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Machine Learning Platform for AI:Billing of EAS

Last Updated:Sep 22, 2023

This topic describes how Elastic Algorithm Service (EAS) is billed.

Billable resources

The following figure shows how EAS is billed. 计费项

billing method

The following table describes the billing rules for public resource groups and dedicated resource groups.

Billable resource

Billable item

Billing rule

Billing method

How to stop billing

Public resource group

The service time of the model service

Bills are generated based on how long the model service occupies public resources. Billing starts immediately after model services are created.

Pay-as-you-go

Stop the model service.

Dedicated resource group

The service time of the model service

You are charged only for nodes in dedicated resource groups. No additional fees are charged when you deploy model services in dedicated resource groups. For pay-as-you-go nodes, billing starts immediately the moment when nodes are created in dedicated resource groups.

Pay-as-you-go

Delete the pay-as-you-go resource group node.

Subscription

N/A

System disk

The capacity and service time of the system disk

Billing starts immediately after the system disk is created.

Pay-as-you-go

  • Release the node from the dedicated resource group.

  • Delete the service created by using the public resource group.

The capacity and service time of the system disk

Billing starts immediately after the system disk is created.

Subscription

N/A

Public resource group

The public resource group provides two options to obtain EAS nodes: resource-based configuration and instance type configuration. The following table describes the billing of each option.

Option

Calculation formula

Unit price

Usage duration

Scaling

Usage notes

Resource-based configuration

Fee for each model service = Number of instances contained in the service × [Number of vCPUs × (Unit price/60) + Amount of memory × (Unit price/60)] × Usage duration (minutes)

Fees are calculated per minute on a pay-as-you-go basis, rounded down to the minute. The table in the Resource-based configuration section of this topic provides the hourly prices for vCPU and memory resources.

  • Start time: the time when the model service starts to occupy resources.

  • End time: the time when the model service releases resources.

Scale-out: EAS generates fees for new resources.

Scale-in: EAS stops charging for resources that are released.

  • The usage duration is measured in minutes.

  • We recommend that you stop model services that you no longer use to prevent unnecessary costs.

Instance type configuration

Fee for each model service = Number of instances contained in the service × (Price per node/60) × Usage duration (minutes)

Fees are calculated per minute on a pay-as-you-go basis and rounded down to the minute. The pricing of resources varies based on the region and the instance type. The table in the Appendix: Pricing of specific instance types for public resource groups section of this topic provides the hourly prices for the supported instance types.

  • Start time: the time when the model service starts to occupy resources.

  • End time: the time when the model service releases resources.

N/A

  • The usage duration is measured in minutes.

  • We recommend that you stop model services that you no longer use to prevent unnecessary costs.

  • Specific instance types may become unavailable for short periods of time in specific regions. In this case, you can purchase instances in different regions.

Table 1. Resource-based configuration

Item

Unit price

CPU

USD 0.03 per vCPU-hour

Memory

USD 0.004 per GB-hour

Dedicated resource group

Dedicated resource groups provide subscription and pay-as-you-go resources. The following table describes the billing of each mode.

Billing mode

Calculation formula

Unit price

Usage duration

Scaling

Usage notes

Subscription

Fee for each resource group = Number of resources × Unit price × Subscription duration (months)

For more information about the pricing of subscription resources in dedicated resource groups, go to the EAS pre-payment for dedicated machine page.

  • Start time: the next day after the purchase, at 00:00:00.

  • End time: the time the model releases its resources.

N/A

  • Some instance types may become unavailable for short periods of time in some regions. If this happens, you can try to purchase instances in different regions.

Pay-as-you-go

Fee for each resource group = Number of resources × (Unit price/60) × Usage duration (minutes)

For more information about the pricing of pay-as-you-go resources in dedicated resource groups, go to the EAS post-payment for dedicated machine page.

  • Start time: the time when the node is created in the dedicated resource group and enters the Running state.

  • End time: the time when the dedicated resource group enters the No available resources state.

Scale-out: EAS generates charges for new resources.

Scale-in: EAS stops charging for resources that are released.

  • The usage duration is measured in minutes.

  • We recommend that you stop model services that you no longer use to prevent unnecessary costs.

  • Some instance types may become unavailable for short periods of time in some regions. If this happens, you can try to purchase instances in different regions.

System disk

System disks support the subscription and pay-as-you-go billing methods. The following table describes the billing of each mode.

