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About

How we rank & score

marketplace · bare metal · Layer 2.5

SF Compute

Training runs that can start when the price is right rather than when the calendar says.

high portability Portable. The workload is standard enough to move to another vendor without a rewrite.

What you are buying

Business model
Brokers capacity somebody else owns. Cheapest headline rates, and the machine you get is not the machine you chose.
How you reach it
You get the physical machine. Maximum control, and every layer above it is yours to run.
Accelerators
H100 clusters
Regions
US
Pricing model
A genuine spot market for cluster time, with prices that clear and are published.
Getting started
Market participation.
Capacity
Cluster-scale blocks.
Ownership
Private.

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

The counterparty

Market mechanics rather than a vendor relationship.

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

You are buying a window, not a service. If your run overruns, you are back in the market at whatever it now costs.

The economics

The closest thing to a true commodity market for training compute. Its clearing price is a genuinely useful benchmark for what a reserved contract should cost.

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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