There is no universally cheapest cloud provider. AWS, Microsoft Azure, Google Cloud, and IBM Cloud can each be the lowest-cost choice for a particular workload—but the answer depends on region, operating system, CPU architecture, utilization, storage, data transfer, managed services, licensing, support, and negotiated discounts.
A low virtual-machine rate is not a complete cloud bill. A defensible comparison must include the services around the VM: disks, backups, databases, load balancers, NAT, monitoring, support, software licenses, and sometimes the labor required to operate the platform.
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As of the pricing information reviewed on August 16, 2026, the practical starting point is:
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- Azure: Frequently compelling for organizations with Windows Server, SQL Server, Microsoft enterprise agreements, or eligible licenses.
- Google Cloud: Often attractive for analytics, Kubernetes, custom-sized compute, and data-platform workloads—but query and network costs must be modeled carefully.
- IBM Cloud: Usually a specialized choice for IBM Power, bare metal, Red Hat OpenShift, hybrid infrastructure, or regulated workloads rather than the cheapest commodity VM.
What a cloud pricing comparison should measure
Cloud pricing has four different meanings:
- List price: The public rate shown by a provider.
- Effective price: The rate after reservations, savings plans, committed-use discounts, enterprise agreements, credits, or existing-license benefits.
- Fully loaded cost: The invoice plus networking, storage, databases, backup, observability, support, security tools, and operating labor.
- Unit economics: Cost per customer, request, transaction, API call, processed gigabyte, query, or completed workload.
For a simple test environment, list price may be enough. For production, total cost of ownership is the more useful measure:
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Monthly TCO = compute
+ attached storage
+ object storage
+ database
+ backup and replication
+ load balancing
+ NAT and gateways
+ internet egress
+ inter-zone and inter-region traffic
+ monitoring and logs
+ security services
+ support
+ software licensing
+ estimated operations labor
- valid credits and discountsMigration belongs in a separate first-year model. Include data transfer, application refactoring, dual-running environments, downtime risk, professional services, staff training, and migration tooling.
A fair four-provider benchmark
Before collecting prices, freeze the assumptions. Otherwise the comparison can look precise while comparing different products.
| Assumption | Recommended treatment |
|---|---|
| Geography | Name one specific, comparable region for each provider. Do not compare US East with Europe or Asia. |
| Currency | Use USD consistently, or disclose currency conversion dates. |
| Billing period | Use 730 hours per month for a continuously running instance and state that assumption. |
| Compute | Model four vCPUs and 16 GB of RAM, or the closest available shape. |
| Operating system | Use Linux for the baseline. Create a separate Windows and SQL Server scenario. |
| Architecture | Hold x86 or Arm constant where possible. Record the CPU generation and architecture. |
| Storage | Include 200 GB of general-purpose SSD or block storage, plus 1 TB of standard object storage. |
| Traffic | Specify internet egress, inter-region traffic, and inter-zone traffic rather than saying “normal bandwidth.” |
| Availability | Distinguish a single-zone test from a multi-zone production design. |
| Database | Use the same engine, capacity, storage, backup retention, and high-availability design. |
| Discounts | Show on-demand first. Model one-year and three-year commitments separately. |
| Support | Either include equivalent production support or exclude it from every provider. |
Record vCPU type, memory, network capability, attached or local storage, burstable versus dedicated performance, availability assumptions, included transfer, and whether commercial software is included. Instance names are not equivalent across providers: an AWS “m” family, Azure “D” family, Google Cloud “n” machine, and IBM balanced virtual server may have materially different performance and licensing.
AWS pricing
AWS pricing commonly combines EC2, EBS, S3, data transfer, load balancing, NAT Gateway, CloudWatch, backups, and a database service such as RDS or Aurora. A small EC2 rate can therefore become a substantially larger application bill.
Commitment options
- On-Demand: Maximum flexibility, but normally the least discounted option for steady usage.