Billing mode

Calculation formula

Unit price

Usage duration

Scaling

Usage notes

Subscription

System disk fee = System disk capacity (GB) × Unit price × Subscription duration (months)

For more information about the pricing in different regions, see the Subscription pricing section in this topic.

  • Start time: the time when you purchase the system disk.

  • End time: the time the model releases resources.

N/A

N/A

Pay-as-you-go

System disk fee = System disk capacity (GB)× Unit price × Usage duration (hours)

For more information about the pricing in different regions, see the Pay-as-you-go pricing section in this topic.

  • Start time: the time when you purchase the system disk.

  • End time: the time when the node is released from the dedicated resource group or when the service is deleted from the public resource group.

N/A

N/A

Table 2. Subscription pricing

Region

Price (USD per GB-month)

India (Mumbai)

0.214

Singapore

0.224

Indonesia (Jakarta)

0.214

China (Beijing)

0.153

China (Hangzhou)

0.153

China (Hong Kong)

0.224

China (Shanghai)

0.153

China (Shenzhen)

0.153

China (Zhangjiakou)

0.153

Germany (Frankfurt)

0.24

US (Virginia)

0.224

US (Silicon Valley)

0.224

Table 3. Pay-as-you-go pricing

Region

Price (USD per GB-month)

India (Mumbai)

0.0005

Singapore

0.0005

Indonesia (Jakarta)

0.0005

China (Beijing)

0.00032

China (Hangzhou)

0.00032

China (Hong Kong)

0.0005

China (Shanghai)

0.00032

China (Shenzhen)

0.00032

China (Zhangjiakou)

0.00032

Germany (Frankfurt)

0.0006

US (Virginia)

0.0005

US (Silicon Valley)

0.0005

Billing examples

Important

The following examples are for reference only. The actual prices listed on the EAS buy page of the Machine Learning Platform for AI (PAI) console shall prevail.

Public resource group

  • Example:

    You deployed a model service in the China (Hangzhou) region. The service was deployed using the resource-based configuration in the public resource group.

    • The model service occupied 2 vCPUs and 8 GB memory and started to run at 09:00:00 (UTC+8) on June 3, 2019.

    • You reduced the resources occupied by the model service to 1 vCPU and 4 GB memory at 10:00:00 (UTC+8) on June 3, 2019.

    • Then, you increased the resources occupied by the model service to 4 vCPUs and 16 GB of memory at 11:00:00 (UTC+8) on June 3, 2019.

    • At 12:00:00 (UTC+8) on June 3, 2019, the model service stopped running.

  • Cost calculation:

    Bill amount = 2 × 0.03 + 8 × 0.004 + 1 × 0.03 + 4 × 0.004 + 4 × 0.03 + 16 × 0.004 = USD 0.322

Dedicated resource group

  • Subscription

    • Example:

      You created two 3-month subscription T4 GPU instances (4 vCPUs, 15 GB) in the China (Hangzhou) region. Each instance costs USD 570 per month.

    • Cost calculation:

      Bill amount = 2 × 570 × 3 = USD 3,420
  • Pay-as-you-go

    • Example:

      You purchase two pay-as-you-go Elastic Compute Service (ECS) instances whose instance type is ecs.g6.6xlarge in the China (Hangzhou) region, and use the instances for 45 minutes. Each ECS instance has 24 vCPUs and 96 GB of memory, and the unit price is USD 2.94 per hour. This unit price is only for reference. The prices listed in the ECS console shall prevail.

    • Cost calculation:

      Bill amount = 2 × (2.94/60) × 45 = USD 4.41

System disk

  • Subscription

    • Example:

      You deployed two subscription nodes to a dedicated resource group in the China (Hangzhou) region for three months. Each node provides 300 GB of system disk capacity.

    • Cost calculation:

      Bill amount = 2 × (300 - 200) × 0.153 × 3 = USD 91.8
  • Pay-as-you-go (applicable to dedicated resource groups)

    • Example:

      You deployed two pay-as-you-go nodes to a dedicated resource group in the China (Hangzhou) region and used the nodes for 5 hours. Each node provides 300 GB of system disk capacity.

    • Cost calculation:

      Bill amount = 2 × (300 - 200) × 0.00032 × 5 = USD 0.32
  • Pay-as-you-go (applicable to the public resource group)

    • Example:

      You deployed two pay-as-you-go nodes to the public resource group in the China (Hangzhou) region and used them for 5 hours. Each node provides 300 GB system disk capacity.

