c9gd.2xlarge

Amazon EC2 · C9gd family

The c9gd.2xlarge is a compute optimized Amazon EC2 instance type with 8 vCPUs and 16 GiB of memory, running on AWS Graviton5 Processor with up to 17 Gigabit networking, starting at $0.4236 per hour on demand.

compute optimizedarm64aws graviton
vCPUs
8

dedicated

memory
16 GiB

2 GiB per vCPU

processor
Graviton

3.3 GHz

on-demand
$0.4272

$312/mo · us-east-1

spot
–

not offered

regions
8

across 3 areas

c9gd.2xlarge price by region

8 regions · hourly list prices in USD · On-demand · Spot · 1-yr Reserved · 3-yr Reserved

Asia Pacific (Malaysia)ap-southeast-5cheapestAsia$0.4236
US East (N. Virginia)us-east-1referenceNorth America$0.4272
US East (Ohio)us-east-2North America$0.4272
US West (Oregon)us-west-2North America$0.4272
Asia Pacific (Seoul)ap-northeast-2Asia$0.4895
EU (Frankfurt)eu-central-1Europe$0.494
Asia Pacific (Singapore)ap-southeast-1Asia$0.4983
Asia Pacific (Tokyo)ap-northeast-1Asia$0.5429

Specifications

compute

vCPUs
8
Memory
16 GiB
Memory per vCPU
2 GiB
Processor
AWS Graviton5 Processor
CPU vendor
AWS Graviton
Architecture
Arm64
Clock speed
3.3 GHz
Burstable CPU
No

storage & network

Local storage
474 GB NVME
Storage detail
1 x 474 NVMe SSD
Network
Up to 17 Gigabit
Peak bandwidth
17 Gbps

aws details

API name
c9gd.2xlarge
Family
C9gd
Category
Compute optimized
Generation
Current
Regions
8 (Asia, Europe, North America)
Cheapest region
Asia Pacific (Malaysia) · $0.4236/hr
Dedicated EBS throughput
Up to 12000 Mbps
Enhanced networking
Yes
Normalization size factor
16

c9gd.2xlarge equivalents on other clouds

closest match by vCPU, memory, CPU architecture, accelerator and class · Linux on-demand in each provider's reference region

compare side by side→
ProviderInstancevCPUMemoryProcessorOn-demandvs c9gd.2xlarge
AWSc9gd.2xlarge816 GiBAWS Graviton5 Processor$0.4272–
AzureD8plds v5816 GiBAmpere Altra$0.307-28%
D8plds v6816 GiBAzure Cobalt 100$0.312-27%
Google Cloudn4a-highcpu-8816 GiBGoogle Axion$0.2598-39%
c4a-highcpu-8816 GiBGoogle Axion$0.303-29%
AkamaiDedicated 16GBx86 CPU816 GiBAMD EPYC$0.216-49%
G7 Dedicated 16x8x86 CPU816 GiBAMD EPYC$0.2595-39%
Vultrvoc-c-8c-16gb-150s-amdx86 CPU816 GiBAMD EPYC$0.219-49%
voc-c-8c-16gb-300s-amdx86 CPU816 GiBAMD EPYC$0.247-42%

C9gd family sizes

all about C9gd→
SizevCPUMemoryLocal storageOn-demandMonthly
c9gd.medium12 GiB59 GB NVME$0.0534$38.98
c9gd.large24 GiB118 GB NVME$0.1068$77.96
c9gd.xlarge48 GiB237 GB NVME$0.2136$156
c9gd.2xlarge816 GiB474 GB NVME$0.4272$312
c9gd.4xlarge1632 GiB950 GB NVME$0.8544$624
c9gd.8xlarge3264 GiB1.9 TB NVME$1.709$1,247
c9gd.12xlarge4896 GiB2.9 TB NVME (3 disks)$2.563$1,871
c9gd.16xlarge64128 GiB3.8 TB NVME$3.418$2,495
c9gd.24xlarge96192 GiB5.7 TB NVME (3 disks)$5.126$3,742
c9gd.48xlarge192384 GiB11.4 TB NVME (3 disks)$10.25$7,485
c9gd.metal-48xl192384 GiB11.4 TB NVME (3 disks)$10.25$7,485

Similar instance types on AWS

other AWS families with a similar shape, cheapest first

c9gd.2xlarge FAQ

How much does c9gd.2xlarge cost?

c9gd.2xlarge costs $0.4272 per hour on demand with Linux in US East (N. Virginia) (us-east-1), about $312 per month. Across 8 regions the Linux on-demand price ranges from $0.4236 in Asia Pacific (Malaysia) to $0.5429 in Asia Pacific (Tokyo).

How many vCPUs and how much memory does c9gd.2xlarge have?

c9gd.2xlarge has 8 vCPUs and 16 GiB of memory (2 GiB per vCPU), running on AWS Graviton5 Processor. It is a compute optimized instance type in the C9gd family.

What is the cheapest region for c9gd.2xlarge?

Asia Pacific (Malaysia) (ap-southeast-5) at $0.4236 per hour for Linux on demand, 1% less than US East (N. Virginia). c9gd.2xlarge is sold in 8 AWS regions.

What are the equivalents of c9gd.2xlarge on other clouds?

The closest matches by vCPU, memory, CPU architecture and instance class are on Azure, D8plds v5 (8 vCPU, 16 GiB, $0.307/hour in East US); on Google Cloud, n4a-highcpu-8 (8 vCPU, 16 GiB, $0.2598/hour in Iowa); on Akamai, Dedicated 16GB (8 vCPU, 16 GiB, $0.216/hour in Newark, NJ); on Vultr, voc-c-8c-16gb-150s-amd (8 vCPU, 16 GiB, $0.219/hour in New Jersey).