Amazon EC2 C9g and C9gd instances powered by AWS Graviton5 processors are now available

When you run compute-intensive workloads like real-time analytics, batch processing, video encoding, scientific modeling, or CPU-based machine learning inference, every percentage point of performance matters. You need instances that deliver higher throughput per vCPU, faster memory access, and more network bandwidth, all while keeping your costs in check.

Today I am happy to announce the general availability of Amazon Elastic Compute Cloud (Amazon EC2) C9g and C9gd instances, powered by AWS Graviton5 processors. C9g instances are compute-optimized and deliver up to 25% higher performance per vCPU compared to previous-generation C8g instances. They feature the fastest memory of any processor instance in the cloud, with DDR5 8800MT/s DIMMs, 5x more L3 cache, and up to 3x higher packet-processing performance compared to Graviton4-based instances. The faster memory and larger caches mean your workloads spend less time waiting on data, translating into higher throughput for in-memory analytics, faster agentic loops, and more responsive real-time applications.

C9g instances are ideal for batch jobs, video encoding pipelines, or distributed analytics that can utilize Amazon Elastic Block Store (Amazon EBS) for storage. It is also a natural fit for agentic AI workloads, where concurrent environments and CPU-bound reasoning steps benefit from Graviton5’s higher core count and larger caches. As AI shifts from answering questions to taking actions, running code, and orchestrating multi-step tasks, the demand for CPU compute is growing, and C9g instances are built for this shift.

Some workloads also need fast local storage alongside that compute power. Choose C9gd when your application benefits from high-speed, low-latency local NVMe SSD storage, for example scratch space during HPC simulations, temporary caches for ML inference, or local buffers for ad-serving engines.

Graviton5-based instances with NVMe instance store volumes also support detailed performance statistics, providing high-resolution I/O metrics, including latency histograms broken down by I/O size, up to 1-second granularity and accessible via Amazon CloudWatch or nvme-cli at no additional cost.

C9g and C9gd instances at a glance

C9g and C9gd instances are available in 11 sizes ranging from medium to 48xlarge, plus a bare metal option. They offer up to 15% higher network bandwidth and 20% higher EBS bandwidth on average across sizes compared to the previous generation, with the largest 48xlarge size delivering up to 100 Gbps of network bandwidth and up to 72 Gbps of EBS bandwidth, a 2x increase.

C9g

vCPUs

Memory

(GiB)

Network Bandwidth

(Gbps)

EBS Bandwidth

(Gbps)

medium

1

2

Up to 15

Up to 12

large

2

4

Up to 15

Up to 12

xlarge

4

8

Up to 15

Up to 12

2xlarge

8

16

Up to 17

Up to 12

4xlarge

16

32

Up to 17

Up to 12

8xlarge

32

64

17

12

12xlarge

48

96

25

18

16xlarge

64

128

34

24

24xlarge

96

192

50

36

48xlarge

192

384

100

72

metal-48xl

192

384

100

72

C9gd instances add local NVMe SSD storage with up to 30% higher storage performance compared to previous-generation local storage instances.

C9gd

vCPUs

Memory

(GiB)

Instance Storage

(GB)

Network Bandwidth

(Gbps)

EBS Bandwidth

(Gbps)

medium

1

2

1 x 59

Up to 15

Up to 12

large

2

4

1 x 118

Up to 15

Up to 12

xlarge

4

8

1 x 237

Up to 15

Up to 12

2xlarge

8

16

1 x 474

Up to 17

Up to 12

4xlarge

16

32

1 x 950

Up to 17

Up to 12

8xlarge

32

64

1 x 1900

17

12

12xlarge

48

96

3 x 950

25

18

16xlarge

64

128

1 x 3800

34

24

24xlarge

96

192

3 x 1900

50

36

48xlarge

192

384

3 x 3800

100

72

metal-48xl

192

384

3 x 3800

100

72

Both families are well-suited for high-performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning inference, and ad serving.

Here are some additional capabilities:

Instance Bandwidth Configuration (IBC) lets you adjust the allocation of bandwidth between Amazon EBS and Amazon VPC networking by up to 25%, helping you optimize performance for workloads with specific bandwidth requirements such as databases and caching.

ENA Express support for enhanced networking.

Up to 128 EBS volumes can be attached to virtual instances.

Support for Savings Plans, On-Demand, Spot Instances, Dedicated Instances, and Dedicated Hosts.

Nitro Isolation Engine

Security and isolation are foundational requirements for running workloads in the cloud. Within the Nitro System, the AWS Nitro Hypervisor is designed to isolate instances from each other as well as AWS operators. With C9g and C9gd instances we are raising the bar even further with the Nitro Isolation Engine, an enhancement to the Nitro System, which enforces isolation of instances and harnesses formal verification to provide assurances of isolation with mathematical precision. C9g and C9gd instances are the first set of compute-optimized instance types to feature Nitro Isolation Engine, a purpose built component that is responsible for enforcing isolation between virtual machines, including mediation of all access to virtual machine memory, CPU register state, and I/O devices through a minimal set of APIs.

To learn more about the Nitro Isolation Engine, visit the blog post. For details on the formal verification results, including scope and assumptions, see our technical white paper.

Now available

Amazon EC2 C9g and C9gd instances are now available in US East (Ohio, N. Virginia), US West (Oregon), and Europe (Frankfurt). Additional regions will follow.

You can launch C9g and C9gd instances today using the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs. For pricing information, visit the Amazon EC2 Pricing page.

To learn more, visit the Amazon EC2 C9g and C9gd instances page and send feedback to AWS re:Post for EC2 or through your usual AWS Support contacts.

— seb Editor’s Note: Updated 7/1/2026- Paragraph about Nitro Isolation Engine rewritten for clarity.