    • The bill amount is calculated based on the following formula:

      Bill amount = 2 × (300 - 30) × 0.00032 × 5 = USD 0.864

Overdue payments

Causes

Your account balance is insufficient to pay your overdue payment.

  • Subscription nodes: Your account balance needs to be sufficient to complete renewal orders.

  • Pay-as-you-go nodes: Your account balance needs to be sufficient to settle the bills from the previous billing cycle. If the payment fails, the payment becomes overdue.

Service suspension

  • Subscription nodes

    If a node expires and fails to be renewed, the node is released. After the node is released, the node enters the stopped state and the EAS services that use this node enter the waiting state.

    If you renew the node within 15 calendar days (360 hours) after the node expires, the node is restored.

    Otherwise, the node is permanently deleted.

  • Pay-as-you-go resource groups (including public resource groups and pay-as-you-go nodes in resource groups)

    If you settle the overdue payments within 24 hours after the payments become overdue, your resource groups remain available. Otherwise, public resource groups are stopped and pay-as-you-go nodes are released. After the nodes are released, the nodes enter the stopped state and the EAS services that use these nodes enter the waiting state.

    If you settle the overdue payments within 15 calendar days (360 hours) after the payments become overdue, the system recovers the resource groups and the data in the groups is retained. Otherwise, the stopped nodes are permanently deleted.

View the overdue amount

  1. Log on to the Billing Management console.

  2. On the Account Overview page, view the outstanding amount due.账户总览

Renewal

Subscription nodes in dedicated resource groups can be automatically renewed upon expiration or manually renewed.

  • Auto-renewal

    To enable auto-renewal, select Auto-renewal when you purchase a subscription node. For more information, see Work with dedicated resource groups.

  • Manual renewal

    To manually renew a subscription node, go to the details page of the dedicated resource group to which the node belongs, find the node that you want to renew, and choose image.png> Renew in the Actions column. For more information, see Work with dedicated resource groups.

Refund policy

Fees incurred in pay-as-you-go mode cannot be refunded.

Appendix: Pricing of specific instance types for public resource groups

CPU Type

Instance Type

Instance Family

vCPU

Memory (GiB)

Price (USD/hour)

Region

ecs.c7.large

c7(2vcpu+4GB)

2

4

0.12

  • Singapore

  • China (Hong Kong)

0.06

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

  • China (Heyuan)

  • China (Ulanqab)

ecs.c7.xlarge

c7(4vcpu+8GB)

4

8

0.24

  • Singapore

  • China (Hong Kong)

0.12

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

  • China (Heyuan)

  • China (Ulanqab)

ecs.c7.2xlarge

c7(8vcpu+16GB)

8

16

0.42

  • Singapore

  • Indonesia (Jakarta)

0.3

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.24

  • China (Heyuan)

  • China (Ulanqab)

0.48

China (Hong Kong)

ecs.c7.4xlarge

c7(16vcpu+32GB)

16

32

0.84

  • Singapore

  • Indonesia (Jakarta)

0.54

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.48

  • China (Heyuan)

  • China (Ulanqab)

0.9

China (Hong Kong)

ecs.c7.6xlarge

c7(24vcpu+48GB)

24

48

1.26

  • Singapore

  • Indonesia (Jakarta)

0.84

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.72

China (Heyuan)

0.78

China (Ulanqab)

1.38

China (Hong Kong)

ecs.c7.8xlarge

c7(32vcpu+64GB)

32

64

1.68

  • Singapore

  • Indonesia (Jakarta)

1.14

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.96

China (Heyuan)

1.02

China (Ulanqab)

1.86

China (Hong Kong)

ecs.c7.16xlarge

c7(64vcpu+128GB)

64

128

3.36

  • Singapore

  • Indonesia (Jakarta)

2.22

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

1.98

  • China (Heyuan)

  • China (Ulanqab)

3.66

China (Hong Kong)

ecs.r7.4xlarge

r7(16vcpu+128GB)

16

128

1.32

Singapore

0.96

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.84

  • China (Heyuan)

  • China (Ulanqab)

1.44

China (Hong Kong)

ecs.r7.large

r7(2vcpu+16GB)

2

16

0.18

  • China (Hong Kong)

  • Singapore

0.12

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

  • China (Heyuan)

