hyperscaler · vm · Layer 2.5
Google Cloud (A3, A4)
Teams already on GCP, and anyone who wants TPUs — which exist nowhere else.
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, B200, plus TPU v5e/v6/v7
- Regions
- Global
- Pricing model
- On-demand, spot, committed use discounts, Dynamic Workload Scheduler.
- Getting started
- Existing GCP account.
- Capacity
- Constrained on newest parts; DWS is the queueing mechanism.
- Ownership
- Alphabet.
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
TPU is the real differentiator and the real lock-in. Choosing a TPU is choosing Google Cloud for the life of that workload; there is no second supplier.
The economics
Spot B200 reported around $6.69/GPU-hour. Committed-use discounts change the picture substantially and are where the actual negotiation happens.
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 cost calculator, where the cheapest and dearest published on-demand price for the identical H100 sit 5.6× apart.
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
- AWS (P5, P6, G6) vs Google Cloud (A3, A4) — Capacity Blocks against Dynamic Workload Scheduler — two answers to the same shortage.Compare with AWS (P5, P6, G6)
- Google Cloud (A3, A4) vs Microsoft Azure (ND, NC) — TPU lock-in against enterprise-agreement pricing.Compare with Microsoft Azure (ND, NC)
Related providers
- AWS (P5, P6, G6) — hyperscaler, medium portability
- Microsoft Azure (ND, NC) — hyperscaler, medium portability
- Crusoe — neocloud, medium portability
- CUDO Compute — marketplace, medium portability
- DataCrunch — neocloud, medium portability
- Genesis Cloud — neocloud, medium portability