u7in-32tb.224xlarge by Amazon Web Services
(All-cores)
(Single-core)
Specifications
Server Metadata
Vendor ID | aws |
Name | u7in-32tb.224xlarge |
Description | High memory [Intel processors] [Network and EBS optimized] Gen7 224xlarge |
Family | u7in-32tb |
Hw Virt | - |
Status | active |
Observed At | 2026-07-23T06:51:14.222559 |
Availability
| REGION / ID | SPOT | ONDEMAND |
|---|---|---|
Northern Virgina (US) / us-east-1 | - | 360.9869 USD/h |
Oregon (US) / us-west-2 | - | 360.9869 USD/h |
Processor
vCPUs | 896 |
Hypervisor | nitro |
CPU Allocation | Dedicated |
CPU Cores | 448 |
CPU Speed | 1.9 GHz |
CPU Architecture | x86_64 |
CPU Manufacturer | Intel |
System Resources and Accelerators
| MEMORY | |
|---|---|
Memory Amount | 32 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 | 100 Gbps |
Network Storage Speed Max | 100 Gbps |
Inbound Traffic | 0 GB/month |
Outbound Traffic | 0 GB/month |
IPv4 | 0 |
Server Description
An ultra-high-memory instance featuring thirty-two terabytes of RAM and eight hundred ninety-six vCPUs for massive in-memory enterprise workloads.
Amazon Web Services u7in-32tb.224xlarge is an ultra-high-memory instance designed for workloads requiring massive RAM capacity. Operating on the AWS Nitro hypervisor, this x86_64 architecture instance is powered by Intel processors with 896 dedicated vCPUs across 448 physical cores running at 1.9 GHz. It features an exceptional 32,768.0 GB of system memory, providing 36.57 GB of RAM per core. The instance does not include local storage or GPUs, relying instead on network-attached storage supported by a baseline network bandwidth of 100 Gbps. This configuration is optimized for network and EBS performance, making it highly efficient for memory-bound enterprise applications. It is best suited for massive in-memory databases, large-scale SAP HANA installations, and heavy real-time data processing workloads.
Economics
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