GPU Computing instances provide powerful computing capabilities to help you process a large number of concurrent computing tasks in real time. They are suitable for general computing scenarios such as deep learning and scientific computing. They provide a fast, stable, and elastic computing service and can be managed just like CVM instances.
Use Cases
They are suitable for AI computing and HPC scenarios, for example:
AI computing
Deep learning inference
Deep learning training
Scientific computing/HPC
Fluid dynamics
Molecular modeling
Meteorological engineering
Seismic analysis
Genomics
Note:
If your GPU instance is to be used for 3D rendering tasks, we recommend you use a rendering instance configured with a vDWs/vWs license and installed with a GRID driver. It eliminates the need to manually configure the basic environment for GPU-based graphics and image processing.
Overview
GPU Computing instances are available in the following types:
Availability | Resource Type | GPU Type | Available Image | AZ |
Featured | NVIDIA A10 | CentOS 7.2 or later Ubuntu 16.04 or later Windows Server 2016 or later | Guangzhou, Shanghai, and Beijing | |
| NVIDIA A100 NVLink 40 GB | | Guangzhou, Shanghai, Beijing, and Nanjing | |
| NVIDIA Tesla V100 NVLink 32 GB | CentOS 7.2 or later Ubuntu 14.04 or later Windows Server 2012 or later | Guangzhou, Shanghai, Beijing, Nanjing, Chengdu, Chongqing, Singapore, Mumbai, Silicon Valley, and Frankfurt | |
| NVIDIA Tesla T4 | | Guangzhou, Shanghai, Nanjing, Beijing, Chengdu, Chongqing, Hong Kong, Singapore, Bangkok, Jakarta, Mumbai, Seoul, Tokyo, Silicon Valley, Virginia, Frankfurt, and São Paulo | |
| NVIDIA Tesla T4 | CentOS 7.2–7.9 Ubuntu 14.04 or later | hanghai and Nanjing | |
Available | NVIDIA Tesla T4 | CentOS 7.2 or later Ubuntu 14.04 or later Windows Server 2012 or later | Guangzhou, Shanghai, Beijing, Nanjing, Chengdu, and Chongqing | |
| NVIDIA Tesla V100 NVLink 32 GB | | Guangzhou, Shanghai, Beijing, Nanjing, Chengdu, Chongqing, Singapore, Silicon Valley, Frankfurt, and Mumbai | |
| NVIDIA Tesla P40 | | Guangzhou, Shanghai, Beijing, Chengdu, Chongqing, Hong Kong, and Silicon Valley | |
| NVIDIA Tesla P4 | | GN6: Chengdu GN6S: Guangzhou, Shanghai, and Beijing | |
Note:
AZ: Accurate to the city level. For more information, see the instance configuration information below.
Suggestions on Computing Instance Model Selection
Tencent Cloud provides NVIDIA GPU instances to meet business needs in different scenarios. Refer to the following tables to select an NVIDIA GPU instance as needed.
The table below lists recommended GPU Computing instance models. A tick (✓) indicates that the model supports the corresponding feature. A pentagram (★) indicates that the model is recommended.
Feature/Instance | PNV4 | GT4 | GN10Xp | GN7 | GN7vi | GI3X | GN10X | GN8 | GN6GN6S |
Graphics and image processing | ✓ | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Video encoding and decoding | ✓ | - | ✓ | ★ | ★ | ★ | ✓ | ✓ | ✓ |
Deep learning training | ✓ | ★ | ★ | ✓ | ✓ | ✓ | ★ | ★ | ✓ |
Deep learning inference | ★ | ✓ | ★ | ★ | ★ | ★ | ★ | ✓ | ✓ |
Scientific computing | - | ★ | ★ | - | - | - | ★ | - | - |
Note:
These recommendations are for reference only. Select an appropriate instance model based on your needs.
To use NVIDIA GPU instances for general computing tasks, you need to install the Tesla driver and CUDA toolkit. For more information, see Installing NVIDIA Driver and Installing CUDA Driver.
To use NVIDIA GPU instances for 3D rendering tasks such as high-performance graphics processing and video encoding and decoding, you need to install a GRID driver and configure a license server.
Service Options
Pay-as-you-go billing is supported.
Instances can be launched in a VPC.
Instances can be connected to other services such as CLB, without additional management and Ops costs. Private network traffic is free of charge.
