AWS Graviton Instances: 40% Better Price-Performance, Explained

What Is AWS Graviton?

Graviton is AWS's family of custom ARM-based processors, designed in-house using the Arm Neoverse platform. Unlike Intel Xeon or AMD EPYC chips that AWS buys from third parties, Graviton is built by Amazon — which means AWS controls the silicon, the pricing, and the optimization for their own cloud infrastructure.

The key difference: Graviton uses the ARM architecture (the same instruction set behind your phone and Apple's M-series chips) instead of the x86 architecture used by Intel and AMD. This means compiled binaries aren't directly compatible — you need ARM64 builds of your software.

Graviton Generations: 2, 3 & 4

AWS has shipped three production generations of Graviton (the original Graviton1 powered the a1 family but is now largely superseded):

Which Instance Families Support Graviton?

Graviton is available across all major EC2 families. The naming convention: a “g” suffix in the family name indicates Graviton (e.g., c6g vs c6i).

There's a Graviton option for virtually every common workload pattern — compute, general-purpose, memory, and burstable. Storage-optimized (i-family) and accelerated (p-family GPU) instances are the notable exceptions.

Pricing: ~20% Cheaper, Consistently

Graviton instances are priced approximately 20% below their Intel counterparts at every size. Here's a direct comparison in us-east-1:

At scale, these savings compound. A fleet of 20 c6g.large instances saves roughly $245/month compared to c6i.large — just from the pricing difference, before accounting for any performance advantage.

Performance: Equal or Better, at Lower Cost

AWS claims up to 40% better price-performance for Graviton, and independent benchmarks broadly confirm this. The math works out to: 20% lower price + comparable raw performance = ~40% better price-performance.

Graviton2 (c6g) raw performance is within 5% of Intel (c6i), but costs 20% less — resulting in clear price-performance wins. Graviton3 (c7g) closes the raw performance gap entirely and often exceeds Intel on multi-threaded workloads.

See real benchmark data: c6g.large benchmarks | c6i.4xlarge benchmarks

Software Compatibility: ARM vs x86

The biggest consideration when adopting Graviton is architecture compatibility. Graviton runs ARM64 (aarch64), not x86_64. This affects:

What works out of the box

• Interpreted languages — Python, Ruby, Node.js, PHP, Java (JVM) all run natively on ARM64 with no code changes
• Most Linux distros — Ubuntu, Amazon Linux 2/2023, Debian, RHEL, and SUSE all ship ARM64 AMIs
• Popular databases — PostgreSQL, MySQL, Redis, MongoDB all have ARM64 builds
• Container runtimes — Docker, containerd, and Kubernetes all support ARM64 natively

What needs attention

• Compiled binaries — C/C++/Go/Rust code must be recompiled for ARM64. Cross-compilation is straightforward for most projects
• Docker images — You need multi-arch images or ARM64-specific builds. Use docker buildx to build for both platforms
• Third-party agents — Monitoring agents, security tools, and vendor SDKs may not have ARM64 builds. Check before migrating
• x86-specific instructions — Code using AVX-512, SSE4, or other Intel-specific SIMD won't run on ARM

Migration Path: Checklist Before Switching

Moving from Intel to Graviton is straightforward for most workloads. Follow this checklist:

1. Audit your software stack — Verify that every binary, agent, and library in your AMI or container has an ARM64 build. Interpreted languages (Python, Node, Java) are usually fine.
2. Build multi-arch Docker images — If you use containers, set up docker buildx to produce both linux/amd64 and linux/arm64 images from a single Dockerfile.
3. Choose the right AMI — Use an ARM64 AMI (Amazon Linux 2023 arm64, Ubuntu 22.04 arm64). Confirm with aws ec2 describe-images --filters “Name=architecture,Values=arm64”.
4. Test in staging first — Launch a Graviton instance alongside your existing Intel instance. Run your full test suite and load tests. Compare performance and correctness.
5. Monitor for regressions — Watch CPU, memory, latency, and error rates for 1–2 weeks before fully switching production traffic.
6. Update IaC and auto-scaling — Update your Terraform, CloudFormation, or CDK templates to use Graviton instance types. Update launch templates in Auto Scaling groups.

Frequently Asked Questions

Are Graviton instances cheaper?

Yes. Graviton instances are consistently ~20% cheaper per hour than their Intel equivalents at the same size. For example, c6g.large costs $0.0680/hr vs $0.0850/hr for c6i.large in us-east-1. This discount applies across all sizes and all regions.

Can I run Docker on Graviton?

Yes. Docker works natively on Graviton instances. You need ARM64 container images, which most popular base images already provide via multi-arch manifests. Run docker buildx build --platform linux/amd64,linux/arm64 . to create images that work on both architectures.

Is Graviton faster than Intel?

For most general-purpose workloads, Graviton3 matches or exceeds Intel Xeon performance at the same vCPU count. Graviton2 is within 5% of Intel in raw benchmarks. The real story is price-performance: because Graviton costs 20% less, you get significantly more compute per dollar spent, even in cases where raw single-core performance is marginally lower.