tencent cloud

Serverless Cloud Function

Release Notes and Announcements
Release Notes
Announcements
User Guide
Product Introduction
Overview
Related Concepts
How It Works
Strengths
Scenarios
Related Products
Purchase Guide
Billing Overview
Billing Mode
Billable Items and Billing Modes
Function Computing Power Support
Free Tier
SCF Pricing
Billing Example
Payment Overdue
Getting Started
Creating Event Function in Console
User Guide
Quota Management
Managing Functions
Web Function Management
Log Management
Concurrence Management
Trigger Management
Function URL
A Custom Domain Name
Version Management
Alias Management
Permission Management
Running Instance Management
Plugin Management
Managing Monitors and Alarms
Network Configuration
Layer Management
Execution Configuration
Extended Storage Management
DNS Caching Configuration
Resource Managed Mode Management
Near-Offline Resource Hosting Model
Workflow
Triggers
Trigger Overview
Trigger Event Message Structure Summary
API Gateway Trigger
COS Trigger
CLS Trigger
Timer Trigger
CKafka Trigger
Apache Kafka Trigger
MQTT Trigger
Trigger Configuration Description
MPS Trigger
CLB Trigger Description
TencentCloud API Trigger
Development Guide
Basic Concepts
Testing a Function
Environment Variables
Dependency Installation
Using Container Image
Error Types and Retry Policies
Dead Letter Queue
Connecting SCF to Database
Automated Deployment
Cloud Function Status Code
Common Errors and Solutions
Developer Tools
Serverless Web IDE
Calling SDK Across Functions
Third-Party Tools
Code Development
Python
Node.js
Golang
PHP
Java
Custom Runtime
Deploying Image as Function
Web Framework Development
Deploying Framework on Command Line
Quickly Deploying Egg Framework
Quickly Deploying Express Framework
Quickly Deploying Flask Framework
Quickly Deploying Koa Framework
Quickly Deploying Laravel Framework
Quickly Deploying Nest.js Framework
Quickly Deploying Next.js Framework
Quickly Deploying Nuxt.js Framework
Quickly Deploying Django Framework
Use Cases
Overview
Solutions with Tencent Cloud Services
Business Development
TRTC Practices
COS Practices
CKafka Practice
CLS
CLB Practice
MPS
CDN
CDWPG
VOD
SMS
ES
Scheduled Task
Video Processing
Success Stories
Tencent Online Education
Online Video Industry
Tencent Online Education
Best Practice of Tencent IEG Going Global
API Documentation
History
Introduction
API Category
Making API Requests
Other APIs
Namespace APIs
Layer Management APIs
Async Event Management APIs
Trigger APIs
Function APIs
Function and Layer Status Description
Data Types
Error Codes
SDK Documentation
FAQs
General
Web Function
Billing FAQs
Network FAQs
Log FAQs
SCF utility class
Event Handling FAQs
API Gateway Trigger FAQs
Related Agreement
Service Level Agreement
Contact Us
Glossary

Function Computing Power Support

PDF
フォーカスモード
フォントサイズ
最終更新日: 2025-04-30 19:16:29
SCF currently supports CPU and GPU computing power. This document introduces the detailed parameter information of different computing powers.

CPU Computing Power

Memory

Specify the available memory size for function runtime. The minimum is 64 MB, the maximum is 120 GB, the default is 128 MB, and the incremental step length is 128 MB. When the memory is greater than or equal to 6 GB, a large specification resource application is required.

CPU

The CPU processing capability of SCF is directly proportional to the function configuration memory. You can increase the memory configuration to get larger CPU computing power. 1280 MB corresponds to 1 accounting power, and 3072 MB corresponds to 2 accounting powers. When the memory is equal to or greater than 6 GB (6144 MB), the CPU computing power is further released, as shown in the table below:
Execution Memory (MB)
CPU Computing Power (Cores)
64
0.1
128
0.1
256
0.2
384
0.3
512
0.4
640
0.5
768
0.6
896
0.7
1024
0.8
1152
0.9
1280
1
1408
1.1
1536
1.2
1664
1.3
1792
1.4
1920
1.5
2048
1.6
2176
1.7
2304
1.8
2432
1.9
2560
2
2688
2
2816
2
2944
2
3072
2
6144
4
14336
8
30720
16
61440
32
122880
64

GPU Computing Power

SCF supports multiple computing powers such as compute-oriented and rendering-oriented for T4 cards, as well as compute-oriented for A10 cards. The detailed parameter information of supported specifications is shown in the table below.
GPU Instance Type
Specification
Number of Cards
Card Type
CPU (Cores)
Memory (GB)
Disk (GB)
Compute-Optimized GN7
GN7.LARGE20 (discontinued)
0.25
T4
4
20
10
GN7.2XLARGE40 (discontinued)
0.5
10
40
10
GN7.2XLARGE32 (default specification for Stable Diffusion AI painting application scenario, not yet open for other scenarios)
1
8
32
10
GN7.5XLARGE80
1
20
80
10
Rendering GN7vw
GN7vw.LARGE16
0.25
T4
4
16
10
GN7vw.2XLARGE32
0.5
8
32
10
GN7vw.4XLARGE64
1
16
64
10
Compute-Optimized PNV4
PNV4.7XLARGE116
1
A10
28
116
10

Must-Knows

Due to the scarcity of resources for large-spec instances and GPU instances, their elasticity capabilities are insufficient. Recommend you use preset concurrency for resource handling to guarantee resource supply stability.

Recommended Usage of GPU

Preset Concurrency: Preset concurrency supports concurrent instances to start in advance according to the configuration. At the same time, the SCF will not proactively reclaim them and will guarantee as much as possible that there are a corresponding number of concurrent instances that can process requests. You can use this feature to set the preset concurrency quota for a specified version of the function. By configuring preset concurrency, you can prepare computing resources in advance and reduce the time taken caused by cold startup, initialization of runtime environment, and business code initialization.

GPU Computing Power Billing Mode

GPU function computing power and CPU computing power share the same billing mode, which charges based on memory usage within a certain time. For details, see Billing Overview.

GPU Computing Power Hybrid Card Type Scheduling

SCF GPU hybrid card type scheduling feature supports businesses to select and assign different GPU models, addressing insufficient resources of a single card type and enhancing cluster computing power resource usage rate and supply capacity.

Operation Steps

1. For functions of container image type, specification selection is supported during creation and updating by clicking.
2. Check corresponding GPU resource specifications in the pop-up: On existing GPU types, users can check multiple card types and sort the checked ones to determine scheduling priority.



ヘルプとサポート

この記事はお役に立ちましたか?

フィードバック