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Platform For AI:Billing for Elastic Algorithm Service (EAS)

Last Updated:May 27, 2026

EAS supports pay-as-you-go, subscription, and Serverless billing for computing resources, system disks, and dedicated gateways.

Billing overview

EAS charges cover computing resources, system disks, and dedicated gateways:

  • Computing resources: Public resource groups, dedicated resource groups, and Lingjun Intelligent Computing resources.

  • System disk (optional): Each node includes a free quota (30 GiB for public resource groups, 200 GiB for dedicated resource groups). Usage beyond the free quota is billed separately.

  • Dedicated gateway (optional): Deployments use a free shared gateway by default. For security isolation, access control, or a custom domain name, purchase a dedicated gateway.

Billing methods:

  • Pay-as-you-go: Billed by service runtime, not by calls. Suitable for variable workloads.

  • Subscription: Prepaid with discounted rates. Suitable for long-term, stable workloads.

EAS also offers a free-to-deploy Serverless version for SDWebUI and ComfyUI, billed only during request processing.

Important

Other Alibaba Cloud services (Elastic IP Address, OSS, NAS) are billed separately.

image

Billing period

Pay-as-you-go

Understand when pay-as-you-go billing starts and stops to avoid unexpected charges. Stop idle services promptly.

Resource type

Billing start time

Billing end time

Public resources

Billing starts when the service enters the running state. Charges apply even if no service calls are made.

Billing stops when the model service is stopped and its resources are released.

Important

Stop or delete the service instance to stop billing.

Dedicated resources

Billing starts when the machine is created and enters the running state. Charges apply even if no services are deployed on the machine.

  • When the machine resource is deleted.

  • When the machine enters the stopped state.

Important

The stopped state is triggered only by overdue payments. You cannot manually stop a machine to pause billing. To stop charges, you must delete the pay-as-you-go machine.

System disk

Billing starts after the system disk is purchased.

  • When the machine in the dedicated resource group is deleted.

  • When the service deployed using public resources is deleted.

Dedicated gateway

Billing starts after the dedicated gateway is created.

When the dedicated gateway is deleted.

Service scaling

  • Scale-out: Billing for new resources starts when the scale-out operation completes.

  • Scale-in: Billing for released resources stops when the release operation completes. You are still billed for the remaining resources.

Subscription

Resource type

Billing start time

Billing end time

Dedicated resources

Billing starts at 00:00:00 on the day after the purchase.

The expiration time.

AI computing resources (Lingjun resources)

Billing starts at 00:00:00 on the day after the purchase.

The expiration time.

System disk

Billing starts after the system disk is purchased.

The expiration time.

Dedicated gateway

Billing starts after the dedicated gateway is created.

The expiration time.

Serverless

Serverless Edition is free to deploy. You pay only for actual request processing time.

  • Example: If an image generation request from the WebUI takes 10 seconds to complete, you are billed for those 10 seconds.

  • Usage limits: Only SDWebUI and ComfyUI support Serverless Edition. Pricing is on the deployment page.

Billable items

Billing methods by resource type:

  • Pay-as-you-go resources are billed per minute (except Serverless).

  • Stop idle pay-as-you-go public services to avoid charges.

  • Availability varies by region.

Billable item

Billing method

Billing formula

Unit price

Public resources

Pay-as-you-go

(Resource-based configuration)

Billable amount for each model service = Number of instances × (Number of CPU cores × (Unit price / 60) + memory size × (Unit price / 60)) × Duration (in minutes)

For pricing details, see Resource-based configuration.

Prices are listed per hour but billed per minute. Divide by 60 for the per-minute rate.

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

Billable amount for each model service = Number of instances × (Unit price of the instance type / 60) × Duration (in minutes)

Pricing varies by region and instance type. Console prices are final.

For a list of supported instance types, see Appendix: Instance types for public resource groups.

Dedicated resources

Pay-as-you-go

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

For pricing details, see the EAS Dedicated Machine Postpay purchase page.

Subscription

Billable amount for each resource group = Number of instances × Unit price × subscription duration (in months)

For pricing details, see the EAS Dedicated Machine Prepay purchase page.

AI computing resources (Lingjun resources)

Subscription

Purchase Lingjun resources by subscription and use the resulting quota to deploy EAS services.

For details on the billing of AI computing resources, see Billing of AI computing resources.

System disk

Pay-as-you-go

Billable amount = Number of instances × system disk capacity (GiB) × (Unit price / 60) × Usage duration (in minutes)

For pricing details, see the Block Storage (ESSD PL1) page.

Subscription

Billable amount = Number of instances × system disk capacity (GiB) × Unit price × subscription duration (in months)

For pricing details, see the Block Storage (ESSD PL1) page.

Dedicated gateway

Pay-as-you-go

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

For pricing details, see the EAS Dedicated Gateway Postpay page.

Subscription

Billable amount = Unit price of the gateway × Number of gateway nodes × subscription duration (in months)

For pricing details, see the EAS Dedicated Gateway Prepay page.

Service inference (Serverless)

Billed by actual request processing time.

Billable amount = service inference duration (in seconds) × Unit price (per second)

Only SDWebUI and ComfyUI support Serverless deployment. Pricing is on the deployment page.

Table 1. Resource-based configuration

Important

Pricing is for reference only. Actual fees are shown on the console or purchase page.

Resource type

Pricing

CPU

0.03 (USD/core/hour)

Memory

0.004 (USD/GB/hour)

Pricing disclaimer

All prices are for reference only. Check your bill for actual charges.

Billing examples

Important

Examples are for reference only. Actual fees are based on console or purchase page prices.

Public resource group

Pay-as-you-go

  • Scenario: Suppose you deploy a model service in a public resource group in the China (Hangzhou) region using the Specified resources option.

    • At 09:00:00, the service enters the running state and uses 2 CPU cores and 8 GB of memory.

    • At 10:00:00, the service scales in to 1 CPU core and 4 GB of memory.

    • At 11:00:00, the service scales out to 4 CPU cores and 16 GB of memory.

    • At 12:00:00, the service enters the stopped state.

  • Cost calculation:

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

Dedicated resource group

Subscription

  • Scenario:

    Suppose you purchase two instances, each with a 4-core CPU and a 15 GB NVIDIA T4 GPU, in the China (Hangzhou) region with a 3-month subscription. The price is 570 USD/month per instance. This price is for reference only.

  • Cost calculation:

  • Total amount = 2 × 570 × 3 = 3,420 USD

Pay-as-you-go

  • Scenario:

    Suppose you purchase two ecs.g6.6xlarge instances (24-core CPU, 96 GB memory) in the China (Hangzhou) region using pay-as-you-go for 45 minutes. The price is 1.02 USD/hour per instance. This price is for reference only.

  • Cost calculation:

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

System disk

Subscription

  • Scenario: Suppose you purchase two instances in a dedicated resource group in the China (Hangzhou) region with a 3-month subscription, each with a 300 GiB system disk.

  • Cost calculation:

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

Pay-as-you-go

  • Dedicated resource group

    • Scenario: Suppose you purchase two instances in a dedicated resource group in the China (Hangzhou) region using pay-as-you-go. Each instance has a 300 GiB system disk and runs for 5 hours.

    • Cost calculation:

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

    • Scenario: Suppose you purchase two instances in a public resource group in the China (Hangzhou) region using pay-as-you-go. Each instance has a 300 GiB system disk and runs for 5 hours.

    • Cost calculation:

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

Public resource group instances

The following tables list some public resource group instance types. For the full list, check the Resource Deployment Information section on the Deploy Service page or Custom Deployment. Supported types vary by region; console specifications take precedence.

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