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Short answer: AWS Graviton2 can deliver better price performance than comparable-generation x86 EC2 instances, but it is not automatically faster or cheaper for every application. Graviton2 uses 64-bit Arm cores; the x86 options use a different architecture and may come from different generations. Compare specific instance families, then test your application, costs, and Arm64 dependencies before migrating.
What Graviton2 and “Intel x86” mean in EC2
AWS Graviton2 is an Arm-based processor generation built on 64-bit Arm Neoverse N1 cores. It appears in EC2 families including general-purpose M6g, compute-optimized C6g, memory-optimized R6g, and burstable T4g. AWS’s EC2 specifications identify M6g as Graviton2-based and M6i as using Intel Xeon Ice Lake processors.
“Intel x86” is not one fixed comparison target: x86-64 EC2 instances vary by processor and generation. Compare named instance types, such as M6g and M5 for a generation-aligned AWS example, rather than treating all Arm or all x86 processors as interchangeable. See AWS’s EC2 general-purpose instance specifications for family details.
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How to interpret AWS’s performance claim
AWS says Graviton2 instances can provide “up to 40% better price performance” than specified comparable-generation x86 instances. AWS makes this claim for particular family comparisons, including M6g relative to M5 and R6g relative to R5. “Up to” describes a maximum reported advantage, not a guaranteed speed increase or cost reduction for every workload. Price performance combines performance and price; it does not mean that every application runs 40% faster or costs 40% less.
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Performance also depends on what is measured: throughput, latency, capacity, or cost at a chosen service level. The result can change with the application, instance size and generation, software stack, AWS Region, purchase model, and benchmark method. AWS’s getting-started guide says, “In many cases, Graviton will provide performance and/or capacity improvements over x86-based instances”; this is AWS guidance, not a universal benchmark result. Read the AWS EC2 Graviton getting-started guide and the AWS Graviton performance-testing whitepaper for its testing advice.
Why equal vCPU counts may not mean equal resources
In the cited AWS comparison, an x86 vCPU represents a logical core using simultaneous multithreading (SMT), while a Graviton vCPU represents a physical core; Graviton has no SMT. Consequently, matching vCPU counts does not mean the instances have the same number of physical cores, nor does it establish equal performance. Compare measured application capacity and service-level outcomes rather than inferring equivalence from vCPU counts alone. AWS explains this distinction in its Graviton getting-started guide.
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What AWS benchmark examples show—and what they do not
AWS’s .NET 5 test
AWS’s December 4, 2020 Compute Blog benchmark tested an ASP.NET Core application under load on m5.xlarge and m6g.xlarge instances. Both configurations had 4 vCPUs and 16 GiB of memory. The post reported then-current us-east-2 (Ohio) hourly prices of $0.192 for m5.xlarge and $0.154 for m6g.xlarge. These are historical prices from that post, not current EC2 rates, and the benchmark applies to its stated application, software version, and method—not every .NET service. See AWS’s benchmark post.
Dream11’s reported workload
In an AWS Game Tech case study, Dream11 reported that 80 m5.4xlarge instances delivered 243 ms average latency at 42% aggregate CPU utilization, while 80 m6g.4xlarge instances delivered 204 ms average latency at 32% aggregate CPU utilization. The case study also reports nearly the same PDF generation time with 60 M6g instances as with 80 M5 instances. These are Dream11’s results for its workloads, as reported by AWS; they are not predictions for another application. See the Dream11 case study.
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How to decide whether your application should move
Run a controlled comparison of the actual candidate instance types. AWS recommends establishing a baseline and fully loading each type to find its maximum sustainable load before latency or error rates exceed acceptable limits. Use the same production-representative application, data, and load profile, and compare results against your service-level objectives.
- Choose the candidates. Identify the current x86 instance and a Graviton2 instance suited to the same role and resource needs. Record the exact family, generation, and size; avoid comparing broad labels such as “Arm” and “x86.”
- Check software support first. Confirm that your operating system, language runtime, native libraries, container base images, monitoring and security agents, and vendor-supported dependencies have compatible Arm64 builds for the versions you use.
- Establish a baseline. Capture the current service’s throughput, latency distribution, error rate, CPU and memory use, and cost under a representative workload.
- Load-test both candidates. Apply the same workload and increase load to determine sustainable throughput while tracking latency and errors. Stop when the service’s acceptable limits are exceeded, as AWS’s testing guidance recommends.
- Compare total cost in context. Use prices for the same AWS Region and purchase model, and compare cost at the capacity needed to meet your service objectives. Do not substitute AWS’s historical benchmark prices for a current estimate.
- Account for migration risk. Include the engineering work and operational risk of replacing unsupported dependencies, rebuilding images, changing deployment pipelines, and validating production behavior.
Arm64 compatibility is a migration gate
AWS lists Amazon Linux 2, Red Hat, SUSE, and Ubuntu among popular supported distributions, and identifies a range of supported software and services. That general support does not confirm that a particular version, package, native extension, or third-party agent in your deployment works on Arm64. Verify each component and its vendor support before treating an application as migration-ready. AWS’s overview is available in its R6g instance information.
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Practical verdict
Graviton2 is a strong EC2 candidate when the required software stack supports Arm64 and a representative load test shows that a specific Graviton2 instance meets the workload’s latency, error-rate, capacity, and cost needs. Keep the existing x86 option when dependencies are incompatible or when measured results do not justify migration. Make the decision from named instance types and your own workload results—not the architecture label or AWS’s maximum price-performance claim.
Quick Recap
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