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Platform For AI:Billing of EAS

Last Updated:Mar 12, 2025

This topic describes the billable items and billing methods of Elastic Algorithm Service (EAS) of Platform for AI (PAI).

Billing overview

When you use EAS to deploy services, you may be charged for computing resources, system disks, and dedicated gateways.

  • Computing resources: includes public resources, dedicated resources, and Lingjun resources.

  • (Optional) System disks: provides free quotas, including 30 GB for each instance created by using public resources and 200 GB for each instance created by using dedicated resources. You are charged for additional system disks.

  • (Optional) Dedicated gateways: By default, a free shared gateway is used. If you require security isolation, access control, or custom domain names, you can purchase a dedicated gateway. To use a dedicated gateway, you must manually configure it.

EAS provides the following billing methods:

  • Pay-as-you-go: You are charged based on your actual usage. This billing method is suitable for uncertain and fluctuating demand scenarios.

  • Subscription: This billing method is more cost-effective. It is suitable for long-term stable business scenarios.

EAS provides Stable Diffusion web UI Serverless Edition and ComfyUI Serverless Edition that you can use to deploy services free of charge. You are charged only based on the inference duration during service calling.

Important

If you use other Alibaba Cloud services, such as Elastic IP Address (EIP), Object Storage Service (OSS), and File Storage NAS (NAS), fees are generated.

image

Billing period

Pay-as-you-go

For pay-as-you-go resources, you must pay special attention to the start and end time of billing to prevent unexpected fee deduction. To prevent unnecessary costs, we recommend that you stop model services that you no longer use.

Resource

Start time of billing

End time of billing

Public resources

The time when the model service enters the Running state. You are charged for the model service even if you do not call the model service.

The time when a model service stops running and releases resources.

Important

You must stop or delete a service instance.

Dedicated resources

The time when the model service is created and enters the Running state. You are charged for the model service even if the model service is not deployed.

  • The time when the instance is deleted.

  • The time when the instance enters the Stopped state.

Important

An instance can enter the stopped state only due to overdue payments. You must delete the pay-as-you-go instance to stop billing.

System disk

The time when you purchase the system disk.

  • The time when the service instance in the dedicated resource group is deleted.

  • The time when the service deployed by using public resources is deleted.

Dedicated gateway

The dedicated gateway is created. The dedicated gateway is billed even if it is not used.

The time when the dedicated gateway is deleted.

Service scaling

  • If you scale out a model service, you are charged for new resources after the scale-out operation is complete.

  • If you scale in a model service, the released resources are no longer billed. You are charged only for the remaining resources.

Subscription

Resource

Start time of billing

End time of billing

Dedicated resources

The next day after the purchase, at 00:00:00.

The expiration time.

AI computing resources (Lingjun resources)

The next day after the purchase, at 00:00:00.

The expiration time.

System disk

The time when you purchase the system disk.

The expiration time.

Dedicated gateway

The time when you purchase the dedicated gateway.

The expiration time.

Service inference (Serverless Edition)

  • The deployment of Serverless Edition services is free of charge. You are charged only if you call the services based on the inference duration.

  • For example, if you click Generate on the web UI page to generate an image and the process requires 10 seconds, the billing duration is 10 seconds.

  • Only Stable Diffusion web UI and ComfyUI support the deployment of Serverless Edition services. You can view the pricing details on the deployment page.

Usage notes

The pricing information in this topic is provided only for reference. The actual prices in the billing statement shall prevail.

Billable resources

The following table describes the billing methods of different resources.

Billable item

Billing method

Fee calculation

Unit price

Usage notes

Public resources

Pay-as-you-go

(specific resources required by the instance)

Bill amount for each model service = Number of instances × [Number of vCPUs × (Unit price of vCPUs/60) + Memory size × (Unit price of memory/60)] × Usage duration (minutes)

Fees are calculated per minute on a pay-as-you-go basis and rounded down to the minute. For more information about the hourly prices of vCPU and memory resources, see Resource-based configuration. To calculate the unit prices per minute, divide the prices listed in Table 1 by 60.

  • The usage duration is measured in minutes.

  • To prevent unnecessary costs, we recommend that you stop model services that you no longer use.

Pay-as-you-go (specific instance type)

Bill amount for each model service = Number of instances × (Unit price/60) × Usage duration (minutes)

Unit prices may vary based on the instance type and the region. See the prices in the console.

For information about the instance types supported by the public resource group, see Appendix: Public resource group instance types.

  • The usage duration is measured in minutes.

  • To prevent unnecessary costs, we recommend that you stop model services that you no longer use.

  • Specific resources may be unavailable in specific regions for a short period of time.

Dedicated resources

Pay-as-you-go

Bill amount for each resource group = Number of instances × (Unit price/60) × Usage duration (minutes)

For information about the unit prices of pay-as-you-go instances, go to the EAS post-payment for dedicated machine buy page.

  • The usage duration is measured in minutes.

  • Specific resources may be unavailable in specific regions for a short period of time.

Subscription

Bill amount for each resource group = Number of instances × Unit price × Subscription duration (months)

For information about the unit prices of subscription instances, go to the EAS pre-payment for dedicated machine buy page.

