r9g.48xlarge by Amazon Web Services
(All-cores)
(Single-core)
Specifications
Server Metadata
Vendor ID | aws |
Name | r9g.48xlarge |
Description | Memory optimized [AWS Graviton processors] Gen9 48xlarge |
Family | r9g |
Hw Virt | - |
Status | active |
Observed At | 2026-09-03T00:20:24.463537 |
Availability
| REGION / ID | SPOT | ONDEMAND |
|---|---|---|
Ohio (US) / us-east-2 | 2.9568 USD/h | 12.3283 USD/h |
Oregon (US) / us-west-2 | 4.88145 USD/h | 12.3283 USD/h |
Northern Virgina (US) / us-east-1 | 4.967275 USD/h | 12.3283 USD/h |
Frankfurt (DE) / eu-central-1 | 6.432067 USD/h | 14.8723 USD/h |
Processor
vCPUs | 192 |
Hypervisor | nitro |
CPU Allocation | Dedicated |
CPU Cores | 192 |
CPU Speed | 3.3 GHz |
CPU Architecture | arm64 |
CPU Manufacturer | AWS |
System Resources and Accelerators
| MEMORY | |
|---|---|
Memory Amount | 2 TB |
| GPU | |
|---|---|
GPU Count | 0 |
GPU Memory Min | 0 MiB |
GPU Memory Total | 0 MiB |
GPUs |
| STORAGE | |
|---|---|
Storage Size | 0 GB |
Storages |
| NETWORK | |
|---|---|
Network Speed Baseline | 100 Gbps |
Network Speed Max | 100 Gbps |
Network Storage Speed Baseline | 72 Gbps |
Network Storage Speed Max | 72 Gbps |
Inbound Traffic | 0 GB/month |
Outbound Traffic | 0 GB/month |
IPv4 | 0 |
Server Description
An arm64 memory-optimized instance featuring one hundred ninety-two dedicated physical cores, over one terabyte of RAM, and high-speed network connectivity.
Amazon Web Services r9g.48xlarge is a memory-optimized server instance powered by custom AWS Graviton arm64 processors running at 3.3 GHz. Built on the AWS Nitro hypervisor, the instance features 192 dedicated physical cores with a single thread per core and is equipped with 1536.0 GB of system memory, establishing an 8.0 GB per core ratio. It does not contain local storage or GPU hardware, but provides a baseline network bandwidth of 100 Gbps. The high core count and memory density of this arm64 architecture deliver qualitative cost efficiency for large-scale deployments. This instance is designed for memory-intensive workloads such as in-memory databases, distributed caching, and large-scale data analytics.
Economics
Alternatives
Servers of the Same Family
| INSTANCE | vCPUs | MEMORY | GPUs |
|---|---|---|---|
| r9g.medium | 1 | 8 GiB | 0 |
| r9g.large | 2 | 16 GiB | 0 |
| r9g.xlarge | 4 | 32 GiB | 0 |
| r9g.2xlarge | 8 | 64 GiB | 0 |
| r9g.4xlarge | 16 | 128 GiB | 0 |
| r9g.8xlarge | 32 | 256 GiB | 0 |
| r9g.12xlarge | 48 | 384 GiB | 0 |
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