Instance Specification
Computing PNV4
Computing PNV4 supports not only general GPU computing tasks such as deep learning, but also graphics and image processing tasks such as 3D rendering and video encoding and decoding.
Use cases
GN6 and GN6S are cost-effective and applicable to the following scenarios:
Deep learning inference and small-scale training scenarios, such as:
AI inference for mass deployment
Small-scale deep learning training
Graphic and image processing scenarios, such as:
Graphic and image processing
Video encoding and decoding
Graph database
AZs
PNV4 instances are available in Guangzhou Zone 7, Shanghai Zones 4 and 5, and Beijing Zone 6.
Hardware specification
CPU: AMD EPYCTM Milan CPU 2.55 GHz, with a Max Boost frequency of 3.5 GHz.
GPU: NVIDIA® A10, providing 62.5 TFLOPS of single-precision floating point performance, 250 TOPS for INT8, and 500 TOPS for INT4.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
PNV4 instances are available in the following configurations:
Model | GPU (NVIDIA A10) | GPU Video Memory (GDDR6) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
PNV4.7XLARGE116 | 1 | 1 * 24 GB | 28 cores | 116 GB | 13 Gbps | 2.3 million | 28 |
PNV4.14XLARGE232 | 2 | 2 * 24 GB | 56 cores | 232 GB | 25 Gbps | 4.7 million | 48 |
PNV4.28XLARGE466 | 4 | 4 * 24 GB | 112 cores | 466 GB | 50 Gbps | 9.5 million | 48 |
PNV4.56XLARGE932 | 8 | 8 * 24 GB | 224 cores | 932 GB | 100 Gbps | 19 million | 48 |
Computing GT4
Computing GT4 instances are suitable for general GPU computing tasks such as deep learning and scientific computing.
Use cases
GT4 features powerful double-precision floating point computing capabilities. It is suitable for large-scale deep learning training and inference as well as scientific computing scenarios, such as:
Deep learning
High-performance database
Computational fluid dynamics
Computational finance
Seismic analysis
Molecular modeling
Genomics and others
AZs
GT4 instances are available in Guangzhou Zones 3, 4, and 6, Shanghai Zones 4 and 5, Beijing Zones 5 and 6, and Nanjing Zone 1.
Hardware specification
CPU: AMD EPYC™ ROME CPU, with a clock rate of 2.6 GHz.
GPU: NVIDIA® A100 NVLink 40 GB, providing 19.5 TFLOPS of single-precision floating point performance, 9.7 TFLOPS of double-precision floating point performance, and 600 GB/s NVLink.
Memory: DDR4 with stable computing performance.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Private network bandwidth of up to 50 Gbps is supported, with strong packet sending/receiving capabilities. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GT4 instances are available in the following configurations:
Model | GPU (NVIDIA Tesla A100 NVLink 40 GB) | GPU Video Memory (HBM2) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GT4.4XLARGE96 | 1 | 1 * 40 GB | 16 cores | 96 GB | 5 Gbps | 1.2 million | 4 |
GT4.8XLARGE192 | 2 | 2 * 40 GB | 32 cores | 192 GB | 10 Gbps | 2.35 million | 8 |
GT4.20XLARGE474 | 4 | 4 * 40 GB | 82 cores | 474 GB | 25 Gbps | 6 million | 16 |
GT4.41XLARGE948 | 8 | 8 * 40 GB | 164 cores | 948 GB | 50 Gbps | 12 million | 32 |
Note:
GPU driver: Drivers of NVIDIA Tesla 450 or later are required for NVIDIA A100 GPUs, and version 460.32.03 (Linux)/461.33 (Windows) are recommended. For more information on driver versions, see NVIDIA Driver Documentation.
Computing GN10Xp
Computing GN10Xp instances support not only general GPU computing tasks such as deep learning and scientific computing, but also graphics and image processing tasks such as 3D rendering and video encoding and decoding.
Use cases
GN10Xp features powerful double-precision floating point computing capabilities. It is suitable for the following scenarios:
Large-scale deep learning training and inference as well as scientific computing scenarios, such as:
Deep learning
High-performance database
Computational fluid dynamics
Computational finance
Seismic analysis
Molecular modeling
Genomics and others
Graphic and image processing scenarios, such as:
Graphic and image processing
Video encoding and decoding
Graph database
AZs
GN10Xp instances are available in Guangzhou Zones 3 and 4, Shanghai Zones 2 and 3, Nanjing Zone 1, Beijing Zones 4, 5, and 7, Chengdu Zone 1, Chongqing Zone 1, Singapore Zone 1, Mumbai Zone 2, Silicon Valley Zone 2, and Frankfurt Zone 1.
