Function Compute supports the following billing methods: free trial quotas, pay-as-you-go, and resource plans. The compute unit (CU) serves as a unified billing metric. This topic describes the unit prices of CU usage and the conversion factors that are used to convert the number of function invocations, active vCPU usage, idle vCPU usage, memory usage, disk usage, active GPU usage, and idle GPU usage to CU usage.
You can log on to the Function Compute console and view the following information in the Global Statistics section of the Overview page: the number of function invocations, active vCPU usage, idle vCPU usage, memory usage, disk usage, and active and idle GPU usage (including Tesla series and Ada series). You can use the price calculator to convert the preceding resource usage into CU usage and calculate the total fee. The resource usage of all Resource Access Management (RAM) users is aggregated and billed to your Alibaba Cloud account.
NoteStarting from 00:00 on January 5, 2024, Cloud Data Transfer (CDT) is used to bill outbound Internet traffic of Function Compute. You are charged for Internet traffic based on the billing rules of CDT. For more information about the billing rules of CDT, see Services and metering methods supported by CDT. For information about the free quota of Internet traffic, see [Product changes] Change of free Internet traffic quota.
Starting from August 27, 2024, the original billable items of Function Compute, which include the number of function invocations, active vCPU usage, idle vCPU usage, memory usage, disk usage, and active and idle GPU usage, are no longer used. The preceding resource usage is converted into CU usage based on established conversion factors. Charges are calculated based on the unit prices of this CU usage. The CU conversion factor varies based on resource type. For more information, see Conversion factors.
If resources of other Alibaba Cloud services are consumed when you use Function Compute, pay attention to the billing of the related services.
Function Compute provides a complimentary trial CU plan for first-time users. If you do not purchase additional resource plans, any usage exceeding the trial quota in each cycle is billed on a pay-as-you-go basis. For more information, see Trial quotas.
Resource plansFunction Compute provides five tiers of CU resource plans. After you buy a resource plan, it is preferentially used to offset resource usage. When the quota in the resource plan is exhausted, you are charged on a pay-as-you-go basis. Resource plans allow you to utilize a fixed amount of resources at a discounted rate, helping you reduce costs. For more information, see Resource plans.
Pay-as-you-goYou are charged for the computing resources that you actually consume. For more information, see Pay-as-you-go.
PricesCU usage is billed monthly on a tiered basis. The following table describes the details.
Tier
CU usage (CU)
Unit price
Discounted unit price
August 27, 2024 to August 27, 2025
1
(0, 100 million]
USD 0.000020/CU
USD 0.0000160/CU
2
(100 million, 500 million]
USD 0.000017/CU
USD 0.0000136/CU
3
> 500 million
USD 0.000014/CU
USD 0.0000112/CU
Conversion factorsThe original billable items of Function Compute, including the number of function invocations, active vCPU usage, idle vCPU usage, memory usage, disk usage, active GPU usage, and idle GPU usage are converted to CU usage based on the following formula: Resource usage × Conversion factor = CU Usage.
The following table lists the conversion factors.
Billable item
Number of function invocations
Active vCPU usage
Idle vCPU usage
Memory usage
Disk usage
Tesla series
Active GPU usage
Tesla series
Idle GPU usage
Ada series
Active GPU usage
Ada series
Idle GPU usage
Unit
CU/10,000 invocations
CU/vCPU-second
CU/vCPU-second
CU/GB-second
CU/GB-second
CU/GB-second
CU/GB-second
CU/GB-second
CU/GB-second
CU conversion factor
75
1
0
0.15
0.05
2.1
0.5
1.5
0.25
TermsIdle mode: Function Compute supports the idle mode feature. When this feature is enabled, CPU and GPU-accelerated instances are classified as either active or idle, depending on whether they are processing requests.
Active instances: instances that are processing requests.
Idle instances: instances that are not processing requests.
Execution duration: Instances in Function Compute can operate in both provisioned and on-demand modes. The measurement of execution duration differs between these two modes. For more information, see Instance types and usage modes.
On-demand mode: Function Compute automatically allocates and releases function instances. The billing of an on-demand function instance starts when the function instance starts to execute requests and ends when the requests are executed.
Provisioned mode: Function instances are allocated, released, and managed by yourself. The billing of a provisioned instance starts when Function Compute allocates the instance and ends when you release the instance.
In provisioned mode, you are charged for your instances regardless of whether they are processing requests or not, until you release them. Therefore, when your provisioned instances are not processing any requests and charges continue to incur, release unneeded instances at your earliest opportunity to avoid unnecessary fees. For more information, see Configure auto scaling rules.
Billing examplesAssume that you have consumed the following resources in a month: 800 million vCPU-seconds of vCPU usage, 2 billion GB-seconds of memory usage, 0 GB-seconds of disk usage, 100 million GB-seconds of active GPU usage (Tesla series), 400 million GB-seconds of idle GPU usage (Tesla series), and 12 billion function invocations. The following table shows the CU usage and total cost.