  • China (Ulanqab)

ecs.r7.xlarge

r7(4vcpu+32GB)

4

32

0.3

Singapore

0.24

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

  • China (Heyuan)

  • China (Ulanqab)

0.36

China (Hong Kong)

ecs.r7.2xlarge

r7(8vcpu+64GB)

8

64

0.66

Singapore

0.48

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.42

  • China (Heyuan)

  • China (Ulanqab)

0.72

China (Hong Kong)

ecs.r7.6xlarge

r7(16vcpu+128GB)

24

192

1.98

Singapore

1.44

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

1.26

  • China (Heyuan)

  • China (Ulanqab)

2.16

China (Hong Kong)

ecs.r7.8xlarge

r7(32vcpu+256GB)

32

256

2.58

Singapore

1.92

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

1.68

  • China (Heyuan)

  • China (Ulanqab)

2.88

China (Hong Kong)

ecs.r7.16xlarge

r7(64vcpu+512GB)

64

512

5.22

Singapore

3.78

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

3.36

China (Heyuan)

3.42

China (Ulanqab)

5.7

China (Hong Kong)

ecs.g7.large

g7(2vcpu+8GB)

2

8

0.12

  • Singapore

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Hong Kong)

  • China (Chengdu)

0.06

  • China (Heyuan)

  • China (Ulanqab)

ecs.g7.xlarge

g7(4vcpu+16GB)

4

16

0.24

Singapore

0.18

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

  • China (Heyuan)

  • China (Ulanqab)

0.3

China (Hong Kong)

ecs.g7.2xlarge

g7(8vcpu+32GB)

8

32

0.54

  • Singapore

  • Indonesia (Jakarta)

  • China (Hong Kong)

0.3

  • China (Heyuan)

  • China (Ulanqab)

0.36

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

ecs.g7.4xlarge

g7(16vcpu+64GB)

16

64

1.02

  • Singapore

  • Indonesia (Jakarta)

0.72

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.66

  • China (Heyuan)

  • China (Ulanqab)

1.14

China (Hong Kong)

ecs.g7.6xlarge

g7(24vcpu+96GB)

24

96

1.56

  • Singapore

  • Indonesia (Jakarta)

1.08

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

0.96

  • China (Heyuan)

  • China (Ulanqab)

1.68

China (Hong Kong)

ecs.g7.8xlarge

g7(32vcpu+128GB)

32

128

2.04

  • Singapore

  • Indonesia (Jakarta)

1.44

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Chengdu)

1.26

  • China (Heyuan)

  • China (Ulanqab)

2.28

China (Hong Kong)

ecs.g7.16xlarge

g7(64vcpu+256GB)

64

256

4.08

  • Singapore

  • Indonesia (Jakarta)

2.88

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

2.58

China (Ulanqab)

4.5

China (Hong Kong)

ecs.g6.large

g6(2vcpu+8GB)

2

8

0.12

  • India (Mumbai)

  • Singapore

  • Indonesia (Jakarta)

  • China (Hong Kong)

  • Germany (Frankfurt)

  • US (Virginia)

  • US (Silicon Valley)

0.06

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Zhangjiakou)

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

ecs.g6.xlarge

g6(4vcpu+16GB)

4

16

0.24

  • India (Mumbai)

  • Germany (Frankfurt)

  • US (Virginia)

  • US (Silicon Valley)

0.3

  • Singapore

  • Indonesia (Jakarta)

  • China (Hong Kong)

0.18

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.12

China (Zhangjiakou)

ecs.g6.2xlarge

g6(8vcpu+32GB)

8

32

0.48

India (Mumbai)

0.54

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

0.36

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

0.6

China (Hong Kong)

0.24

China (Zhangjiakou)

0.3

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.42

  • US (Virginia)

  • US (Silicon Valley)

ecs.g6.4xlarge

g6(16vcpu+64GB)

16

64

0.9

  • India (Mumbai)

  • US (Virginia)

  • US (Silicon Valley)

1.08

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

0.66

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.2

China (Hong Kong)

0.6

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.48

China (Zhangjiakou)

ecs.g6.6xlarge

g6(24vcpu+96GB)

24

96

1.38

India (Mumbai)

1.68

  • Singapore

  • Indonesia (Jakarta)

1.02

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.8

China (Hong Kong)

0.72

China (Zhangjiakou)

1.62

Germany (Frankfurt)

