c9gd.16xlarge by Amazon Web Services
(All-cores)
(Single-core)
Specifications
Server Metadata
Vendor ID | aws |
Name | c9gd.16xlarge |
Description | Compute optimized [AWS Graviton processors] [Instance store volumes] Gen9 16xlarge |
Family | c9gd |
Hw Virt | - |
Status | active |
Observed At | 2026-07-22T00:53:27.543171 |
Availability
| REGION / ID | SPOT | ONDEMAND |
|---|---|---|
Ohio (US) / us-east-2 | 0.853133 USD/h | 3.4176 USD/h |
Northern Virgina (US) / us-east-1 | 1.0275 USD/h | 3.4176 USD/h |
Oregon (US) / us-west-2 | 1.160825 USD/h | 3.4176 USD/h |
Frankfurt (DE) / eu-central-1 | 1.1687 USD/h | 3.952 USD/h |
Processor
vCPUs | 64 |
Hypervisor | nitro |
CPU Allocation | Dedicated |
CPU Cores | 64 |
CPU Speed | 2.8 GHz |
CPU Architecture | arm64 |
CPU Manufacturer | AWS |
System Resources and Accelerators
| MEMORY | |
|---|---|
Memory Amount | 128 GiB |
| GPU | |
|---|---|
GPU Count | 0 |
GPU Memory Min | 0 MiB |
GPU Memory Total | 0 MiB |
GPUs |
| STORAGE | |
|---|---|
Storage Size | 3800 GB |
Storage Type | nvme ssd |
Storages |
|
| NETWORK | |
|---|---|
Network Speed Baseline | 34 Gbps |
Network Speed Max | 34 Gbps |
Network Storage Speed Baseline | 24 Gbps |
Network Storage Speed Max | 24 Gbps |
Inbound Traffic | 0 GB/month |
Outbound Traffic | 0 GB/month |
IPv4 | 0 |
Server Description
A dedicated arm64 compute-optimized instance featuring high-speed local NVMe storage and balanced memory for intensive processing workloads.
Amazon Web Services c9gd.16xlarge is a compute-optimized server powered by 64-core AWS Graviton arm64 processors running at 2.8 GHz. Utilizing the AWS Nitro hypervisor, the instance provides 64 dedicated vCPUs with a single thread per core, ensuring consistent performance for compute-heavy tasks. It features 128.0 GB of system memory, establishing a 2.0 GB per core ratio. Storage needs are met by 3800 GB of local NVMe SSD instance store volumes, which deliver high-speed, low-latency data access. Additionally, the server supports a baseline network bandwidth of 34 Gbps. This hardware profile makes the c9gd.16xlarge highly efficient for workloads requiring a balance of dedicated arm64 compute power and fast local storage, such as distributed databases, batch processing, and web serving.
Economics
Alternatives
Servers of the Same Family
| INSTANCE | vCPUs | MEMORY | GPUs |
|---|---|---|---|
| c9gd.medium | 1 | 2 GiB | 0 |
| c9gd.large | 2 | 4 GiB | 0 |
| c9gd.xlarge | 4 | 8 GiB | 0 |
| c9gd.2xlarge | 8 | 16 GiB | 0 |
| c9gd.4xlarge | 16 | 32 GiB | 0 |
| c9gd.8xlarge | 32 | 64 GiB | 0 |
| c9gd.12xlarge | 48 | 96 GiB | 0 |
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