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About

How we rank & score

hyperscaler · vm · Layer 2.5

Microsoft Azure (ND, NC)

Enterprises with an Azure agreement, and anyone whose procurement runs through a Microsoft EA.

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

What you are buying

Business model
A general cloud that also rents accelerators. Most expensive per hour, and the one your compliance team has already approved.
How you reach it
You get virtual machines. The familiar cloud model.
Accelerators
H100, H200, GB200, A100, plus Maia internally
Regions
Global
Pricing model
On-demand, spot, reservations.
Getting started
Existing Azure account.
Capacity
Heavily committed to OpenAI workloads historically; general availability varies sharply by region.
Ownership
Microsoft.

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

The counterparty

Effectively none.

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

Reported at the top of the H100 price range — around $6.98/hr, the highest in a 15-provider survey. Enterprise agreements are where that number actually gets decided.

The economics

List price is close to meaningless here. If you are paying list on Azure GPUs, the negotiation has not happened yet.

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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