0.9

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

1.32

  • US (Virginia)

  • US (Silicon Valley)

ecs.g6.8xlarge

g6(32vcpu+128GB)

32

128

1.86

India (Mumbai)

2.22

  • Singapore

  • Indonesia (Jakarta)

1.38

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

2.4

China (Hong Kong)

0.96

China (Zhangjiakou)

1.2

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

1.8

  • US (Virginia)

  • US (Silicon Valley)

ecs.c6.large

c6(2vcpu+4GB)

2

4

0.12

  • India (Mumbai)

  • Singapore

  • Indonesia (Jakarta)

  • China (Hong Kong)

  • Germany (Frankfurt)

  • US (Virginia)

  • US (Silicon Valley)

0.06

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Zhangjiakou)

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

ecs.c6.xlarge

c6(4vcpu+8GB)

4

8

0.18

  • India (Mumbai)

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

  • US (Virginia)

  • US (Silicon Valley)

0.12

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Zhangjiakou)

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.24

China (Hong Kong)

ecs.c6.2xlarge

c6(8vcpu+16GB)

8

16

0.36

  • India (Mumbai)

  • US (Virginia)

  • US (Silicon Valley)

0.42

  • Indonesia (Jakarta)

  • Singapore

  • Germany (Frankfurt)

0.24

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.48

China (Hong Kong)

0.18

China (Zhangjiakou)

ecs.c6.4xlarge

c6(16vcpu+32GB)

16

32

0.72

  • India (Mumbai)

  • US (Virginia)

  • US (Silicon Valley)

0.84

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

0.54

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

0.9

China (Hong Kong)

0.48

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.36

China (Zhangjiakou)

ecs.c6.6xlarge

c6(24vcpu+48GB)

24

48

1.08

  • India (Mumbai)

  • US (Virginia)

  • US (Silicon Valley)

1.26

  • Singapore

  • Indonesia (Jakarta)

0.78

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.38

China (Hong Kong)

0.54

China (Zhangjiakou)

0.72

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

1.2

Germany (Frankfurt)

ecs.c6.8xlarge

c6(32vcpu+64GB)

32

64

1.44

  • India (Mumbai)

  • US (Virginia)

  • US (Silicon Valley)

1.68

  • Singapore

  • Indonesia (Jakarta)

1.08

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.8

China (Hong Kong)

0.72

China (Zhangjiakou)

0.96

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

1.62

Germany (Frankfurt)

ecs.r6.large

r6(2vcpu+16GB)

2

16

0.12

  • India (Mumbai)

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • US (Virginia)

  • US (Silicon Valley)

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.18

  • Singapore

  • Indonesia (Jakarta)

  • China (Hong Kong)

  • Germany (Frankfurt)

0.06

China (Zhangjiakou)

ecs.r6.xlarge

r6(4vcpu+32GB)

4

32

0.3

  • India (Mumbai)

  • US (Virginia)

  • US (Silicon Valley)

0.36

  • Singapore

  • Indonesia (Jakarta)

  • China (Hong Kong)

  • Germany (Frankfurt)

0.24

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

0.18

  • China (Zhangjiakou)

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

ecs.r6.2xlarge

r6(8vcpu+64GB)

8

64

0.6

  • India (Mumbai)

  • US (Virginia)

  • US (Silicon Valley)

0.72

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

0.48

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

0.78

China (Hong Kong)

0.42

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

0.3

China (Zhangjiakou)

ecs.r6.4xlarge

r6(16vcpu+128GB)

16

128

1.2

India (Mumbai)

1.38

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

0.9

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.56

China (Hong Kong)

0.6

China (Zhangjiakou)

0.78

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

1.14

  • US (Virginia)

  • US (Silicon Valley)

ecs.r6.6xlarge

r6(24vcpu+192GB)

24

192

1.8

India (Mumbai)

1.38

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

2.1

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

2.34

China (Hong Kong)

0.96

China (Zhangjiakou)

1.2

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

1.74

  • US (Virginia)

  • US (Silicon Valley)

ecs.r6.8xlarge

r6(32vcpu+256GB)

32

256

2.4

India (Mumbai)

2.76

  • Singapore

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

1.8

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

3.06

China (Hong Kong)

1.26

China (Zhangjiakou)

1.62

  • China (Heyuan)

  • China (Chengdu)

  • China (Ulanqab)

2.34

  • US (Virginia)

