Elastic GPU Service provides GPU-accelerated computing capabilities and ready-to-use, scalable GPU computing resources. Elastic GPU Service is an elastic computing service provided by Alibaba Cloud. This service combines the computing power of GPUs and CPUs to address the challenges of scenarios such as AI, high-performance computing, and professional graphics and image processing.
Background information
Before you read further in this topic, you must be familiar with the following information:
Classification and naming of instance types. Familiarize yourself with the instance family categories, naming conventions of instance types, and differences between instance families. For more information, see Classification and naming of instance types.
Instance type metrics. For information about the metrics of instance types, see Instance type metrics.
Instructions for selecting instance types based on your business scenarios. For more information, see Instance type selection.
After you determine an instance type for your use case, you may need to learn about the following information:
Regions in which the instance type is available for purchase. Instance types that are available for purchase vary based on the region. You can go to the Instance Types Available for Each Region page to view the instance types available for purchase in each region.
Estimated instance costs. You can calculate the price of instances that uses different billing methods in the Price Calculator.
Instructions for purchasing an instance. You can go to the ECS instance buy page to place a purchase order for instances.
You may be concerned about the following information:
Retired instance families. If you cannot find an instance type in this topic, the instance type may be in a retired instance family. For information about retired instance families, see Retired instance families.
Supported instance type changes. Before you change the instance type of an instance, check whether the instance type can be changed and identify compatible instance types. For more information, see Instance types and families that support instance type changes.
vGPU-accelerated instance family | GPU-accelerated compute-optimized instance family | Not recommended instance families (If the following instance families are sold out, we recommend that you use the instance families in the preceding columns.) |
sgn7i-vws, vGPU-accelerated instance family with shared CPUs
Introduction:
This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data storage and model loading can be performed more quickly.
Instances of this instance family share CPU and network resources to maximize the utilization of underlying resources. Each instance has exclusive access to its memory and GPU memory to provide data isolation and performance assurance.
NoteIf you want to use exclusive CPU resources, select the vgn7i-vws instance family.
This instance family comes with an NVIDIA GRID vWS license and provides certified graphics acceleration capabilities for Computer Aided Design (CAD) software to meet the requirements of professional graphic design. Instances of this instance family can serve as lightweight GPU-accelerated compute-optimized instances to reduce the costs of small-scale AI inference tasks.
Supported scenarios:
Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification
Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming
3D modeling in fields that require the use of Ice Lake processors, such as animation and film production, cloud gaming, and mechanical design
Compute:
Uses NVIDIA A10 GPUs that have the following features:
Innovative NVIDIA Ampere architecture
Support for acceleration features, such as vGPU, RTX, and TensorRT, to provide diversified business support
Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports Enterprise SSDs (ESSDs) and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline/burst bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.sgn7i-vws-m2.xlarge | 4 | 15.5 | NVIDIA A10 * 1/12 | 24GB * 1/12 | 1.5/5 | 500,000 | 4 | 2 | 2 | 1 |
ecs.sgn7i-vws-m4.2xlarge | 8 | 31 | NVIDIA A10 * 1/6 | 24GB * 1/6 | 2.5/10 | 1,000,000 | 4 | 4 | 6 | 1 |
ecs.sgn7i-vws-m8.4xlarge | 16 | 62 | NVIDIA A10 * 1/3 | 24GB * 1/3 | 5/20 | 2,000,000 | 8 | 4 | 10 | 1 |
ecs.sgn7i-vws-m2s.xlarge | 4 | 8 | NVIDIA A10 * 1/12 | 24GB * 1/12 | 1.5/5 | 500,000 | 4 | 2 | 2 | 1 |
ecs.sgn7i-vws-m4s.2xlarge | 8 | 16 | NVIDIA A10 * 1/6 | 24GB * 1/6 | 2.5/10 | 1,000,000 | 4 | 4 | 6 | 1 |
ecs.sgn7i-vws-m8s.4xlarge | 16 | 32 | NVIDIA A10 * 1/3 | 24GB * 1/3 | 5/20 | 2,000,000 | 8 | 4 | 10 | 1 |
The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:
NVIDIA A10 * 1/12. NVIDIA A10 is the GPU model. 1/12 indicates that a GPU is sliced into 12 GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.
vgn7i-vws, vGPU-accelerated instance family
Introduction:
This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data storage and model loading can be performed more quickly.
This instance family comes with an NVIDIA GRID vWS license and provides certified graphics acceleration capabilities for CAD software to meet the requirements of professional graphic design. Instances of this instance family can serve as lightweight GPU-accelerated compute-optimized instances to reduce the costs of small-scale AI inference tasks.
Supported scenarios:
Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification
Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming
3D modeling in fields that require the use of Ice Lake processors, such as animation and film production, cloud gaming, and mechanical design
Compute:
Uses NVIDIA A10 GPUs that have the following features:
Innovative NVIDIA Ampere architecture
Support for acceleration features, such as vGPU, RTX, and TensorRT, to provide diversified business support
Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.vgn7i-vws-m4.xlarge | 4 | 30 | NVIDIA A10 * 1/6 | 24GB * 1/6 | 3 | 1,000,000 | 4 | 4 | 10 | 1 |
ecs.vgn7i-vws-m8.2xlarge | 10 | 62 | NVIDIA A10 * 1/3 | 24GB * 1/3 | 5 | 2,000,000 | 8 | 6 | 10 | 1 |
ecs.vgn7i-vws-m12.3xlarge | 14 | 93 | NVIDIA A10 * 1/2 | 24GB * 1/2 | 8 | 3,000,000 | 8 | 6 | 15 | 1 |
ecs.vgn7i-vws-m24.7xlarge | 30 | 186 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 6,000,000 | 12 | 8 | 30 | 1 |
The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:
NVIDIA A10 * 1/6. NVIDIA A10 is the GPU model. 1/6 indicates that a GPU is sliced into six GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.
vgn6i-vws, vGPU-accelerated instance family
In light of the NVIDIA GRID driver upgrade, Alibaba Cloud upgrades the vgn6i instance family to the vgn6i-vws instance family. The vgn6i-vws instance family uses the latest NVIDIA GRID driver and provides an NVIDIA GRID vWS license. To apply for free images for which the NVIDIA GRID driver is pre-installed, submit a ticket.