Specific resources may be unavailable in specific regions for a short period of time.

AI computing resources (Lingjun resources)

Subscription

Lingjun resources support the subscription billing method. You can deploy model services in EAS by using Lingjun resource quotas. For more information, see Billing of AI computing resources.

System disk

Pay-as-you-go

Bill amount = Number of instances × System disk capacity (GiB) × (Unit price/60) × Usage duration (minutes)

To view the unit prices of system disks, go to the product overview page of Elastic Compute Service (ECS), click the Pricing tab, and then click Storage. The pricing information of Enterprise SSD (ESSD) PL1 is displayed in the System Cloud Disk Fee section.

N/A.

Subscription

Bill amount = Number of instances × System disk capacity (GiB) × Unit price × Subscription duration (months)

To view the unit prices of system disks, go to the product overview page of ECS, click the Pricing tab, and then click Storage. The pricing information of ESSD PL1 is displayed in the System Cloud Disk Fee section.

N/A.

Dedicated gateway

Pay-as-you-go

Bill amount = (Unit price/60) × Number of gateway nodes × Usage duration (minutes)

To view the unit prices of dedicated gateways, go to the EAS Dedicated Gateway Postpay buy page.

N/A.

Subscription

Bill amount = Unit price × Number of gateway nodes × Usage duration (months)

To view the unit prices of subscription dedicated gateways, go to the EAS dedicated gateway prepay buy page.

N/A.

Service inference (Serverless Edition)

Pay-by-inference-duration

Bill amount = Service inference duration (seconds) × Unit price (USD/second)

Only Stable Diffusion web UI and ComfyUI support the deployment of Serverless Edition services. You can view the pricing details on the deployment page.

N/A.

Table 1 Resource-based configuration

Important

The unit prices listed in the following table are provided only for reference. You can view the actual prices in the console or on the buy page of the service resource that you want to purchase.

Resource

Pricing

CPU

USD 0.03 per vCPU-hour

Memory

USD 0.004 per GB-hour

Billing examples

Important

The following examples are provided only for reference. The actual prices listed on the EAS buy page of the PAI console shall prevail.

Public resource group

Pay-as-you-go

  • Scenario

    You used the public resource group to deploy a model service in the China (Hangzhou) region. You specified the public resources used for model deployment based on your business requirements.

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

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

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

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

  • Fee 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

  • Scenario

    You subscribed to two NVIDIA T4 GPUs in the China (Hangzhou) region for three months. Each GPU provides 4 vCPUs and 15 GB of memory. The unit price of the GPU is USD 570 per month.

  • Fee calculation

    Bill amount = 2 × 570 × 3 = USD 3,420

Pay-as-you-go

  • Scenario

    You purchased two pay-as-you-go ecs.g6.6xlarge instances in the China (Hangzhou) region and used the instances for 45 minutes. Each instance provides 24 vCPUs and 96 GB of memory. The unit price of the instance is USD 1.02 per hour.

  • Fee calculation

    Bill amount = 2 × (1.02/60) × 45 = USD 1.53

System disk

Subscription

  • Scenario

    You purchased two subscription instances in the China (Hangzhou) region for a dedicated resource group. Each instance provides a system disk capacity of 300 GiB (free storage: 200 GiB). The subscription duration is three months.

  • Fee calculation

    Bill amount = 2 × (300 - 200) × 0.153 × 3 = USD 91.8

Pay-as-you-go

  • Dedicated resource group

    • Scenario

      You purchased two pay-as-you-go instances in the China (Hangzhou) region for a dedicated resource group and used them for 5 hours. Each instance provides a system disk capacity of 300 GiB (free storage: 200 GiB).

    • Fee calculation

      Bill amount = 2 × (300 - 200) × 0.000319 × 5 = USD 0.319
  • Public resource group

    • Scenario

      You purchased two pay-as-you-go instances in the public resource group and deployed them in the China (Hangzhou) region. You used the instances for 5 hours. Each instance provides a system disk capacity of 300 GiB (free storage: 30 GiB).

    • Fee calculation

      Bill amount = 2 × (300 - 30) × 0.000319 × 5 = USD 0.8613

Appendix: Public resource group instance types

The following table describes specific instance types that can be used to deploy EAS services in the public resource group. For a complete list of supported instance types, go to the EAS page in the PAI console, click Deploy Service, and then click Custom Deployment. In the Resource Deployment Information section, you can view the supported instance types. For more information, see Deploy a model service in the PAI console. The supported instance types may vary based on the region.

