Cloud Services > Azure > E20ads_v5
Experience our Interactive Instance Data Table

E20ads_v5

The 'E' family of VM size series are one of Azure's memory-optimized VM instances.

The E20ads_v5 is a azure vm instance type featuring multiple vCPUs and optimized memory, commonly used for vm workloads.

Last updated at Thu May 28 2026
Instance Info
Compute Value
vCPUs 20
Memory (GB) 160
CPU Architecture x64
Capacity Support True
VM Generations V1,V2
VM Deployment Types PaaS,IaaS
Network Value
Accelerated Networking True
Storage Value
Local Temp Storage (MB) 768000
Cache/Temp Storage Throughput (IOPS) 94000
Cache/Temp Storage Read/Write Throughput (Bytes/s) 1250000000
Uncached Disk Throughput (IOPS) 32000
Uncached Disk Read/Write Throughput (Bytes/s) 480000000
Premium I/O True
Ultra Disks Supported False, True
Encryption True
Memory Maintenance True
Family Instances
Instance vCPUs Memory
E2ads_v5 2 16
E4-2ads_v5 4 32
E4ads_v5 4 32
E8-2ads_v5 8 64
E8-4ads_v5 8 64
E8ads_v5 8 64
E16-4ads_v5 16 128
E16-8ads_v5 16 128
E16ads_v5 16 128
E20ads_v5 20 160
E32-16ads_v5 32 256
E32-8ads_v5 32 256
E32ads_v5 32 256
E48ads_v5 48 384
E64-16ads_v5 64 512
E64-32ads_v5 64 512
E64ads_v5 64 512
E96-24ads_v5 96 672
E96-48ads_v5 96 672
E96ads_v5 96 672
Related Instances
Instance vCPUs Memory
E20as_v4 20 160
E20as_v5 20 160
E20as_v6 20 160
E20a_v4 20 160
E20ads_v6 20 160
21 Practical Azure Cost Optimization Techniques To Implement Today

21 Practical Azure Cost Optimization Techniques To Implement Today

Discover over 21 Azure cost optimization best practices you can implement now to reduce spending and maximize your cloud ROI.

Read more
AWS Vs. Azure: How To Choose The Right Cloud Provider

AWS Vs. Azure: How To Choose The Right Cloud Provider

Trying to decide which cloud provider is best for you? Check out our comprehensive guide on how AWS and Azure compare.

Read more
A Guide To Azure Database Pricing (And Reducing Costs)

A Guide To Azure Database Pricing (And Reducing Costs)

Confused by Azure database pricing? We explain how it works and share tips to optimize costs across SQL, Cosmos DB, PostgreSQL, and beyond.

Read more