  • US (Silicon Valley)

ecs.g5.6xlarge

g5(24vcpu+96GB)

24

96

1.8

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.38

  • China (Zhangjiakou)

  • US (Virginia)

1.68

China (Hong Kong)

1.32

India (Mumbai)

1.74

Singapore

1.62

Indonesia (Jakarta)

1.56

Germany (Frankfurt)

ecs.c5.6xlarge

c5(24vcpu+48GB)

24

48

1.08

  • India (Mumbai)

  • US (Virginia)

1.26

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • Singapore

1.2

  • Indonesia (Jakarta)

  • China (Hong Kong)

0.96

China (Zhangjiakou)

1.14

Germany (Frankfurt)

ecs.g8y.large

Yitian(2vcpu+8GB)

2

8

0.06

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g8y.xlarge

Yitian(4vcpu+16GB)

4

16

0.12

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g8y.2xlarge

Yitian(8vcpu+32GB)

8

32

0.24

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g8y.4xlarge

Yitian(16vcpu+64GB)

16

64

0.54

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g8y.8xlarge

Yitian(32vcpu+128GB)

32

128

1.08

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g8y.16xlarge

Yitian(64vcpu+256GB)

64

256

2.16

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.c7a.large

AMD(2vcpu+4GB)

2

4

0.12

Singapore

0.06

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Hong Kong)

  • China (Ulanqab)

ecs.c7a.xlarge

AMD(4vcpu+8GB)

4

8

0.18

  • China (Hong Kong)

  • Singapore

0.12

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

ecs.c7a.2xlarge

AMD(8vcpu+16GB)

8

16

0.36

  • China (Hong Kong)

  • Singapore

0.18

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

ecs.c7a.4xlarge

AMD(16vcpu+32GB)

16

32

0.72

Singapore

0.66

China (Hong Kong)

0.36

China (Ulanqab)

0.42

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.c7a.8xlarge

AMD(32vcpu+64GB)

32

64

1.44

Singapore

1.38

China (Hong Kong)

0.72

China (Ulanqab)

0.78

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.c7a.16xlarge

AMD(64vcpu+128GB)

64

128

2.88

Singapore

2.76

China (Hong Kong)

1.62

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g7a.large

AMD(2vcpu+8GB)

2

8

0.12

  • Singapore

  • China (Hong Kong)

0.06

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

ecs.g7a.xlarge

AMD(4vcpu+16GB)

4

16

0.24

  • Singapore

  • China (Hong Kong)

0.12

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

ecs.g7a.2xlarge

AMD(8vcpu+32GB)

8

32

0.48

  • Singapore

  • China (Hong Kong)

0.24

China (Ulanqab)

0.3

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g7a.4xlarge

AMD(16vcpu+64GB)

16

64

0.96

  • Singapore

  • China (Hong Kong)

0.54

China (Ulanqab)

0.6

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g7a.8xlarge

AMD(32vcpu+128GB)

32

128

1.98

Singapore

1.86

China (Hong Kong)

1.08

China (Ulanqab)

1.2

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.g7a.16xlarge

AMD(64vcpu+256GB)

64

256

3.9

Singapore

3.78

China (Hong Kong)

2.16

China (Ulanqab)

2.4

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

GPU Type

Instance Type

Instance Family

vCPU

Memory (GiB)

Price (USD/hour)

Region

ml.gu7i.c8m30.1-gu30

8vcpu30GB+1*GU30

8

30

1.18

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.41

US (Virginia)

1.72

Germany (Frankfurt)

1.68

Singapore

1.06

China (Ulanqab)

ml.gu7i.c16m60.1-gu30

16vcpu60GB+1*GU30

16

60

1.25

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.49

US (Virginia)

1.82

Germany (Frankfurt)

1.78

Singapore

1.13

China (Ulanqab)

ml.gu7i.c32m188.1-gu30

32vcpu188GB+1*GU30

32

188

1.39

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.65

US (Virginia)

2.02

Germany (Frankfurt)

1.97

Singapore

1.25

China (Ulanqab)

ml.gu7i.c64m376.2-gu30

64vcpu376GB+2*GU30

64

376

2.78

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

3.31

US (Virginia)

4.04

Germany (Frankfurt)

3.95

Singapore

2.5

China (Ulanqab)

ml.gu7i.c128m752.4-gu30

128vcpu752GB+4*GU30

128

752

5.55

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

6.62

US (Virginia)

