Layer 2.5 · head to head
AWS (P5, P6, G6) vs Oracle Cloud (OCI)
The most expensive hyperscaler against the cheapest, on egress as much as on GPUs.
| AWS (P5, P6, G6) | Oracle Cloud (OCI) | |
|---|---|---|
| Can you leave | Movable with effort. Expect to redo images, storage wiring and networking. | Portable. The workload is standard enough to move to another vendor without a rewrite. |
| Counterparty | Effectively none. This is the reason the premium exists. | 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 the physical machine. Maximum control, and every layer above it is yours to run. |
| Accelerators | H100 (P5), B200 (P6), L4/L40S (G6), plus Trainium and Inferentia | H100, H200, B200, GB200, A100 |
| Regions | Global | Global |
| Pricing model | On-demand, spot, Savings Plans, and Capacity Blocks for reserved GPU windows. | On-demand and heavily discounted committed contracts. Bare metal is a first-class product rather than an afterthought. |
| Getting started | Existing AWS account. | Account, with a sales motion for clusters. |
| Capacity | Constrained on the newest parts; Capacity Blocks exist precisely because on-demand cannot be relied on. | Aggressively expanded; OCI has won several very large AI contracts. |
| Ownership | Amazon. | Oracle. |
AWS (P5, P6, G6)
For: Anyone whose data, VPC, compliance boundary and team already live in AWS. The GPU price is rarely the deciding number.
The catch: Reported around $9.36/GPU-hour for a B200 Capacity Block against roughly $5.50 at Lambda. You are buying integration and counterparty certainty, and paying for both.
Economics: Egress and adjacency costs usually dominate the GPU line. Compare total workload cost, never the hourly rate alone.
Oracle Cloud (OCI)
For: Large training runs that want bare-metal RDMA clusters with hyperscaler counterparty certainty.
The catch: The cheapest hyperscaler on paper and the one whose commercial relationship people most often regret not reading carefully. Read the commit terms.
Economics: Consistently undercuts AWS and Azure on comparable GPU instances, and low egress pricing is a genuine structural difference rather than a promotion.
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