Hardware specification
CPU: Intel® Xeon® Platinum 8255C CPU, with a clock rate of 2.5 GHz.
GPU: NVIDIA® Tesla® V100 NVLink 32GB, providing 15.7 TFLOPS of single-precision floating point performance, 7.8 TFLOPS of double-precision floating point performance, 125 TFLOPS of deep learning accelerator performance with Tensor cores, and 300 GB/s NVLink.
Memory: DDR4, providing memory bandwidth of up to 2,666 MT/s.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GN10Xp instances are available in the following configurations:
Model | GPU (NVIDIA Tesla V100 NVLink 32 GB) | GPU Video Memory (HBM2) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GN10Xp.2XLARGE40 | 1 | 1 * 32 GB | 10 cores | 40 GB | 3 Gbps | 0.8 million | 2 |
GN10Xp.5XLARGE80 | 2 | 2 * 32 GB | 20 cores | 80 GB | 6 Gbps | 1.5 million | 5 |
GN10Xp.10XLARGE160 | 4 | 4 * 32 GB | 40 cores | 160 GB | 12 Gbps | 2.5 million | 10 |
GN10Xp.20XLARGE320 | 8 | 8 * 32 GB | 80 cores | 320 GB | 24 Gbps | 4.9 million | 16 |
Computing GN7
NVIDIA GPU instance GN7 supports not only general GPU computing tasks such as deep learning, but also graphic and image processing tasks such as 3D rendering and video encoding and decoding.
Use cases
GN6 and GN6S are cost-effective and applicable to the following scenarios:
Deep learning inference and small-scale training scenarios, such as:
AI inference for mass deployment
Small-scale deep learning training
Graphic and image processing scenarios, such as:
Graphic and image processing
Video encoding and decoding
Graph database
AZs
GN7 instances are available in Guangzhou Zones 3, 4, 6, and 7, Shanghai Zones 2, 3, 4, and 5, Nanjing Zones 1, 2, and 3, Beijing Zones 3, 5, 6, and 7, Chengdu Zone 1, Chongqing Zone 1, Hong Kong Zone 2, Singapore Zones 1, 2, and 3, Bangkok Zone 2, Jakarta Zone 2, Mumbai Zone 2, Seoul Zones 1 and 2, Tokyo Zone 2, Silicon Valley Zone 2, Frankfurt Zone 1, Virginia Zone 2, and São Paulo Zone 1.
Hardware specification
CPU: Intel® Xeon® Platinum 8255C CPU, with a clock rate of 2.5 GHz.
GPU: NVIDIA® Tesla® T4, providing 8.1 TFLOPS of single-precision floating point performance, 130 TOPS for INT8, and 260 TOPS for INT4.
Memory: DDR4, providing memory bandwidth of up to 2,666 MT/s.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GN7 instances are available in the following configurations:
Model | GPU (NVIDIA Tesla T4) | GPU Video Memory (HBM2) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GN7.2XLARGE32 | 1 | 1 * 16 GB | 8 cores | 32 GB | 3 Gbps | 0.6 million | 8 |
GN7.5XLARGE80 | 1 | 1 * 16 GB | 20 cores | 80 GB | 7 Gbps | 1.4 million | 10 |
GN7.8XLARGE128 | 1 | 1 * 16 GB | 32 cores | 128 GB | 10 Gbps | 2.4 million | 16 |
GN7.10XLARGE160 | 2 | 2 * 16 GB | 40 cores | 160 GB | 13 Gbps | 2.8 million | 20 |
GN7.20XLARGE320 | 4 | 4 * 16 GB | 80 cores | 320 GB | 25 Gbps | 5.6 million | 32 |
Video enhancement GN7vi
NVIDIA GN7vi instances are GN7 instances configured with Tencent's proprietary MPS technology and integrated with AI. They include the TSC encoding and decoding engine and image quality enhancement toolkit and are suitable for VOD and live streaming scenarios. This type of instance allows you to leverage Tencent Cloud's proprietary TSC encoding and decoding as well as AI image quality enhancement features.
AZs
GN7vi instances are available in Shanghai Zones 2, 3, 4, and 5 and Nanjing Zones 1 and 2.
