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AWS vs Oracle Cloud: GPU Compute Price Comparison

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for AWS and Oracle Cloud. Updated July 2026.

Provider Overview

Provider type
Hyperscaler
Hyperscaler
Founded
2006
2016
Headquarters
Seattle, WA
Austin, TX
Billing model
On-demand, Reserved (1yr/3yr), Spot
Pay-as-you-go, Annual Flex
Min commitment
None (on-demand)
None (pay-as-you-go)
Support tier
Basic → Enterprise
Basic → Premier
Regions
5 regions
4 regions

Strengths & Best For

AWS

AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.

Strengths
  • Widest global region coverage
  • Deep ecosystem integrations
  • Enterprise SLAs
  • Reserved instance discounts
Best For
Enterprise workloadsProduction ML inferenceTeams already on AWS
Visit AWS
Oracle Cloud

Oracle Cloud Infrastructure offers BM.GPU.H100.8 bare-metal nodes and VM.GPU.A10 instances with some of the most aggressive enterprise GPU pricing among hyperscalers. Bare-metal H100 configurations deliver full hardware performance with no virtualization overhead, ideal for large-scale AI training and HPC. Strong Oracle Database integration makes OCI a compelling choice for enterprises running AI alongside data-intensive workloads.

Strengths
  • Competitive pricing
  • Bare-metal GPU options
  • Oracle DB integration
  • Free tier
Best For
Oracle database workloadsEnterprise MLCost-sensitive enterprise
Visit Oracle Cloud

Live GPU Pricing

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Region Coverage

AWS5 regions
us-east-1us-west-2eu-west-1ap-southeast-1ap-northeast-1
Oracle Cloud4 regions
us-ashburn-1us-phoenix-1eu-frankfurt-1ap-tokyo-1

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