AWS M7gd instance types
M7gd is a general purpose Amazon EC2 family with 9 instance types, from 1 – 64 vCPUs and 4 GiB – 256 GiB of memory, running on AWS Graviton3 Processor. Linux on demand starts at $0.0534 per hour.
general purposearm64
- sizes
- 9
- vCPUs
- 1 – 64
- memory
- 4 GiB – 256 GiB
- processor
- AWS Graviton3 Processor
- on-demand from
- $0.0534
per hour · 22 regions
M7gd sizes and prices
Linux, hourly, US East (N. Virginia) (other regions on each size's page)
| Size | vCPU | Memory | Local storage | On-demand | Monthly | Spot | 1-yr |
|---|---|---|---|---|---|---|---|
| m7gd.medium | 1 | 4 GiB | 59 GB NVME | $0.0534 | $38.98 | $0.0215 | $0.0336 |
| m7gd.large | 2 | 8 GiB | 118 GB NVME | $0.1068 | $77.96 | $0.0452 | $0.0673 |
| m7gd.xlarge | 4 | 16 GiB | 237 GB NVME | $0.2136 | $156 | $0.0909 | $0.1345 |
| m7gd.2xlarge | 8 | 32 GiB | 475 GB NVME | $0.4271 | $312 | $0.1869 | $0.2691 |
| m7gd.4xlarge | 16 | 64 GiB | 950 GB NVME | $0.8543 | $624 | $0.3838 | $0.5382 |
| m7gd.8xlarge | 32 | 128 GiB | 1.9 TB NVME | $1.709 | $1,247 | $0.6849 | $1.076 |
| m7gd.12xlarge | 48 | 192 GiB | 2.9 TB NVME (2 disks) | $2.563 | $1,871 | $1.063 | $1.615 |
| m7gd.16xlarge | 64 | 256 GiB | 3.8 TB NVME (2 disks) | $3.417 | $2,494 | $1.436 | $2.153 |
| m7gd.metal | 64 | 256 GiB | 3.8 TB NVME (2 disks) | $3.417 | $2,494 | $0.8565 | $2.153 |
M7gd equivalents on other clouds
closest match to m7gd.4xlarge (16 vCPU, 64 GiB)
AkamaiG8 Dedicated 64x16Dedicated CPU (G8) family · 16 vCPU · 64 GiB$0.84/hr · Newark, NJDedicated CPU (G8) family →
Other general purpose families on AWS
M7gd FAQ
What sizes does the AWS M7gd family have?
M7gd has 9 instance types, from m7gd.medium (1 vCPU, 4 GiB) to m7gd.metal (64 vCPU, 256 GiB). They run on AWS Graviton3 Processor.
What is the cheapest M7gd instance type?
m7gd.medium at $0.0534 per hour (Linux, on demand) in US East (N. Virginia), about $38.98 per month.
What is M7gd best for?
M7gd is a general purpose family. Balanced CPU and memory (about 4 GiB per vCPU) for web apps, services and most workloads.