model, acknowledgement and restoration targets |
| Portability and exit | Export process, deletion proof, assistance, fees and transition period |
| Concentration risk | Dependence on one GPU lessor, facility, utility, carrier or anchor customer |
Geography changes the meaning of “available.” The OECD’s methodology includes local providers partnered with major cloud providers and notes that relationships and infrastructure arrangements vary by geography. Record the legal provider, physical site, operating partner and ownership of each resource instead of treating a partnership badge as equivalent to redundancy.
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- A single aggregate GPU number with no model, site, topology or committed-hour schedule.
- Capacity described as “planned,” “coming soon” or “subject to financing” after the contract start date.
- Refusal to provide audited or equivalent financial information while requesting a large non-refundable prepayment.
- Unilateral substitution rights covering generation, region or topology.
- SLA language that measures only API uptime and excludes capacity shortages, queueing or fabric failures.
- Provider-controlled telemetry with no retention period, audit right or correction process.
- Broad maintenance and force-majeure exclusions that can remove most of the commitment.
- No named fallback for a failed lessor, colocation site, utility, network or storage provider.
- Credits that are the sole remedy even after repeated misses or an insolvency event.
Escalate a red flag to finance, legal, security and engineering together. A sales explanation is not a substitute for a changed schedule, evidence package or contract clause.
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- Define the workload: GPU model, memory, topology, region, concurrency, storage, network and minimum performance.
- Issue the evidence request: financial file, dependency map, capacity schedule, telemetry sample and draft SLA.
- Validate a representative cluster: inspect inventory and run acceptance tests before the start date.
- Score confidence: mark every claim filed or audited, contractually committed, installed and tested, or forecast.
- Model failure cases: delayed build, power loss, failed node, fabric partition, financing failure and provider insolvency.
- Negotiate protections: measurement, exclusions, remedies, substitution, security, export and termination.
- Attach the baseline: make the inventory, topology, performance results and committed hours contractual exhibits.
- Gate payment: tie deposits and ramp payments to documentary milestones and acceptance, not calendar promises.
- Operate a review cadence: receive monthly availability, utilization, incident, metering and capacity-forecast reports.
Sign only when the provider can show both the means to deliver and the obligation to deliver. If a critical fact remains a forecast, price and structure the deal as a contingent build rather than a firm GPU reservation.
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Frequently Asked Questions
How do I check whether an AI cloud provider can actually deliver the GPUs I am signing for?
Require a site-by-site schedule naming the GPU model, quantity, node configuration, interconnect, location, tenancy and committed hours. Match every row to purchase or lease evidence, rack and power allocation, installation records, acceptance tests and tenant-visible telemetry. A fleet total or future-build announcement is not proof of deliverable capacity.
What financial statements should I request from a GPU cloud vendor?
Request audited annual and interim statements, cash and restricted-cash balances, available credit, debt and maturity schedules, lease and equipment-finance obligations, recent financings, insurance, guarantees, litigation and customer concentration. For a private provider without audits, obtain reviewed or management accounts plus bank, financing and guarantee evidence, all tied to reporting dates.
What SLA protects me if reserved GPU capacity is unavailable?
Use separate service-availability and capacity-availability metrics. Define delivered system hours divided by committed system hours, the sampling interval, exclusions, telemetry source, metering accuracy, claim deadline and automatic credits or fee reductions. NVIDIA’s DGX Cloud example uses a 95% capacity target and 99% service-availability target per calendar month; negotiate remedies, termination and refunds that match your workload’s impact.
How accurate should GPU-cloud metering be?
NVIDIA’s 2026 AI-cloud requirements specify monthly accuracy of plus or minus 0.5% for shared or serverless capacity and plus or minus 0.1% for dedicated capacity. Put the tolerance, data-retention period, customer access, audit rights and overbilling correction process in the contract.
What should count as a committed system hour?
Define it as an hour in which the named GPU system, topology and region are usable by your tenant and meet agreed health, access and performance thresholds. State the time zone, rounding rule and treatment of maintenance, customer-caused incidents, force majeure, failed nodes and substitutions. API responsiveness alone should not satisfy a capacity commitment.
How can I reduce the risk of a provider’s future build slipping?
Tie deposits and ramp payments to documentary milestones such as delivery or lease control, installation, power and cooling allocation, acceptance testing and customer-observed validation. Require notice of financing or supplier failures, a delayed-build scenario, a named fallback and the right to suspend prepayments or terminate for an uncured material financial event.
What exit protections belong in a GPU contract?
Specify data and model export formats, image and container portability, log access, deletion certificates, security controls, egress and transition fees, assistance during migration and a defined transition period. Add refunds for prepaid unused capacity and reasonable exit assistance after repeated availability misses or a material provider failure.
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The Bottom Line
Approve a GPU contract only when financial resilience, infrastructure control and contractual measurement are documented separately. The strongest evidence is audited or filed information, a committed dependency map, installed-and-tested capacity, and telemetry-backed obligations with meaningful remedies.
If any critical element remains a forecast, do not treat it as reserved capacity. Make the build contingent, limit prepayment, and preserve suspension, refund and exit rights until the provider proves delivery.
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