Skip to content

AWS C7g Instances: Next-Generation Compute with AWS Graviton3

AWS has steadily evolved its compute-optimized EC2 families to deliver higher performance and better cost efficiency. The C7g family is the latest in this line, powered by the AWS Graviton3 processors—custom silicon designed by AWS using Arm architecture. With significant performance improvements over Graviton2-based C6g instances, C7g is ideal for modern compute-intensive workloads.

What Are C7g Instances?

C7g instances are compute-optimized EC2 instances that leverage the third-generation AWS Graviton3 processors. These processors deliver:

  • Up to 25% better performance over Graviton2 (C6g).
  • Up to 2× better floating-point performance—critical for scientific and AI workloads.
  • Up to 2× faster cryptographic performance—ideal for security-sensitive applications.
  • Up to 3× better machine learning (ML) inference performance compared to Graviton2.

Key Features

  • Processor: AWS Graviton3 (64-bit Arm Neoverse V1 cores)
  • Architecture: Arm-based (AArch64)
  • vCPUs: From 1 to 64 depending on instance size
  • Memory: 2 GiB per vCPU (same ratio as C6g)
  • Networking: Up to 30 Gbps with Elastic Network Adapter (ENA)
  • EBS Bandwidth: Up to 20 Gbps
  • Nitro System: Secure, lightweight hypervisor with hardware acceleration
  • Sustainability: Up to 60% less energy usage for the same performance compared to comparable x86 instances

Instance Sizes

C7g instances come in a variety of sizes to suit different workloads:

  • c7g.medium – 1 vCPU, 2 GiB RAM
  • c7g.large – 2 vCPUs, 4 GiB RAM
  • c7g.xlarge – 4 vCPUs, 8 GiB RAM
  • c7g.2xlarge – 8 vCPUs, 16 GiB RAM
  • c7g.4xlarge – 16 vCPUs, 32 GiB RAM
  • c7g.8xlarge – 32 vCPUs, 64 GiB RAM
  • c7g.12xlarge – 48 vCPUs, 96 GiB RAM
  • c7g.16xlarge – 64 vCPUs, 128 GiB RAM

Use Cases

C7g instances are ideal for modern compute-heavy applications where performance and efficiency are critical:

  • High-performance computing (HPC)
  • Machine learning inference
  • Scientific modeling and simulations
  • Media encoding and transcoding
  • Cryptographic workloads (TLS termination, VPNs, data encryption)
  • Web servers, microservices, and containerized applications

Benefits of Choosing C7g

  1. Next-Level Performance – Faster than C6g, especially for floating-point, cryptographic, and ML workloads.
  2. Energy Efficiency – Up to 60% less energy usage, aligning with sustainability goals.
  3. Cost Savings – Better price-performance compared to x86 instances.
  4. Scalability – From small microservices to large-scale compute clusters.
  5. Future-Proof – Designed for modern workloads that benefit from specialized acceleration.

C7g vs. Other Compute-Optimized Families

  • C6g – Graviton2-powered, cost-efficient but slower than C7g.
  • C7g – Graviton3-powered, offering the best Arm performance for compute workloads.
  • C6i – Intel Xeon Scalable (x86), for workloads requiring Intel-specific features.
  • C6a – AMD EPYC (x86), generally cheaper than Intel but less efficient than Graviton.

If your workloads are Arm-compatible and performance-critical, C7g is the best option today.

Things to Keep in Mind

  • Arm Compatibility – Like C6g, applications must be compiled for Arm64 (AArch64). Most modern stacks already support this (Docker, Kubernetes, major Linux distros, databases, and runtimes like Python, Java, Node.js, etc.).
  • Memory Ratio – Same as C6g (2 GiB per vCPU). If you need higher memory per vCPU, consider general-purpose (M7g) or memory-optimized (R7g) families.

Conclusion

AWS C7g instances represent a leap forward in compute-optimized performance, powered by the Graviton3 processor. With substantial improvements in floating-point, cryptography, and ML inference, they enable businesses to run demanding workloads more efficiently and at lower cost.

For organizations aiming to combine performance, sustainability, and cost efficiency, C7g stands out as the flagship compute-optimized Arm option on AWS.