8.08

Germany (Frankfurt)

7.9

Singapore

5

China (Ulanqab)

ecs.gn5i-c4g1.xlarge

4vcpu+16GB+1*P4

4

16

1.68

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.26

China (Zhangjiakou)

ecs.gn5i-c8g1.2xlarge

8vcpu+32GB+1*P4

8

32

1.98

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

1.5

China (Zhangjiakou)

ecs.gn5-c4g1.xlarge

4vcpu+30GB+1*P100

4

30

2.04

  • India (Mumbai)

  • China (Hong Kong)

  • US (Silicon Valley)

2.16

  • Singapore

  • Indonesia (Jakarta)

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

1.98

China (Zhangjiakou)

1.92

Germany (Frankfurt)

1.86

US (Virginia)

ecs.gn5-c8g1.2xlarge

8vcpu+60GB+1*P100

8

60

2.46

  • India (Mumbai)

  • China (Hong Kong)

  • US (Silicon Valley)

2.58

  • Singapore

  • Indonesia (Jakarta)

2.64

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

2.34

China (Zhangjiakou)

2.28

Germany (Frankfurt)

2.22

US (Virginia)

ecs.gn5-c28g1.7xlarge

28vcpu+112GB+1*P100

28

112

3.78

India (Mumbai)

3.72

  • Singapore

  • Indonesia (Jakarta)

4.08

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

3.54

China (Hong Kong)

3.84

Germany (Frankfurt)

3.48

  • US (Virginia)

  • US (Silicon Valley)

ecs.gn5-c8g1.4xlarge

16vcpu+120GB+2*P100

16

120

4.92

  • China (Hong Kong)

  • India (Mumbai)

5.16

  • Singapore

  • Indonesia (Jakarta)

5.22

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

4.74

China (Zhangjiakou)

4.62

Germany (Frankfurt)

4.44

US (Virginia)

4.86

US (Silicon Valley)

ecs.vgn6i-m4-vws.xlarge

4vcpu+23GB+1/4*T4

4

23

0.54

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

ecs.vgn6i-m8-vws.2xlarge

10vcpu+46GB+1/2*T4

10

46

1.02

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

ecs.gn6i-c4g1.xlarge

4vcpu+15GB+1*T4

4

15

1.5

  • India (Mumbai)

  • Singapore

1.44

Indonesia (Jakarta)

1.98

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

1.32

  • China (Hong Kong)

  • US (Virginia)

1.8

  • China (Zhangjiakou)

  • China (Chengdu)

  • China (Ulanqab)

1.38

  • Germany (Frankfurt)

  • US (Silicon Valley)

ecs.gn6i-c8g1.2xlarge

8vcpu+31GB+1*T4

8

31

1.74

India (Mumbai)

1.8

Singapore

1.68

  • Indonesia (Jakarta)

  • Germany (Frankfurt)

2.4

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

1.56

  • China (Hong Kong)

  • US (Virginia)

1.62

US (Silicon Valley)

2.16

  • China (Zhangjiakou)

  • China (Chengdu)

  • China (Ulanqab)

ecs.gn6i-c16g1.4xlarge

16vcpu+62GB+1*T4

16

62

2.28

  • India (Mumbai)

  • Germany (Frankfurt)

2.34

Singapore

2.22

Indonesia (Jakarta)

2.82

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

2.1

China (Hong Kong)

2.52

  • China (Zhangjiakou)

  • China (Chengdu)

  • China (Ulanqab)

2.04

US (Silicon Valley)

1.98

US (Virginia)

ecs.gn6i-c24g1.6xlarge

24vcpu+93GB+1*T4

24

93

2.7

India (Mumbai)

2.76

Indonesia (Jakarta)

2.94

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • Singapore

  • China (Heyuan)

2.64

  • China (Hong Kong)

  • China (Zhangjiakou)

  • China (Chengdu)

  • China (Ulanqab)

2.88

Germany (Frankfurt)

2.58

US (Silicon Valley)

2.52

US (Virginia)

ecs.gn6i-c24g1.12xlarge

48vcpu+186GB+2*T4

48

186

5.46

India (Mumbai)

5.94

Singapore

5.52

Indonesia (Jakarta)

5.88

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

5.22

  • China (Hong Kong)

  • US (Silicon Valley)

5.28

  • China (Zhangjiakou)

