tencent cloud

Cloud GPU Service

Release Notes and Announcements
Release Notes
Announcements
Product Introduction
Overview
Strengths
Scenarios
Notes
Instance Types
Computing Instance
Rendering Instance
Billing
Billing Overview
Renewal
Getting Started
User Guide
Logging In to Instances
Restarting Instances
Installing NVIDIA Driver
Uninstalling NVIDIA Driver
Upgrading NVIDIA Driver
Using GPU Monitoring and Alarm
Use Cases
Installing NVIDIA Container Toolkit on a Linux Cloud GPU Service
Using Windows Cloud GPU Service to build a Deep Learning Environment
Implementing Image Quality Enhancement with GN7vi Instances
Using Docker to Install TensorFlow and Set GPU/CPU Support
Using GPU Instance to Train ViT Model
Troubleshooting
GPU Instance Troubleshooting Guide
Troubleshooting Common Xid Errors
Collecting Log for GPU Instances
GPU Usage Shows 100%
VNC Login Failures
FAQs
Related Agreement
Special Terms for Committed Sales Model
Contact Us

Overview

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마지막 업데이트 시간: 2026-03-11 11:49:06
Cloud GPU Service is a fast, stable and elastic GPU-based computing service. It's applicable to training or reasoning of deep learning, graphics and image processing, and scientific computing, etc. Cloud GPU Service is easily managed in the same way as the CVMs. With the powerful computing performance of processing massive data, it can effectively relieve the computing pressure of users and improve the efficiency and competitiveness of business processing.

Comparison between Cloud GPU Service and Self-built GPU Computing

Advantages
Cloud GPU Service
Self-built GPU Computing
Elastic
In just a few minutes, you can easily obtain one or more high-performance computing instances.
It can be customized flexibly as needed, and upgraded to an instance specification with higher performance and larger capacity with just one click, to achieve rapid, smooth expansion, and satisfy the requirement for fast business development.
Fixed configuration makes it hard to satisfy the ever-changing requirements.
High-performance
It supports GPU pass-through to make the most advantage of GPU.
Peak computing capacity for a single machine: 125.6T Flops for single-precision floating point computing and 62.4T Flops for double-precision floating point computing.
Users have to perform disaster recovery manually, depending on the robustness of hardware.
A single point of failure may occur on physical servers. Data security is uncontrollable.
Easy-to-use
It can be seamlessly connected to CVM, CLB and many other Tencent Cloud products. Private network traffic is free of charge.
Designed for ease of use, it is managed in the same way as CVMs, without the need to use jump server for login.
It provides clear guides on installation and deployment of GPU driver to make it easier for users to get started with it.
Users must purchase installation management service to achieve automatic hardware expansion and driver installation.
Jump server is required for login with complicated operation procedures.
Secure
Resources are completely isolated among different users to ensure the data security.
Complete security groups and network ACL settings allow you to control and securely filter the inbound and outbound network traffic to or from instances and subnets.
It can be seamlessly connected to Tencent Cloud security serices, just the same as CVM.
Resources are shared among different users, and data is not isolated.
Additional security protection services must be purchased.
Low-cost
It supports yearly/monthly subscription. You can purchase physical servers without the need to make a huge one-off investment.
Hardware is updated with the mainstream GPU, eliminating the need to replace the hardware after each update.
With low server OPS cost, you can effectively reduce investment in infrastructure construction without the need to purchase and prepare hardware resources in advance.
High server investment and operating costs.
Due to high power consumption of devices, hardware modification is required.
High IT Ops costs are required to ensure service stability.


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