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Layer 2.5 · head to head

Prime Intellect vs CUDO Compute

Two aggregators, and the question both make harder to answer: whose datacentre is this?

Prime IntellectCUDO Compute
Can you leaveMovable with effort. Expect to redo images, storage wiring and networking.Movable with effort. Expect to redo images, storage wiring and networking.
CounterpartyOne contract, many underlying suppliers. Convenient, and it obscures who actually holds your data.You are one layer removed from whoever owns the metal. Ask who that is.
What it isSells access across other people's clouds through one contract and one API.Brokers capacity somebody else owns. Cheapest headline rates, and the machine you get is not the machine you chose.
How you reach itYou get virtual machines. The familiar cloud model.You get virtual machines. The familiar cloud model.
AcceleratorsAggregated H100, A100 and others across providersH100, A100, V100, consumer parts
RegionsMulti-providerGlobal, distributed supply
Pricing modelAggregated marketplace across other clouds.On-demand and committed, aggregated from multiple suppliers.
Getting startedSelf-serve.Self-serve.
CapacityWhatever its suppliers have.Aggregated, therefore variable.
OwnershipPrivate.Private.

Prime Intellect

For: Researchers hunting the cheapest available cluster without opening ten accounts.

The catch: An aggregator's price advantage disappears the moment you need a guarantee it cannot make on its suppliers' behalf.

Economics: Genuinely useful for price discovery even if you end up buying direct.

CUDO Compute

For: Buyers who want marketplace pricing with a single commercial relationship.

The catch: Aggregation abstracts away the thing you most need to know for compliance: whose datacentre this actually is.

Economics: Competitive because it arbitrages underused capacity.

Neither table row is a price

Deliberately. Published on-demand rates at this layer move weekly, and essentially nobody signing a real contract pays them — every serious buyer pays less than every list figure either of these companies publishes. Quoting one here would date this page within a month.

The GPU rental price index carries dated, sourced figures instead, and the durable finding there is the spread: the identical H100 rents from roughly $1.38 to $12.29 an hour depending only on who you rent it from.

The layers underneath both

Whichever you pick is renting you chips in a building that needs power. In 2026 that is the constraint that binds: Microsoft has disclosed an Azure backlog it cannot fill for want of megawatts rather than accelerators, and the US interconnection queue exceeds 2,600 GW with roughly 80% of projects withdrawing before they energise.

Layer 2 — Silicon · Layer 1 — Energy · The interconnection queue

Verified 2026-09-09. We do not benchmark clusters and take no position paid for by either company. Where a provider here runs a referral programme it has not moved its placement — the comparison was written before any link was attached.

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