The three largest public cloud platforms—Amazon Web Services, Microsoft Azure, and Google Cloud Platform—all offer similar core services, but their pricing models vary. A virtual machine with the same CPU and memory requirements may cost more or less depending on the provider and region. Because infrastructure expenses add up quickly at scale, understanding these differences helps developers and businesses make informed decisions about where to deploy workloads. This tool offers a simplified comparison based on hourly rates for compute resources and lets you experiment with different usage patterns.
Each provider publishes detailed pricing tables for various instance types. To keep things straightforward, we use representative averages: $0.046 per vCPU-hour and $0.005 per GB-hour for AWS, $0.05 per vCPU-hour and $0.006 per GB-hour for Azure, and $0.031 per vCPU-hour and $0.004 per GB-hour for Google Cloud. These numbers roughly match midrange instance classes in popular regions. When you enter the number of vCPUs, memory, and hours per month, the calculator multiplies those values by the respective rates to estimate total monthly cost.
The output displays a small table showing the calculated cost for each provider. Keep in mind that these figures exclude additional charges such as storage, networking, operating system licensing, and premium support. Discounts like reserved instances or sustained-use pricing also affect the final bill. Nevertheless, this quick comparison highlights how different providers price their compute resources and can reveal opportunities to save money by switching or negotiating volume discounts.
Cloud pricing depends heavily on geographic region. For instance, running a server in northern Virginia might cost less than in Tokyo or São Paulo. Our simplified model doesn’t include regional adjustments, but you can approximate them by modifying the hourly rates. Most provider pricing pages list the per-region costs; copy those numbers into the rate variables if you need a precise projection for your location.
Imagine you run a web application that requires four vCPUs and 16 GB of memory, operating 720 hours each month (essentially 24/7). According to our defaults, AWS would charge about $174, Azure would cost roughly $201, and Google Cloud would come in near $134. These numbers highlight Google’s generally lower compute pricing, though the gap may narrow or widen depending on specific instance families and discount programs. Use the calculator to see how higher memory or more CPU cores influence the total.
While price is important, it isn’t the only factor in choosing a cloud provider. AWS boasts the broadest range of services and a mature ecosystem, while Azure integrates tightly with Microsoft’s enterprise software. Google Cloud is known for its data and machine learning capabilities. Performance, reliability, compliance certifications, and support options all play roles in the decision. The cost comparison simply adds one more data point to evaluate.
Regardless of provider, you can often reduce spending by rightsizing instances, using autoscaling to match demand, or taking advantage of spot/preemptible pricing for flexible workloads. Compute costs frequently dominate the infrastructure budget, so small optimizations make a big impact. If the calculator shows a significant cost difference between providers, consider whether migrating workloads is feasible or if hybrid strategies—mixing providers for specific tasks—might offer the best balance of cost and features.
This Cloud Compute Cost Comparison tool is designed for quick experimentation. Adjust the CPU, memory, and runtime numbers to see how your projected bill changes. For accurate forecasting, consult the detailed pricing calculators from each provider and account for discounts, storage, bandwidth, and management overhead. Nonetheless, this snapshot view demonstrates that prices vary noticeably, and savvy cloud users continually review their options to keep costs under control.
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