- Compute Savings Plans: A one- or three-year commitment to a consistent hourly spend. AWS describes these as flexible across EC2 instance families, regions, operating systems, Fargate, and Lambda.
- EC2 Instance Savings Plans: Potentially larger discounts, but tied more closely to an instance family and region.
- Reserved Instances: Useful when the instance type, region, and operating pattern are predictable.
- Spot Instances: Suitable for interruptible jobs, batch processing, and fault-tolerant workers—not a direct replacement for reliable production capacity.
AWS advertises savings of up to 66% for Compute Savings Plans and up to 72% for EC2 Instance Savings Plans. Those are maximum advertised figures, not a guaranteed saving for an individual workload. See the AWS Compute Savings Plans pricing page.
Common AWS cost traps
- NAT Gateway charges for hourly operation and processed data.
- Elastic Load Balancing, public IPv4 addresses, and cross-zone or cross-region traffic.
- EBS volume capacity, provisioned performance, snapshots, and backup retention.
- S3 requests, retrieval, storage-class transitions, replication, and transfer.
- CloudWatch metrics, log ingestion, log storage, alarms, and CloudTrail data events.
- Separate RDS, Aurora, DynamoDB, Redshift, or other managed-service consumption.
AWS is often a strong fit when the team needs a broad service catalog, already has AWS expertise, or can benefit from Savings Plans, Spot capacity, or Arm-based compute. Its flexibility also creates more meters to govern and more opportunities for an overlooked charge.
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Build the estimate in the AWS Pricing Calculator. Add each service separately, choose the exact region and operating system, produce an on-demand estimate, then create separate Savings Plan, Reserved Instance, and Spot models.
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Azure Virtual Machines are only one part of an Azure cost model. Include managed disks, snapshots, Azure Backup, bandwidth, load balancing, NAT Gateway, monitoring, security services, and the selected database architecture.
Azure commitment and licensing options
- Pay-as-you-go: Flexible and useful for uncertain or short-lived workloads.
- Reserved VM Instances: Designed for predictable VM capacity over a one- or three-year term.
- Azure Savings Plan for Compute: A commitment-based option for eligible compute usage.
- Spot VMs: Lower-cost interruptible capacity for workloads that can tolerate eviction.
- Azure Hybrid Benefit: Allows eligible customers to apply qualifying Windows Server or SQL Server licenses. Eligibility and rights must be confirmed.
Azure Hybrid Benefit can change the comparison substantially, but it does not make Azure automatically cheaper for every Microsoft customer. Check the license edition, Software Assurance or subscription rights, license mobility, VM family, region, and agreement terms. Show license-included and eligible-BYOL calculations separately.
Azure pricing may also depend on whether the buyer uses a Microsoft Customer Agreement, Enterprise Agreement, or Cloud Solution Provider. Logged-in customers may see negotiated billing-account rates in the calculator rather than only retail prices.
Use the Azure Pricing Calculator. Add the region, VM size, operating system, disks, backup, bandwidth, and expected consumption. The calculator supports retail, reservation, and savings-plan scenarios. Microsoft’s documentation notes that a one-month VM example defaults to 730 hours; published examples are not current price quotes. See the Azure calculator documentation.
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Google Cloud pricing
Google Cloud—often still called GCP—can be particularly competitive when custom machine sizing prevents overprovisioning or when analytics, Kubernetes, and data services are central to the architecture.
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- The available storage capacity may vary.
Important Google Cloud cost components
- Compute Engine: Model the exact machine family, region, operating system, usage, and attached disks.
- Custom machine types: A useful option when standard vCPU-to-memory ratios do not fit the workload.
- Sustained-use discounts: Product- and machine-family-dependent; do not assume they apply identically to every current Compute Engine product.
- Committed-use discounts: Appropriate for predictable compute demand.
- Spot VMs: Useful for interruptible workloads.
- BigQuery: Separate query scans or capacity charges from ingestion, storage, streaming, reservations, and data transfer.
