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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →AI neoclouds make money by selling access to GPU computing and the infrastructure and software needed to run AI workloads. Their economics hinge on turning costly, installed capacity into billable service: long-term customer commitments can help forecast demand and finance infrastructure, but they do not guarantee that equipment will be delivered on time, kept busy, or operated profitably.
What an AI neocloud sells
A neocloud is not simply renting out individual graphics processing units (GPUs). It sells a service stack: GPU compute plus the servers, high-speed networking, storage, orchestration software, and support needed to run large AI workloads. Customers may use that capacity to train models, run inference, or develop AI applications. CoreWeave describes its platform in these terms in its 2025 Form 10-K.
The customer pays for usable computing capacity, while the provider must assemble and operate the physical and software systems behind it. That distinction matters: owning or securing GPUs is only one step between investment and revenue.
How capacity becomes a service
Secure and prepare infrastructure
The provider must obtain GPU systems, arrange powered data-center space, and install networking, storage, and cooling suited to dense AI workloads. It may own facilities, lease them, or work with infrastructure partners. A site or power commitment is not the same as a ready-to-rent GPU cluster: facilities must be built or prepared, connected to power, equipped, and made available to customers.
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CoreWeave reported 850 MW of active power and approximately 3.1 GW of contracted power capacity as of December 31, 2025. In its August 11, 2026 second-quarter results, it reported 1.5 GW of active power and approximately 3.7 GW of total contracted power as of June 30, 2026. These are company-reported infrastructure capacity measures, not figures for GPU utilization or billable hours.
Make the capacity usable
Once capacity is ready, the operator provisions access and supports customers’ workloads. The surrounding platform can matter as much as raw GPU access: networking and data movement affect how efficiently systems work together, while storage, orchestration, and support help customers deploy and manage workloads. CoreWeave describes infrastructure and proprietary software for training, inference, and related AI workloads in its 2025 Form 10-K.
How cloud contracts create revenue visibility
Neoclouds can sell capacity through commitments that reserve a specified amount for a term, through usage-based consumption, or through a mix. A take-or-pay commitment generally requires payment for contracted capacity even if the customer does not use all of it. This can make expected demand and cash flows more visible than relying only on sporadic usage, and may help a provider finance assets against contracted revenue. It does not remove the need to build and deliver the capacity.
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CoreWeave’s 2025 Form 10-K says committed contracts accounted for the following shares of its revenue. These are CoreWeave figures, not an industry-wide pattern:
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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →| Year | Share of revenue from committed contracts |
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| 2023 | 88% |
| 2024 | 96% |
| 2025 | Over 98% |
The same filing put the weighted-average duration of CoreWeave’s committed contracts at approximately five years as of December 31, 2025. Across active contracts at that date, weighted-average customer prepayment was 15% to 25% of total contract value. Those advances can help fund deployment, but contract value and prepayment are not the same as recognized revenue or profit.
CoreWeave also cautions in its 2025 Form 10-K that customers and the industry may not continue to support take-or-pay contracts. If business shifts toward pay-as-you-go consumption, cash-flow predictability and margins could change. Contract structure therefore affects the risk profile; it is not a permanent guarantee of demand or economics.
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Why utilization is the economic hinge
Utilization describes how much installed, available GPU capacity is productively used and billed over time. GPUs, servers, facilities, power arrangements, and financing create costs whether equipment is busy or sitting idle. When more GPU-hours are billed, the provider can spread those costs across more customer revenue. Low utilization leaves more of the cost base to be covered by fewer billable hours.
Utilization alone does not determine profit. Results also depend on achieved customer prices, workload mix, electricity and hosting costs, depreciation, financing, networking, maintenance, and whether nominal capacity is actually ready to serve. A contracted power figure, active power figure, backlog, or revenue total cannot substitute for a comparable utilization rate.
CoreWeave’s cited public materials report financial and capacity measures but do not provide a comparable company-wide metric for GPU-hours sold divided by available GPU-hours. As a result, those disclosures do not establish a utilization percentage that can responsibly be stated here.
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How to read revenue, backlog, and losses
Revenue is what a company recognizes for services delivered under its accounting rules; it is not the same as contract value, cash received, or profit. Backlog is a forward-looking measure, not money already earned. CoreWeave’s August 11, 2026 results reported a $104 billion revenue backlog as of June 30, 2026, excluding more than $25 billion in net new customer commitments added in early Q3. The company said its backlog measure includes remaining performance obligations and other amounts it estimates will be recognized under committed contracts, and remains subject to delivery and service-availability requirements.
CoreWeave’s reported results show why revenue growth and profitability must be read separately. The company reported the following for full-year 2025 and the second quarter of 2026:
| Period | Revenue | Operating result | GAAP net result | Adjusted EBITDA |
|---|---|---|---|---|
| Full year 2025 | $5.1 billion | Not stated in the cited summary | $1.2 billion net loss | Not stated in the cited summary |
| Q2 2026 | $2.575 billion, compared with $1.212 billion in Q2 2025 | $49 million operating loss | $626 million net loss | $1.510 billion |
Adjusted EBITDA is a non-GAAP measure, which CoreWeave says is supplemental and not a substitute for GAAP results. It should not be used by itself to describe the company as profitable. CoreWeave’s 2025 filing also attributes rising costs in part to infrastructure investment and depreciation and amortization. The central trade-off is capital recovery: revenue and commitments can grow while the equipment, facilities, and financing needed to fulfill them remain expensive.
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Why a data-center partner may earn a different kind of revenue
A cloud operator can depend on a separate company to provide facilities and power capacity. In that arrangement, the host earns fees for infrastructure rather than selling GPU compute directly to the end customer. Core Scientific’s March 2, 2026 Q4 FY2025 presentation describes one such CoreWeave relationship across five sites.
- The presentation describes approximately 590 MW of leased customer power capacity covered by the contracts.
- It estimates more than $10 billion in potential revenue over the contract terms and approximately $850 million in average annual revenue.
- For the summarized arrangement, it says CoreWeave pays for capital expenditures, power, and utilities. Core Scientific funds some construction costs, which are credited against hosting payments subject to specified limits.
These are Core Scientific’s presentation figures for its disclosed contract, not a general estimate of data-center-host margins or neocloud economics. The example illustrates that host revenue and cloud-operator revenue arise at different points in the service chain.
What to compare when evaluating a neocloud’s model
There is no like-for-like multi-provider scorecard in the cited company materials. For a meaningful comparison, look for comparable disclosures across these areas rather than treating one headline number as a proxy for business quality:
- Contract mix: reserved or take-or-pay commitments versus consumption-based usage, along with duration, prepayments, termination terms, and customer concentration.
- Capacity readiness: distinguish power secured, facilities energized, GPU systems installed, and capacity actually available to customers.
- Utilization and pricing: seek comparable billable GPU-hours and achieved prices per unit; note when providers do not publish them.
- Capital and ownership: identify who funds and owns GPUs, facilities, and power infrastructure, and how debt, leases, customer advances, and partner financing fit together.
- Financial performance: examine cost of revenue, depreciation, interest, operating cash flow, and GAAP profit or loss. Keep adjusted measures labeled separately.
- Platform capability: assess software, networking, storage, workload support, reliability, and technical assistance in addition to access to GPUs.
These distinctions help explain the model without assuming that a large contract book, secured power, or rising sales automatically means high utilization or durable profits.
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