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ARM-Based Instances

An ARM-based instance is a cloud virtual machine that runs on ARM processor architecture, offering lower cost per compute unit compared to traditional x86-based instances for compatible workloads.

How It Works

Standard cloud instances run on x86 processors, the architecture that has powered most servers for decades. ARM-based instances use a different processor design, originally built for mobile and embedded systems, that delivers strong performance per watt at a lower price point. On AWS, the ARM offering is called Graviton, with Graviton3 and Graviton4 being the current generations. On GCP, the equivalent is Tau T2A instances, which run on Ampere Altra ARM processors. On Azure, the ARM option is Dpsv5-series instances, powered by Ampere Altra. Workloads written in languages like Go, Java, Python, and Node.js typically run on ARM without modification. Compiled code written for x86 may require a recompile or compatibility layer before it can run on ARM.

Why It Matters for Cloud Cost

Compute is usually the largest line item in a cloud bill. Switching eligible workloads to ARM-based instances can reduce the per-hour cost of those instances without reducing performance. Teams that run web servers, containerized microservices, data processing pipelines, or build systems often find ARM a straightforward substitution. The cost benefit is lost, however, if teams over-provision ARM instances just as they would x86 ones. The instance type alone does not fix poor sizing or idle resource waste. ARM savings also stack with commitment-based discounts such as AWS Reserved Instances, AWS Savings Plans, GCP Committed Use Discounts, and Azure Reservations, meaning teams that combine right-sizing to ARM with commitment purchasing can capture savings from both levers simultaneously.

Usage AI: Usage AI’s Usage Flex Savings Plan covers EC2, including Graviton-based instance families, so teams that have already migrated to ARM can apply commitment-based discounts on top of the lower on-demand rate without carrying any financial risk.

See how Usage AI saves 30 to 50% on AWS, GCP, and Azure.