Azure Dasv7 VM sizes
Dasv7 is a general purpose Azure Virtual Machines family with 10 VM sizes, from 2 – 160 vCPUs and 8 GiB – 640 GiB of memory, running on AMD EPYC 9005 (Turin). Linux on demand starts at $0.0908 per hour.
general purposex86-64
- sizes
- 10
- vCPUs
- 2 – 160
- memory
- 8 GiB – 640 GiB
- processor
- AMD EPYC 9005 (Turin)
- on-demand from
- $0.0908
per hour · 33 regions
Dasv7 sizes and prices
Linux, hourly, East US (other regions on each size's page)
| Size | vCPU | Memory | Local storage | On-demand | Monthly | Spot | 1-yr |
|---|---|---|---|---|---|---|---|
| D2as v7 | 2 | 8 GiB | – | $0.0908 | $66.28 | $0.0176 | $0.0535 |
| D4as v7 | 4 | 16 GiB | – | $0.182 | $133 | $0.0353 | $0.1072 |
| D8as v7 | 8 | 32 GiB | – | $0.363 | $265 | $0.0704 | $0.2143 |
| D16as v7 | 16 | 64 GiB | – | $0.726 | $530 | $0.1408 | $0.4285 |
| D32as v7 | 32 | 128 GiB | – | $1.453 | $1,061 | $0.2819 | $0.8572 |
| D48as v7 | 48 | 192 GiB | – | $2.179 | $1,591 | $0.4227 | $1.286 |
| D64as v7 | 64 | 256 GiB | – | $2.906 | $2,121 | $0.5638 | $1.714 |
| D96as v7 | 96 | 384 GiB | – | $4.358 | $3,181 | $0.8455 | $2.571 |
| D128as v7 | 128 | 512 GiB | – | $5.811 | $4,242 | $1.127 | $3.429 |
| D160as v7 | 160 | 640 GiB | – | $7.264 | $5,303 | $1.409 | $4.286 |
Dasv7 equivalents on other clouds
closest match to D32as v7 (32 vCPU, 128 GiB)
AkamaiG8 Dedicated 128x32Dedicated CPU (G8) family · 32 vCPU · 128 GiB$1.68/hr · Newark, NJDedicated CPU (G8) family →
Vultrvx1-g-32c-128gVX1: General Purpose family · 32 vCPU · 128 GiB$0.96/hr · New JerseyVX1: General Purpose family →
Other general purpose families on Azure
Dasv7 FAQ
What sizes does the Azure Dasv7 family have?
Dasv7 has 10 VM sizes, from D2as v7 (2 vCPU, 8 GiB) to D160as v7 (160 vCPU, 640 GiB). They run on AMD EPYC 9005 (Turin).
What is the cheapest Dasv7 VM size?
D2as v7 at $0.0908 per hour (Linux, on demand) in East US, about $66.28 per month.
What is Dasv7 best for?
Dasv7 is a general purpose family. Balanced CPU and memory (about 4 GiB per vCPU) for web apps, services and most workloads.