AWS vs GCP vs Azure
Cost Comparison 2026
Compare equivalent compute instances across all three major clouds.
See real price differences — and how scheduling off-hours compounds the gap.
* Prices are indicative on-demand (pay-as-you-go) rates for 2025. Actual billing varies by exact instance generation, data transfer, storage, and any negotiated discounts. AWS = EC2, GCP = Compute Engine, Azure = Virtual Machines. Equivalent classes: AWS m-series / GCP n2-standard / Azure D-series (general purpose); AWS c-series / GCP c2-standard / Azure F-series (compute); AWS r-series / GCP m2 / Azure E-series (memory).
Cloud provider pricing is genuinely difficult to compare because instance specifications, pricing models, and discount structures differ significantly across AWS, GCP, and Azure. The comparison tool above maps equivalent instance types across all three providers and shows current on-demand pricing so you can see the cost differential for your specific workload profile.
Comparing Compute Costs Fairly
Comparing cloud providers on compute cost requires mapping equivalent instances rather than comparing raw specifications. A 4 vCPU, 16 GB memory instance on AWS (m5.xlarge) is broadly comparable to an n2-standard-4 on GCP and a Standard_D4s_v3 on Azure, but the underlying hardware, network capabilities, and included features differ. The comparison tool handles this mapping automatically, using standardised CPU and memory tiers.
Pricing is also region-dependent. AWS us-east-1 is typically the cheapest AWS region, while GCP's us-central1 and Azure's East US are similarly competitive. If your workload requires a specific region — for data sovereignty or latency reasons — the comparison will look different. The tool defaults to US East pricing, which represents each provider's most competitive tier.
On-demand pricing is a ceiling, not a floor. All three providers offer significant discounts through commitment-based programmes (Reserved Instances, Committed Use Discounts, Azure Reservations). A fair multi-year TCO comparison needs to account for these, not just list prices.
AWS Pricing Model
AWS prices EC2 by the second, with a minimum charge of one minute. On-demand pricing is the list rate with no commitment. Reserved Instances and Savings Plans reduce that rate by 30 to 72% in exchange for one- or three-year commitments. Spot Instances offer up to 90% discount for interruptible workloads. AWS's pricing is generally competitive on larger instance types but can be more expensive on smaller sizes compared to GCP.
AWS's cost optimisation ecosystem is also the most mature of the three providers. Tools like ServerScheduler, Cost Explorer, and Trusted Advisor give you more visibility and control over AWS spend than equivalent tools on GCP or Azure. For teams already running workloads on AWS, the Savings Plans recommendations and right-sizing tools can significantly close any cost gap with competing providers.
GCP Pricing Model
Google Cloud prices Compute Engine instances by the second with no minimum. GCP's Sustained Use Discounts are unique among cloud providers — they apply automatically without any commitment, giving a discount of up to 30% simply for running an instance for a large fraction of the month. For workloads that run consistently, this makes GCP's effective on-demand price lower than AWS's without any action required.
GCP's Committed Use Discounts (CUDs) offer further reductions of up to 57% for one- or three-year resource commitments. GCP also tends to have competitive pricing on custom instance shapes, which allow you to specify exact CPU and memory rather than choosing from fixed tiers — useful for workloads where standard AWS instance sizes are either slightly too small or significantly too large.
Azure Pricing Model
Azure Virtual Machines are priced per minute with standard on-demand rates comparable to AWS and GCP for equivalent specifications. Azure Reservations (one- or three-year commitments) provide discounts of up to 72%, similar to AWS's Savings Plans. Azure Hybrid Benefit allows customers with existing Windows Server and SQL Server licences to use them on Azure, which can significantly reduce costs for Microsoft-heavy environments.
Azure is often the most competitive option for teams running Microsoft workloads — .NET applications, SQL Server databases, Active Directory — where licence portability and native Azure AD integration provide additional value beyond raw compute price. For Linux workloads, the cost differential between providers is typically smaller.
Beyond Instance Price: Total Cost of Ownership
Instance price is only one component of cloud spend. Egress costs, managed service pricing (databases, load balancers, managed Kubernetes), support costs, and migration effort all factor into the real cost of a cloud platform. A provider that's 10% cheaper on compute might be more expensive overall once you account for higher egress rates or more expensive managed services.
For teams already on AWS, migration costs are also a significant consideration. Moving to a cheaper cloud provider rarely delivers the projected savings when you factor in re-architecture, testing, team retraining, and the operational complexity of running workloads during a migration period. In most cases, optimising your existing AWS spend through scheduling, right-sizing, and commitment planning delivers better economics than migration — and faster. The total cost of ownership guide explains how to model this properly.