Resource usage type
Total usage
Conversion factor
Converted CU usage
Active vCPU usage
800,000,000 vCPU-seconds
1 CU/vCPU-second
800,000,000 CU
Memory usage
2,000,000,000 GB-seconds
0.15 CU/GB-second
300,000,000 CU
Disk usage
0 GB-seconds
0.05 CU/GB-second
Note: The disk size of 512 MB is free. You are charged for disk capacity exceeding 512 MB.
0 CU
Tesla series
Active GPU usage
100,000,000 GB-seconds
2.1 CU/GB-second
210,000,000 CU
Tesla series
Idle GPU usage
400,000,000 GB-seconds
0.5 CU/GB-second
200,000,000 CU
Number of function invocations
12,000,000,000 invocations
0.0075 CU/invocation
90,000,000 CU
Total CU usage: 1,600,000,000 CUs
Fee = Tier 1 unit price × Tier 1 usage + Tier 2 unit price × Tier 2 usage + Tier 3 unit price × Tier 3 usage = USD 0.000020/CU × 100,000,000 CUs + USD 0.000017/CU × 400,000,000 CUs + USD 0.000014/CU × 1,100,000,000 CUs = USD 24,200
ImportantThe vCPU usage, memory usage, disk usage, and GPU usage are calculated based on the specifications that you configure for your function and durations of usage, not based on the actual amount of consumed resources during function invocations.
Billing examples for provisioned instances CPU instancesThis section presents a billing example for provisioned CPU instances. In this scenario, you have created a function with the following specifications: 0.35 vCPUs, 512 MB of memory, and 512 MB of disk size. The function instances are provisioned for a total of 50 hours, during which they are active for 10 hours and idle for 40 hours. A total of 1 million invocations are initiated. The following table lists the CU usage and the total billable amount.
NoteIn provisioned mode of CPU instances, memory usage and disk usage are billed based on the total execution duration. The active vCPU usage is billed based on the active execution duration.
Resource usage type
Usage
Conversion factor
Converted CU usage
Active vCPU usage
12,600 vCPU-seconds
1 CU/vCPU-second
12,600 CU
Idle vCPU usage
50,400 vCPU-seconds
0 CU/vCPU-second
Note: No fees are incurred for idle vCPUs.
0 CU
Memory usage
90,000 GB-seconds
0.15 CU/GB-second
13,500 CU
Disk usage
0 GB-seconds
0.05 CU/GB-second
Note: The disk size of 512 MB is free. You are charged for disk capacity exceeding 512 MB.
0 CU
Number of function invocations
1,000,000 invocations
0.0075 CU/invocation
7,500 CU
Total CU usage: 33,600 CUs
Fee = Tier 1 unit price × Tier 1 usage = USD 0.000020/CU × 33,600 CUs = USD 0.67
GPU-accelerated instancesThis section presents a billing example for GPU-accelerated instances. In this scenario, you have created a GPU function with the following specifications: 16 GB of GPU memory provided by a Tesla series GPU, 8 vCPUs, 32 GB of memory, and 512 MB of disk size. The function instances are provisioned for a total of 50 hours, during which they are active for 10 hours and idle for 40 hours. A total of 1 million invocations are initiated. The following table lists the CU usage and the total billable amount.
NoteIn provisioned mode of GPU-accelerated instances, memory usage and disk usage are billed based on the total execution duration. The active vCPU and GPU usage is billed based on the active execution duration. vCPUs and GPUs of GPU-accelerated instances are frozen when no requests are made to the instances.
Resource usage type
Usage
Conversion factor
Converted CU usage
Active vCPU usage
288,000 vCPU-seconds
1 CU/vCPU-second
288,000 CU
Idle vCPU usage
1,152,000 vCPU-seconds
0 CU/vCPU-second
Note: No fees are incurred for idle vCPUs.
0 CU
Memory usage
5,760,000 GB-seconds
0.15 CU/GB-second
864,000 CU
Disk usage
0 GB-seconds
0.05 CU/GB-second
Note: The disk size of 512 MB is free. You are charged for disk capacity exceeding 512 MB.
0 CU
Tesla series
Active GPU usage
576,000 GB-seconds
2.1 CU/GB-second
1,209,600 CU
Tesla series
Idle GPU usage
2,304,000 GB-seconds
0.5 CU/GB-second
1,152,000 CU
Number of function invocations
1,000,000 invocations
0.0075 CU/invocation
7,500 CU
Total CU usage: 3,521,100 CUs
Fee = Tier 1 unit price × Tier 1 usage = USD 0.000020/CU × 3,521,100 CUs = USD 70.42
FAQHow do I view overdue payments and why do overdue payments occur?
Why does billing continue after I stop services in Function Compute?
What resource usage items are involved in the running of GPU-accelerated instances?
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