- GKE: Include cluster or control-plane charges where applicable, worker nodes, disks, load balancers, logs, and network traffic.
- Cloud Storage: Include operations, retrieval, replication, and egress—not only stored capacity.
Google Cloud may win an analytics project on data-platform productivity or custom sizing, but “analytics” is not one price category. Query volume, scan efficiency, ingestion, inter-region movement, and premium networking can overwhelm an attractive compute rate.
Use the Google Cloud Pricing Calculator. Add Compute Engine, BigQuery, GKE, Cloud Storage, Cloud Run, Pub/Sub, or other services individually. Keep on-demand, committed-use, and Spot models separate.
IBM Cloud pricing
IBM Cloud should be evaluated by functional fit rather than treated as simply the fourth commodity VM provider. Its economics can make more sense when the workload needs dedicated hardware, IBM Power, Red Hat OpenShift, hybrid infrastructure, license portability, isolation, or regulated-industry capabilities.
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- IBM Cloud VPC Virtual Server Instances.
- Bare metal servers and dedicated capacity.
- IBM Power Virtual Server.
- IBM Kubernetes Service and Red Hat OpenShift on IBM Cloud.
- Object, block, and file storage.
- Managed databases, backups, monitoring, logging, and connectivity.
IBM lists pay-as-you-go, reservations, subscriptions, and an Enterprise Savings Plan among its commercial routes. IBM also highlights license portability, bare-metal offers, object-storage plans, migration incentives, and enterprise payment options. Promotions and credits are temporary: treat them as a separate first-year cash-flow scenario, not as the normal long-term rate.
IBM can be a poor fit for a simple elastic web server if its specialized capabilities are unused. Conversely, comparing only the hourly VM rate can miss the cost of replacing Power, OpenShift, bare metal, or an existing IBM and Red Hat operating model elsewhere.
Use the IBM Cloud cost estimator. Select the service, configure the pricing plan and usage, calculate the estimate, review the assumptions, and download a quote where available. Create separate estimates for VPC servers, bare metal, OpenShift, Power, and storage when those are realistic alternatives.
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- To get set up, connect the portable hard drive to a computer for automatic recognition no software required
- This USB drive provides plug and play simplicity with the included 18 inch USB 3.0 cable
- The available storage capacity may vary.
Three comparison scenarios that produce useful answers
Scenario A: Short-lived or unpredictable application
Use on-demand compute, moderate storage, bursty traffic, explicit internet egress, and no promotional credits. Do not assume a one- or three-year commitment is cheaper unless the workload remains active long enough to reach break-even.
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Scenario B: Steady production application
Model 24/7 compute, multi-zone deployment, a managed database, backups, monitoring, logs, load balancing, NAT, and normal internet egress. Compare on-demand, one-year, and three-year commitments.
Here, the commitment discount and architecture often matter more than a small difference in VM list rates. Calculate the break-even utilization:
Break-even months = commitment cost / comparable on-demand monthly costThen test a downside case in which capacity falls by 20% or the workload migrates early. An unused commitment can cost more than on-demand capacity.
Scenario C: Microsoft Windows and SQL Server
Run two separate models:
- Windows Server and SQL Server with licenses included in the cloud price.
- Azure using eligible existing licenses through Azure Hybrid Benefit, compared with the licensing treatment available on other providers.
Include Software Assurance or subscription rights, license mobility, edition, core requirements, region, VM family, and the organization’s actual Microsoft agreement. Azure often becomes more attractive in this scenario, but the result is conditional on eligibility and negotiated terms.
