(All-cores)
(Single-core)
Specifications
Server Metadata
Vendor ID | aws |
Name | r9gd.2xlarge |
Description | Memory optimized [AWS Graviton processors] [Instance store volumes] Gen9 2xlarge |
Family | r9gd |
Hw Virt | - |
Status | active |
Observed At | 2026-10-16T06:58:04.995983 |
Availability
| REGION / ID | SPOT | ONDEMAND |
|---|---|---|
Ohio (US) / us-east-2 | 0.130667 USD/h | 0.6407 USD/h |
Oregon (US) / us-west-2 | 0.211175 USD/h | 0.6407 USD/h |
Northern Virgina (US) / us-east-1 | 0.2608 USD/h | 0.6407 USD/h |
Frankfurt (DE) / eu-central-1 | 0.312 USD/h | 0.7698 USD/h |
Processor
vCPUs | 8 |
Hypervisor | nitro |
CPU Allocation | Dedicated |
CPU Cores | 8 |
CPU Speed | 3.3 GHz |
CPU Architecture | arm64 |
CPU Manufacturer | AWS |
System Resources and Accelerators
| MEMORY | |
|---|---|
Memory Amount | 64 GiB |
| ACCELERATORS | |
|---|---|
Accelerator Count | 0 |
Accelerator Memory Min | 0 MiB |
Accelerator Memory Total | 0 MiB |
Accelerators |
| STORAGE | |
|---|---|
Storage Size | 474 GB |
Storage Type | nvme ssd |
Storages |
|
| NETWORK | |
|---|---|
Network Speed Baseline | 4.25 Gbps |
Network Speed Max | 17 Gbps |
Network Storage Speed Baseline | 3 Gbps |
Network Storage Speed Max | 12 Gbps |
Inbound Traffic | 0 GB/month |
Outbound Traffic | 0 GB/month |
IPv4 | 0 |
Server Description
An ARM64 memory-optimized instance featuring dedicated Graviton cores, high memory density, and integrated high-speed local NVMe SSD storage.
Amazon Web Services r9gd.2xlarge is a memory-optimized instance powered by custom AWS Graviton ARM64 processors. Operating on the AWS Nitro hypervisor, it features 8 dedicated physical cores running at 3.3 GHz with a single thread per core. The instance provides 64.0 GB of system memory, establishing a high 8.0 GB per core ratio designed for memory-intensive applications. Storage is supported by a bundled 474 GB local NVMe SSD instance store volume, offering high-speed local data access. Network performance is defined by a baseline bandwidth of 4 Gbps. This hardware profile delivers qualitative cost efficiency by leveraging energy-efficient ARM architecture alongside dense memory and local storage resources. It is suited for workloads such as in-memory databases, caching layers, and data analytics pipelines requiring fast local scratch space.
Economics
Alternatives
Servers of the Same Family
| INSTANCE | vCPUs | MEMORY | Accelerators |
|---|---|---|---|
| r9gd.medium | 1 | 8 GiB | 0 |
| r9gd.large | 2 | 16 GiB | 0 |
| r9gd.xlarge | 4 | 32 GiB | 0 |
| r9gd.4xlarge | 16 | 128 GiB | 0 |
| r9gd.8xlarge | 32 | 256 GiB | 0 |
| r9gd.12xlarge | 48 | 384 GiB | 0 |
| r9gd.16xlarge | 64 | 512 GiB | 0 |
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