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Neocloud vs hyperscaler: what's the difference?

A neocloud is a GPU-first cloud whose product is rented AI compute, independent of AWS, Azure, Google Cloud and Oracle. A hyperscaler is a general-purpose cloud at global scale where AI compute is one product of many. DEPLOY tracks 32 verified neoclouds against that border; here is the full contrast.


Dimension by dimension

NeocloudHyperscaler
What it sellsAI compute itself: GPU / accelerator time, rented to third parties.A broad platform (compute, storage, database, networking); AI is one product of many.
GPU-first?Yes. The fleet and the data-center design exist for accelerated AI workloads.No. General-purpose fleets; GPU capacity is a segment inside a much larger estate.
IndependenceIndependent of AWS, Azure, Google Cloud and Oracle.Is one of them, or operates at that scale and scope.
Capacity modelDedicated AI data-center capacity, often single-tenant clusters with high-bandwidth interconnect.Massive multi-tenant regions serving every workload class.
Typical customerAI labs, model builders and enterprises that need large, cost-efficient GPU clusters.Every kind of IT buyer, from a hobbyist to a bank.
ExamplesCoreWeave, Lambda, Crusoe, Nebius, and the fast-growing Asian operators.AWS, Microsoft Azure, Google Cloud, Oracle Cloud.

The test that draws the border

A neocloud IS

  • GPU / AI-accelerator-first: compute is the product, not incidental to another business.
  • Rents that compute to third parties (not solely for its own workloads).
  • Independent of the hyperscalers (not AWS / Azure / Google Cloud / Oracle).
  • Operates or contracts dedicated AI data-center capacity (a real physical footprint).

A neocloud is NOT

  • Hyperscalers (general cloud at scale; AI is one product of many).
  • Pure colocation / REITs (sell space + power, not compute).
  • Enterprise self-builders that do not rent (xAI, Meta, Tesla for own use).
  • AI labs that do not resell compute, and brokers/aggregators with no capacity of their own.

The full operator-class contrast set (neocloud, hyperscaler, colocation, enterprise self-build, sovereign) and the global roster are on the neocloud taxonomy page.

Common questions

Is CoreWeave a neocloud or a hyperscaler?

A neocloud. CoreWeave is the reference example: a GPU-first cloud whose product is rented AI compute, independent of the hyperscalers, running dedicated AI data-center capacity. Scale alone does not make a hyperscaler; selling a general-purpose platform does. See the full neocloud test.

Is Azure or AWS a neocloud?

No. Microsoft Azure, AWS, Google Cloud and Oracle Cloud are hyperscalers: general-purpose clouds at global scale where GPU/AI capacity is one product among many. A neocloud is defined partly by being independent of exactly these four.

Can a company be both a neocloud and a hyperscaler?

Not under this taxonomy. The neocloud definition requires independence from the hyperscalers, so the two classes are mutually exclusive at the top. A hyperscaler can offer neocloud-like GPU products, but it remains a hyperscaler because AI compute is one product of many on a general-purpose platform.

Why does the distinction matter?

Because it changes who you are buying from and what you are exposed to: a neocloud is a focused, independent GPU supplier, while a hyperscaler is a diversified platform. For mapping the AI-compute supply chain, conflating the two hides where dedicated GPU capacity actually sits. The physical campuses are in the data-center registry.