Hardware specification
CPU: Intel® Xeon® Platinum 8255C CPU, with a clock rate of 2.5 GHz.
GPU: NVIDIA® Tesla® T4, providing 8.1 TFLOPS of single-precision floating point performance, 130 TOPS for INT8, and 260 TOPS for INT4.
Memory: DDR4, providing memory bandwidth of up to 2,666 MT/s.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GN7vi instances are available in the following configurations:
Model | GPU (NVIDIA Tesla T4) | GPU Video Memory (HBM2) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GN7vi.5XLARGE80 | 1 | 1 * 16 GB | 20 cores | 80 GB | 6 Gbps | 1.4 million | 20 |
GN7vi.10XLARGE160 | 2 | 2 * 16 GB | 40 cores | 160 GB | 13 Gbps | 2.8 million | 32 |
GN7vi.20XLARGE320 | 4 | 4 * 16 GB | 80 cores | 320 GB | 25 Gbps | 5.6 million | 32 |
Interference GI3X
NVIDIA GI3X supports not only general GPU computing tasks such as deep learning, but also graphics and image processing tasks such as 3D rendering and video encoding and decoding.
Use cases
GN6 and GN6S are cost-effective and applicable to the following scenarios:
Deep learning inference and small-scale training scenarios, such as:
AI inference for mass deployment
Small-scale deep learning training
Graphic and image processing scenarios, such as:
Graphic and image processing
Video encoding and decoding
Graph database
AZs
GI3X instances are available in Guangzhou Zone 3, Shanghai Zones 4 and 5, Nanjing Zones 1 and 2, Beijing Zones 5 and 6, Chengdu Zone 1, and Chongqing Zone 1.
Hardware specification
CPU: AMD EPYC™ ROME CPU 2.6 GHz, with a Max Boost frequency of 3.3 GHz.
GPU: NVIDIA® Tesla® T4, providing 8.1 TFLOPS of single-precision floating point performance, 130 TOPS for INT8, and 260 TOPS for INT4.
Memory: Latest eight-channel DDR4 with stable computing performance.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GI3X instances are available in the following configurations:
Model | GPU (NVIDIA Tesla T4) | GPU Video Memory (GDDR6) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GI3X.8XLARGE64 | 1 | 1 * 16 GB | 32 cores | 64 GB | 5 Gbps | 1.4 million | 8 |
GI3X.22XLARGE226 | 2 | 2 * 16 GB | 90 cores | 226 GB | 13 Gbps | 3.75 million | 16 |
GI3X.45XLARGE452 | 4 | 4 * 16 GB | 180 cores | 452 GB | 25 Gbps | 7.5 million | 32 |
Computing GN10X
Computing GN10X supports not only general GPU computing tasks such as deep learning and scientific computing, but also graphics and image processing tasks such as 3D rendering and video encoding and decoding.
Use cases
GN10X features powerful double-precision floating point computing capabilities. It is suitable for the following scenarios:
Large-scale deep learning training and inference as well as scientific computing scenarios, such as:
Deep learning
High-performance database
Computational fluid dynamics
Computational finance
Seismic analysis
Molecular modeling
Genomics and others
Graphic and image processing scenarios, such as:
Graphic and image processing
Video encoding and decoding
Graph database
AZs
GN10X instances are available in Guangzhou Zones 3 and 4, Shanghai Zones 2 and 3, Nanjing Zone 1, Beijing Zones 4, 5, and 7, Chengdu Zone 1, Chongqing Zone 1, Singapore Zone 1, Silicon Valley Zone 2, Frankfurt Zone 1, and Mumbai Zone 2.
Hardware specification
CPU: GN10X is configured with an Intel® Xeon® Gold 6133 CPU, with a clock rate of 2.5 GHz.
GPU: NVIDIA® Tesla® V100 NVLink 32GB, providing 15.7 TFLOPS of single-precision floating point performance, 7.8 TFLOPS of double-precision floating point performance, 125 TFLOPS of deep learning accelerator performance with Tensor cores, and 300 GB/s NVLink.
