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About

How we rank & score

neocloud · vm · Layer 2.5

Vultr

Teams that want a GPU near their users rather than near Virginia, and anyone who needs a fraction of a GPU.

medium portability Movable with effort. Expect to redo images, storage wiring and networking.

What you are buying

Business model
Purpose-built GPU cloud. Owns or leases its own datacentre capacity and sells it directly.
How you reach it
You get virtual machines. The familiar cloud model.
Accelerators
H100, H200, A100, L40S, MI300X, plus fractional GPUs
Regions
Global, 30+ locations
Pricing model
Hourly on-demand, published openly. Fractional GPU options are unusual and useful.
Getting started
Credit card.
Capacity
Generally available; broad geographic spread is the differentiator.
Ownership
Private, long-established as a general cloud before GPUs.

Verified 2026-09-09. Fields reading “not published” are exactly that — we do not estimate a figure a vendor withholds.

The counterparty

Lower than the pure-play neoclouds — the GPU business sits on top of a profitable general hosting business rather than being the whole company.

A multi-year GPU commitment is a credit decision wearing a cloud contract. This is the section no benchmark covers and the one that decides what happens to your workload in 2028.

The catch

Not the cheapest and not the biggest. It wins on geography and on fractional sizes, which are the two things bigger providers handle badly.

The economics

Fractional GPU pricing makes small inference workloads viable that would be absurd on a whole H100.

No rate is quoted on this page on purpose. Published list prices at this layer move weekly and essentially nobody signing a real contract pays them. Dated, sourced figures live in the GPU rental price index, where the spread between the cheapest and dearest seller of the identical chip runs to roughly 9x.

The layers underneath this one

Whatever you rent here is a chip in a building that needs power. In 2026 megawatts, not silicon, are the binding constraint on the whole industry — a frontier rack draws 120–200 kW against a 2026 average near 27 kW, and the US interconnection queue exceeds 2,600 GW.

Layer 2 — Silicon · Layer 1 — Energy · The interconnection queue · Tokens per watt

Compared against

Related providers

Sources

Macrostackdoes not benchmark clusters and does not pretend to. For hands-on performance ratings of GPU clouds, SemiAnalysis’s ClusterMAX tests the hardware directly. This page covers what their scorecard does not: who owns the company and how you get out.

The Macrostack brief

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