  • China (Chengdu)

  • China (Ulanqab)

5.7

Germany (Frankfurt)

5.04

US (Virginia)

ecs.gn6i-c24g1.24xlarge

96vcpu+372GB+4*T4

96

372

11.7

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • Singapore

10.56

  • China (Zhangjiakou)

  • China (Ulanqab)

ecs.gn7i-c8g1.2xlarge

8vcpu+30GB+1*A10

8

30

3.06

Singapore

1.98

China (Ulanqab)

2.16

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

  • China (Chengdu)

ecs.gn7i-c16g1.4xlarge

16vcpu+60GB+1*A10

16

60

3.24

Singapore

2.04

China (Ulanqab)

2.28

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

  • China (Chengdu)

ecs.gn7i-c32g1.8xlarge

32vcpu+188GB+1*A10

32

188

3.6

Singapore

2.28

China (Ulanqab)

2.52

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

  • China (Chengdu)

ecs.gn7i-c32g1.16xlarge

64vcpu+376GB+2*A10

64

376

5.1

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

  • China (Chengdu)

7.26

Singapore

4.56

China (Ulanqab)

ecs.gn7i-c32g1.32xlarge

128vcpu+752GB+4*A10

128

752

10.2

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Heyuan)

  • China (Chengdu)

14.46

Singapore

9.18

China (Ulanqab)

ecs.gn6v-c8g1.2xlarge

8vcpu+32GB+1*V100

8

32

5.22

Singapore

4.5

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Ulanqab)

3.36

China (Zhangjiakou)

3.12

US (Virginia)

ecs.gn6v-c8g1.4xlarge

16vcpu+64GB+2*V100

16

64

9

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

  • China (Zhangjiakou)

  • China (Ulanqab)

10.38

Singapore

ecs.gn6v-c8g1.8xlarge

32vcpu+128GB+4*V100

32

128

18

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

13.5

China (Zhangjiakou)

20.76

Singapore

9.72

China (Ulanqab)

ecs.gn6v-c8g1.16xlarge

64vcpu+256GB+8*V100

64

256

36.06

China (Ulanqab)

ecs.gn6e-c12g1.3xlarge

12vcpu+92GB+1*V100

12

92

4.68

Singapore

3

  • China (Zhangjiakou)

  • China (Ulanqab)

3.36

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

ecs.gn6e-c12g1.12xlarge

48vcpu+368GB+4*V100

48

368

13.44

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

18.78

Singapore

12.12

  • China (Zhangjiakou)

  • China (Ulanqab)

ecs.gn6e-c12g1.24xlarge

96vcpu+736GB+8*V100

96

736

26.88

  • China (Beijing)

  • China (Hangzhou)

  • China (Shanghai)

  • China (Shenzhen)

37.56

Singapore

24.18

  • China (Zhangjiakou)

  • China (Ulanqab)

ecs.gn7-c12g1.3xlarge

12vcpu+95GB+1*A100

12

95

5.4

  • China (Beijing)

  • China (Shanghai)

4.86

China (Ulanqab)

ecs.gn7-c13g1.6xlarge

26vcpu+189GB+2*A100

26

189

10.74

  • China (Beijing)

  • China (Shanghai)

9.66

China (Ulanqab)

ecs.gn7-c13g1.13xlarge

52vcpu+378GB+4*A100

52

378

21.48

  • China (Beijing)

  • China (Shanghai)

19.38

China (Ulanqab)

ecs.gn7-c13g1.26xlarge

104vcpu+756GB+8*A100

104

756

43.02

  • China (Beijing)

  • China (Shanghai)

38.7

China (Ulanqab)

ecs.gn7e-c16g1.4xlarge

16vcpu+125GB+1*A100

16

125

5.94

  • China (Beijing)

  • China (Shanghai)

5.34

China (Ulanqab)

ecs.gn7e-c16g1.8xlarge

32vcpu+250GB+2*A100

32

250

11.82

  • China (Beijing)

  • China (Shanghai)

ecs.gn7e-c16g1.16xlarge

64vcpu+500GB+4*A100

64

500

23.64

  • China (Beijing)

  • China (Shanghai)

21.3

China (Ulanqab)

ecs.gn7e-c16g1.32xlarge

128vcpu+1000GB+8*A100

128

1000

47.34

  • China (Beijing)

  • China (Shanghai)

42.6

China (Ulanqab)