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AWS Graviton3 vs Intel vs AMD: Real-World Cost Savings and Performance Benchmarks

📅 November 2025⏱️ 8 min read✍️ TCOIQ Team

The Graviton Promise

AWS claims Graviton3 delivers "up to 40% better price-performance" than equivalent Intel and AMD instances. Let's verify this with real pricing data.

Graviton3 vs Intel vs AMD — Verified Pricing

CategoryGraviton3Intel (latest)AMD (latest)Graviton3 vs Intel
General 2vCPU/8GBm7g.large $0.0816m7i.large $0.1008m7a.large $0.1073-19% vs Intel
General 8vCPU/32GBm7g.2xlarge $0.3264m7i.2xlarge $0.4032m7a.2xlarge $0.4290-19% vs Intel
Compute 4vCPU/8GBc7g.xlarge $0.1450c7i.xlarge $0.1786c7a.xlarge $0.1769-19% vs Intel
Memory 8vCPU/64GBr7g.2xlarge $0.4271r7i.2xlarge $0.5292-19% vs Intel

The pricing advantage is consistent at ~19% cheaper than equivalent Intel and ~25% cheaper than AMD for Linux workloads.

Workloads Best Suited for Graviton

  • Web application servers (Node.js, Python, Ruby, Go)
  • API gateways and microservices
  • Containers and Kubernetes (EKS)
  • Java applications (OpenJDK excellent on Graviton)
  • Big data processing (Spark, Kafka)
  • Media encoding (FFMPEG)

Workloads That Don't Migrate Easily

  • Windows applications (no Windows support on Graviton)
  • Applications with x86-specific compiled dependencies
  • Legacy .NET Framework (not .NET Core)
  • Some database binaries (verify with vendor)

Real Savings Example — 50-Node Web Cluster

ConfigurationInstanceMonthly CostAnnual Cost
Current (m7i.xlarge)50× $0.2016/hr$7,378$88,534
Graviton3 (m7g.xlarge)50× $0.1632/hr$5,957$71,462
Saving$1,421/mo$17,072/yr

Migration Effort

Most containerised applications: rebuild container images with multi-arch (ARM64 + AMD64) support — typically 1-2 days. Native applications: recompile for ARM64, run test suite. For most modern languages, this is straightforward. Oracle-specific note: if your Java application uses specific JVM flags or commercial extensions, test thoroughly before migration.

For any new deployment, default to Graviton3. For existing deployments, run a 1-week side-by-side test on a subset of nodes. The 19% saving is virtually guaranteed for Linux workloads.

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