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Workload-specific guidance
| Workload | Provider to model first | What can change the result |
|---|---|---|
| Small Linux web application | All four, starting with on-demand rates | Egress, NAT, load balancing, support, and management labor often exceed the VM-rate difference. |
| Always-on production application | AWS, Azure, and Google Cloud with commitments | Multi-zone design, database HA, backups, and unused reservations. |
| Windows and SQL Server | Azure | Azure Hybrid Benefit, Microsoft agreement rates, license eligibility, and SQL edition. |
| Kubernetes platform | Google Cloud, AWS, and Azure | Worker-node utilization, control-plane charges, disks, load balancers, logs, and team expertise. |
| Analytics warehouse | Google Cloud | BigQuery scans, capacity commitments, ingestion, storage, and inter-region data movement. |
| Serverless API | AWS, Google Cloud, or Azure | Request volume, execution time, API gateway, queues, logs, cold starts, and egress. |
| High-egress SaaS or video | Benchmark all four | Internet egress, CDN architecture, origin traffic, caching, and regional replication can dominate. |
| Power, OpenShift, bare metal, or regulated workload | IBM Cloud | Availability, compliance, license portability, dedicated capacity, and migration effort. |
Hidden costs that commonly invalidate comparisons
- Different regions: Prices and service availability vary by region.
- Different operating systems: Linux, Windows, RHEL, and commercial software images are not interchangeable.
- Ignored egress: Internet, cross-region, cross-zone, CDN-origin, and managed-service transfer can be significant.
- Missing NAT: Private-subnet architectures can add gateway hourly and processing charges.
- Capacity-only storage models: IOPS, throughput, requests, retrieval, snapshots, replication, and backup retention may be separately billed.
- Single-instance databases: A low-cost database is not equivalent to a production multi-zone or replicated deployment.
- Self-managed versus managed services: A database VM may have a lower invoice but require more patching, backup, monitoring, and staff time.
- Promotional credits: Startup, migration, free-tier, and promotional credits expire and should not be treated as recurring savings.
- Support: Production support may materially increase the cost of a small environment.
- Unused commitments: Reservations and savings plans become liabilities when demand falls or architecture changes.
- Operational labor: A provider with a lower infrastructure invoice may require more engineering time.
How to calculate your own cloud TCO
- Describe the workload: requests, users, transactions, query scans, storage growth, uptime, and traffic destinations.
- Freeze technical assumptions: region, architecture, vCPU, memory, OS, database engine, availability, retention, and performance.
- Build an on-demand baseline: add every required service in each official calculator.
- Separate fixed and variable costs: compute and storage differ from requests, scans, egress, and execution time.
- Model commitments separately: compare one-year and three-year options and calculate the utilization break-even.
- Add licensing: show license-included and eligible-BYOL cases.
- Add operations: estimate labor for deployment, patching, security, monitoring, incident response, and optimization.
- Run sensitivity cases: low, expected, and high traffic; lower utilization; increased egress; and early migration.
- Save evidence: export the calculator results and record date, region, currency, plan, and assumptions.
Start with the providers’ official tools rather than a generic comparison site. AWS has the AWS calculator; Azure has its pricing calculator; Google Cloud has its pricing calculator; and IBM has its cloud estimator. Third-party calculators can help identify categories to investigate, but verify every price against the provider’s current calculator and your account terms.
Which cloud is cheapest?
For a broad, flexible application: Begin with AWS, Azure, and Google Cloud, then compare the fully loaded architecture. AWS may be attractive when breadth and existing expertise reduce labor, while Google Cloud may benefit custom sizing or data-heavy designs.
For a Microsoft estate: Begin with Azure and model Azure Hybrid Benefit and the organization’s actual Microsoft purchasing agreement. Compare both license-included and eligible-license scenarios.
For analytics and data platforms: Begin with Google Cloud, but calculate BigQuery scans, ingestion, storage, replication, and egress rather than comparing VM rates.
For IBM Power, OpenShift, bare metal, or hybrid requirements: Evaluate IBM Cloud on functional and migration economics. A commodity VM comparison is not the right test.
For a cost-sensitive workload: Benchmark all relevant providers with identical regions, specifications, availability, licensing, traffic, support, and commitment assumptions. The cheapest VM is not necessarily the cheapest application.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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