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How we rank & score

Layer 2.5 · head to head

Paperspace (DigitalOcean) vs JarvisLabs

Notebook-first workflows at two very different scales.

Paperspace (DigitalOcean)JarvisLabs
Can you leaveMovable with effort. Expect to redo images, storage wiring and networking.Movable with effort. Expect to redo images, storage wiring and networking.
CounterpartyBacked by a public parent, which is a genuine difference from the private pure-plays.Small provider.
What it isPurpose-built GPU cloud. Owns or leases its own datacentre capacity and sells it directly.Purpose-built GPU cloud. Owns or leases its own datacentre capacity and sells it directly.
How you reach itYou get virtual machines. The familiar cloud model.You push a container image and it runs. No cluster to operate.
AcceleratorsH100, A100, A6000, RTX 4000A100, H100, RTX 6000 Ada, A6000
RegionsUS, EUIndia, US
Pricing modelHourly on-demand plus subscription tiers.Hourly, pause-and-resume billing.
Getting startedCredit card.Very low.
CapacityModerate; newest parts are limited.Small.
OwnershipAcquired by DigitalOcean.Private.

Paperspace (DigitalOcean)

For: Notebook-first workflows and teams already on DigitalOcean.

The catch: The acquisition has meant a long, slow product convergence. Check which console you are actually buying in.

Economics: Mid-market pricing. The notebook product is the reason to be here, not the GPU rate.

JarvisLabs

For: Individual researchers and small teams, particularly in India.

The catch: Small scale. Fine for one machine, not for a cluster.

Economics: Pause-and-resume is the useful feature — you stop paying without losing the environment.

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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