So-called neocloud companies are facing a dilemma: They need to move up the AI stack to avoid being commoditized, but they risk competing against their big hyperscale customers if they do.

Neocloud operators, or GPU-as-a-service providers, sprang up to take advantage of the huge demand for compute using GPU accelerators for AI. Many customers were forced to rent the chips because they were unable to secure their own supply.

But this business model is fragile, according to consultants [1]McKinsey & Company , because it is inherently commoditized. There is limited differentiation in renting out access to specific hardware - typically Nvidia products - and price-driven competition can be fierce.

[2]

Investors backing neoclouds such as CoreWeave, Nebius (both publicly traded), and Crusoe (privately held), are betting that the companies will be able to transition to offering services built on their AI infrastructure instead. Such platforms would comprise training tools, inferencing services, and domain-specific stacks for particular industries such as financial services.

[3]

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Moving up the software stack like this will put them directly against the hyperscalers that have come to be their biggest customers, and will also require considerable time and resources to develop.

New Jersey-based CoreWeave is one of the larger neocloud operators, and 77 percent of its revenue came from just two customers during 2024. Microsoft accounted for 62 percent, and Nvidia was understood to make up a large chunk of the rest.

[5]

In its Q2 results released in August, the firm [6]reported revenues of $1.21 billion , up an impressive 207 percent year-on-year – but it also recorded a net loss of $290.5 million and spent $2.9 billion on capital expenditures during the quarter, building out new infrastructure to meet customer demand.

To stay in business, neoclouds must pursue differentiation without alienating the same hyperscalers that provide the bulk of their income, McKinsey says.

[7]CoreWeave CFO: $25B raised in debt and equity in 18 months

[8]Microsoft turning away AI training workloads – inferencing makes better money

[9]CoreWeave signs megalease at Applied Digital's not-so-little house on the prairie

[10]CoreWeave's $9B Core Scientific acquisition is a bid for more power

It foresees three potential pathways for these companies to follow in the mid- to long-term.

One is to carve out a niche position in markets where hyperscalers are less effective or less welcome, offering specialized services. Another is to focus instead on start-ups and hope to grow along with those customers, which McKinsey says could serve as a launchpad to expand into AI-native enterprise-scale companies.

The third fate is consolidation. Like many early cloud providers, some neocloud operators will be absorbed by hyperscalers, telcos, or other buyers. Other players in the market are also likely to simply fade away once the supply of GPUs catches up with demand. ®

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[1] https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-evolution-of-neoclouds-and-their-next-moves

[2] https://pubads.g.doubleclick.net/gampad/jump?co=1&iu=/6978/reg_offprem/paasiaas&sz=300x50%7C300x100%7C300x250%7C300x251%7C300x252%7C300x600%7C300x601&tile=2&c=2aSY1CbbPNtDd8fYctJWSEgAAAFY&t=ct%3Dns%26unitnum%3D2%26raptor%3Dcondor%26pos%3Dtop%26test%3D0

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[6] https://www.theregister.com/2025/08/13/debtladen_coreweave_continues_to_invest/

[7] https://www.theregister.com/2025/08/13/debtladen_coreweave_continues_to_invest/

[8] https://www.theregister.com/2024/10/31/microsoft_q1_fy_2025/

[9] https://www.theregister.com/2025/06/02/coreweave_applied_digital_nd/

[10] https://www.theregister.com/2025/07/07/coreweave_core_scientific_buy/

[11] https://whitepapers.theregister.com/