Memory: DDR4, providing memory bandwidth of up to 2,666 MT/s.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GN10X instances are available in the following configurations:
Model | GPU (NVIDIA Tesla V100 NVLink 32 GB) | GPU Video Memory (HBM2) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GN10X.2XLARGE40 | 1 | 1 * 32 GB | 8 cores | 40 GB | 3 Gbps | 0.8 million | 2 |
GN10X.9XLARGE160 | 4 | 4 * 32 GB | 36 cores | 160 GB | 13 Gbps | 2.5 million | 9 |
GN10X.18XLARGE320 | 8 | 8 * 32 GB | 72 cores | 320 GB | 25 Gbps | 4.9 million | 16 |
Computing GN8
NVIDIA GPU instance GN8 supports not only general GPU computing tasks such as deep learning, but also graphic and image processing tasks such as 3D rendering and video encoding and decoding.
Use cases
GN8 is applicable to the following scenarios:
Deep learning training and inference scenarios, such as:
AI inference with high throughput
Deep learning
Graphic and image processing scenarios, such as:
Graphic and image processing
Video encoding and decoding
Graph database
AZs
GN8 instances are available in Guangzhou Zone 3, Beijing Zones 2 and 4, Chengdu Zone 1, Hong Kong Zone 2, Shanghai Zone 3, Chongqing Zone 1, and Silicon Valley Zone 1.
Hardware specification
CPU: Intel® Xeon® E5-2680 v4 CPU, with a clock rate of 2.4 GHz.
GPU: NVIDIA® Tesla® P40, providing 12 TFLOPS of single-precision floating point performance and 47 TOPS for INT8.
Memory: DDR4, providing memory bandwidth of up to 2,666 MT/s.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GN8 instances are available in the following configurations:
Model | GPU (NVIDIA Tesla P40) | GPU Video Memory (HBM2) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GN8.LARGE56 | 1 | 24 GB | 6 cores | 56 GB | 1.5 Gbps | 0.45 million | 8 |
GN8.3XLARGE112 | 2 | 48 GB | 14 cores | 112 GB | 2.5 Gbps | 0.5 million | 8 |
GN8.7XLARGE224 | 4 | 96 GB | 28 cores | 224 GB | 5 Gbps | 0.7 million | 14 |
GN8.14XLARGE448 | 8 | 192 GB | 56 cores | 448 GB | 10 Gbps | 0.7 million | 28 |
Computing GN6 and GN6S
NVIDIA GPU instances GN6 and GN6S support not only general GPU computing tasks such as deep learning, but also graphic and image processing tasks such as 3D rendering and video encoding and decoding.
Use cases
GN6 and GN6S are cost-effective and applicable to the following scenarios:
Deep learning inference and small-scale training scenarios, such as:
AI inference for mass deployment
Small-scale deep learning training
Graphic and image processing scenarios, such as:
Graphic and image processing
Video encoding and decoding
Graph database
AZs
GN6 and GN6S instances are available in the following AZs:
GN6: Chengdu Zone 1.
GN6S: Guangzhou Zone 3, Shanghai Zones 2, 3, and 4, and Beijing Zones 4 and 5.
Hardware specification
CPU: GN6 is configured with an Intel® Xeon® E5-2680 v4 CPU, with a clock rate of 2.4 GHz. GN6S is configured with an Intel® Xeon® Silver 4110 CPU, with a clock rate of 2.1 GHz.
GPU: NVIDIA<® Tesla® P4, providing 5.5 TFLOPS of single-precision floating point performance and 22 TOPS for INT8.
Memory: DDR4, providing memory bandwidth of up to 2,666 MT/s.
Storage: Select the appropriate CBS cloud disk type. To expand the cloud disk capacity, create and mount an elastic cloud disk.
Network: Network optimization is enabled by default. The network performance of an instance depends on its specification. You can purchase public network bandwidth as needed.
GN6 and GN6S instances are available in the following configurations:
Model | GPU (NVIDIA Tesla P4) | GPU Video Memory (HBM2) | vCPU | Memory (DDR4) | Private Network Bandwidth | Packets In/Out(PPS) | Number of Queues |
GN6.7XLARGE48 | 1 | 8 GB | 28 cores | 48 GB | 5 Gbps | 1.2 million | 14 |
GN6.14XLARGE96 | 2 | 16 GB | 56 cores | 96 GB | 10 Gbps | 1.2 million | 28 |
GN6S.LARGE20 | 1 | 8 GB | 4 cores | 20 GB | 5 Gbps | 0.5 million | 8 |
GN6S.2XLARGE40 | 2 | 16 GB | 8 cores | 40 GB | 9 Gbps | 0.8 million | 8 |
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