Layer 2.5 · head to head
Google Cloud (A3, A4) vs Microsoft Azure (ND, NC)
TPU lock-in against enterprise-agreement pricing.
| Google Cloud (A3, A4) | Microsoft Azure (ND, NC) | |
|---|---|---|
| Can you leave | Movable with effort. Expect to redo images, storage wiring and networking. | Movable with effort. Expect to redo images, storage wiring and networking. |
| Counterparty | Effectively none. | Effectively none. |
| What it is | A general cloud that also rents accelerators. Most expensive per hour, and the one your compliance team has already approved. | 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. | You get virtual machines. The familiar cloud model. |
| Accelerators | H100, H200, B200, plus TPU v5e/v6/v7 | H100, H200, GB200, A100, plus Maia internally |
| Regions | Global | Global |
| Pricing model | On-demand, spot, committed use discounts, Dynamic Workload Scheduler. | On-demand, spot, reservations. |
| Getting started | Existing GCP account. | Existing Azure account. |
| Capacity | Constrained on newest parts; DWS is the queueing mechanism. | Heavily committed to OpenAI workloads historically; general availability varies sharply by region. |
| Ownership | Alphabet. | Microsoft. |
Google Cloud (A3, A4)
For: Teams already on GCP, and anyone who wants TPUs — which exist nowhere else.
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.
Economics: Spot B200 reported around $6.69/GPU-hour. Committed-use discounts change the picture substantially and are where the actual negotiation happens.
Microsoft Azure (ND, NC)
For: Enterprises with an Azure agreement, and anyone whose procurement runs through a Microsoft EA.
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.
Economics: List price is close to meaningless here. If you are paying list on Azure GPUs, the negotiation has not happened yet.
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