CPU type

Instance type

vCPU

Memory (GB)

ecs.c7.large

2

4

ecs.c7.xlarge

4

8

ecs.c7.2xlarge

8

16

ecs.c7.4xlarge

16

32

ecs.c7.6xlarge

24

48

ecs.c7.8xlarge

32

64

ecs.c7.16xlarge

64

128

ecs.r7.4xlarge

16

128

ecs.r7.large

2

16

ecs.r7.xlarge

4

32

ecs.r7.2xlarge

8

64

ecs.r7.6xlarge

24

192

ecs.r7.8xlarge

32

256

ecs.r7.16xlarge

64

512

ecs.g7.large

2

8

ecs.g7.xlarge

4

16

ecs.g7.2xlarge

8

32

ecs.g7.4xlarge

16

64

ecs.g7.6xlarge

24

96

ecs.g7.8xlarge

32

128

ecs.g7.16xlarge

64

256

ecs.g6.large

2

8

ecs.g6.xlarge

4

16

ecs.g6.2xlarge

8

32

ecs.g6.4xlarge

16

64

ecs.g6.6xlarge

24

96

ecs.g6.8xlarge

32

128

ecs.c6.large

2

4

ecs.c6.xlarge

4

8

ecs.c6.2xlarge

8

16

ecs.c6.4xlarge

16

32

ecs.c6.6xlarge

24

48

ecs.c6.8xlarge

32

64

ecs.r6.large

2

16

ecs.r6.xlarge

4

32

ecs.r6.2xlarge

8

64

ecs.r6.4xlarge

16

128

ecs.r6.6xlarge

24

192

ecs.r6.8xlarge

32

256

ecs.g5.6xlarge

24

96

ecs.c5.6xlarge

24

48

ecs.g8y.large

2

8

ecs.g8y.xlarge

4

16

ecs.g8y.2xlarge

8

32

ecs.g8y.4xlarge

16

64

ecs.g8y.8xlarge

32

128

ecs.g8y.16xlarge

64

256

ecs.c7a.large

2

4

ecs.c7a.xlarge

4

8

ecs.c7a.2xlarge

8

16

ecs.c7a.4xlarge

16

32

ecs.c7a.8xlarge

32

64

ecs.c7a.16xlarge

64

128

ecs.g7a.large

2

8

ecs.g7a.xlarge

4

16

ecs.g7a.2xlarge

8

32

ecs.g7a.4xlarge

16

64

ecs.g7a.8xlarge

32

128

ecs.g7a.16xlarge

64

256

GPU type

Instance type

vCPU

Memory (GB)

GPU memory

ml.gu7i.c8m30.1-gu30

8

30

1 × 24 GB

ml.gu7i.c16m60.1-gu30

16

60

1 × 24 GB

ml.gu7i.c32m188.1-gu30

32

188

1 × 24 GB

ml.gu7i.c64m376.2-gu30

64

376

2 × 24 GB

ml.gu7i.c128m752.4-gu30

80

256

4 × 24 GB

ecs.gn5i-c4g1.xlarge

4

16

1 × 8 GB

ecs.gn5i-c8g1.2xlarge

8

32

1 × 8 GB

ecs.gn5-c4g1.xlarge

4

30

1 × 16 GB

ecs.gn5-c8g1.2xlarge

8

60

1 × 16 GB

ecs.gn5-c8g1.4xlarge

16

120

2 × 16 GB

ecs.gn5-c28g1.7xlarge

28

112

1 × 16 GB

ecs.vgn6i-m4-vws.xlarge

4

23

1 × 4 GB

ecs.vgn6i-m8-vws.2xlarge

10

46

1 × 8 GB

ecs.gn6i-c4g1.xlarge

4

15

1 × 16 GB

ecs.gn6i-c8g1.2xlarge

8

31

1 × 16 GB

ecs.gn6i-c16g1.4xlarge

16

62

1 × 16 GB

ecs.gn6i-c24g1.6xlarge

24

93

1 × 16 GB

ecs.gn6i-c24g1.12xlarge

48

186

2 × 16 GB

ecs.gn6i-c24g1.24xlarge

96

372

4 × 16 GB

ecs.gn7i-c8g1.2xlarge

8

30

1 × 24 GB

ecs.gn7i-c16g1.4xlarge

16

60

1 × 24 GB

ecs.gn7i-c32g1.8xlarge

32

188

1 × 24 GB

ecs.gn7i-c32g1.16xlarge

64

376

2 × 24 GB

ecs.gn7i-c32g1.32xlarge

128

752

4 × 24 GB

ecs.gn6v-c8g1.2xlarge

8

32

1 × 16 GB

ecs.gn6v-c8g1.4xlarge

16

64

2 × 16 GB

ecs.gn6v-c8g1.8xlarge

32

128

4 × 16 GB

ecs.gn6e-c12g1.3xlarge

12

92

1 × 32 GB

ecs.gn6e-c12g1.12xlarge

48

368

4 × 32 GB

ecs.gn6e-c12g1.24xlarge

96

736

8 × 32 GB

ecs.gn7-c12g1.3xlarge

12

94

1 × 40 GB

ecs.gn7-c13g1.13xlarge

52

378

4 × 40 GB

ecs.gn7-c13g1.26xlarge

104

756

8 × 40 GB

ecs.gn7-c13g1.6xlarge

26

189

2 × 40 GB

ecs.gn7e-c16g1.4xlarge

16

125

1 × 80 GB

ecs.gn7e-c16g1.8xlarge

32

250

2 × 80 GB

ecs.gn7e-c16g1.16xlarge

64

500

4 × 80 GB

ecs.gn7e-c16g1.32xlarge

128

1000

8 × 80 GB