To use other public images or custom images that do not contain an NVIDIA GRID driver, submit a ticket to apply for the GRID driver file and install the NVIDIA GRID driver. Alibaba Cloud does not charge additional license fees for the GRID driver.
Supported scenarios:
Real-time rendering for cloud gaming
Real-time rendering for Augmented Reality (AR) and Virtual Reality (VR) applications
AI (deep learning and machine learning) inference for elastic Internet service deployment
Educational environment of deep learning
Modeling experiment environment of deep learning
Compute:
Uses NVIDIA T4 GPUs.
Uses vGPUs.
Supports the 1/4 and 1/2 compute capacity of NVIDIA Tesla T4 GPUs.
Supports 4 GB and 8 GB of GPU memory.
Offers a CPU-to-memory ratio of 1:5.
Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports standard SSDs and ultra disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.vgn6i-m4-vws.xlarge | 4 | 23 | NVIDIA T4 * 1/4 | 16GB * 1/4 | 2 | 500,000 | 4/2 | 3 | 10 | 1 |
ecs.vgn6i-m8-vws.2xlarge | 10 | 46 | NVIDIA T4 * 1/2 | 16GB * 1/2 | 4 | 800,000 | 8/2 | 4 | 10 | 1 |
ecs.vgn6i-m16-vws.5xlarge | 20 | 92 | NVIDIA T4 * 1 | 16GB * 1 | 7.5 | 1,200,000 | 6 | 4 | 10 | 1 |
The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:
NVIDIA T4 * 1/4. NVIDIA T4 is the GPU model. 1/4 indicates that a GPU is sliced into four GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.
gn8is, GPU-accelerated compute-optimized instance family
This instance family is available only in specific regions, including regions outside China. To use the instance family, contact Alibaba Cloud sales personnel.
Introduction: This instance family is an 8th-generation GPU-accelerated compute-optimized instance family provided by Alibaba Cloud in response to the recent development of AI-generated business. This instance family consists of multiple instance types that provide 1, 2, 4, or 8 GPUs per instance and have different CPU-to-GPU ratios to fit various use cases.
Benefits and positioning:
Graphic processing: This instance family uses high-frequency 5th-generation Intel Xeon Scalable processors to provide sufficient CPU capacity for smooth graphics rendering and design in 3D modeling scenarios.
Inference tasks: This instance family uses innovative GPUs, each with 48 GB of memory, which accelerate inference tasks and support the FP8 floating-point format. You can use this instance family together with Container Service for Kubernetes (ACK) to support the inference of various AI-generated content (AIGC) models and accommodate inference tasks for 70B or larger large language models (LLMs).
Supported scenarios:
Animation, special effects for film and television, and rendering
Generation of AIGC images and inference of LLMs
Other general-purpose AI recognition, image recognition, and speech recognition scenarios
Compute:
Uses innovative GPUs that have the following features:
Support for acceleration features, such as TensorRT, and the FP8 floating-point format to improve LLM inference performance.
Up to 48 GB of memory per GPU and support for the inference of 70B or larger LLMs on a single instance with multiple GPUs.
Improved graphic processing capabilities. For example, after you install a GRID driver on a gn8is instance by using Cloud Assistant or an Alibaba Cloud Marketplace image, the instance can provide graphic processing performance twice that of a 7th-generation instance.
Uses the latest high-frequency Intel® Xeon® processors that deliver an all-core turbo frequency of 3.9 GHz to meet complex 3D modeling requirements.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs, ESSD AutoPL disks, and elastic ephemeral disks (EEDs).
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Supports Elastic RDMA interfaces (ERIs).
NoteFor information about how to use ERIs, see Configure eRDMA on an enterprise-level instance.
Instance types
Instance type | vCPU | Memory (GiB) | GPU memory | Network baseline bandwidth (Gbit/s) | ENIs | NIC queues per primary ENI | Private IPv4 addresses per ENI | IPv6 addresses per ENI | Maximum disks | Disk baseline IOPS | Disk baseline bandwidth (Gbit/s) |
ecs.gn8is.2xlarge | 8 | 64 | 48GB * 1 | 8 | 4 | 8 | 15 | 15 | 17 | 60,000 | 0.75 |
ecs.gn8is.4xlarge | 16 | 128 | 48GB * 1 | 16 | 8 | 16 | 30 | 30 | 17 | 120,000 | 1.25 |
ecs.gn8is-2x.8xlarge | 32 | 256 | 48GB * 2 | 32 | 8 | 32 | 30 | 30 | 33 | 250,000 | 2 |
ecs.gn8is-4x.16xlarge | 64 | 512 | 48GB * 4 | 64 | 8 | 64 | 30 | 30 | 33 | 450,000 | 4 |
ecs.gn8is-8x.32xlarge | 128 | 1024 | 48GB * 8 | 100 | 15 | 64 | 50 | 50 | 65 | 900,000 | 8 |
gn7e, GPU-accelerated compute-optimized instance family
Features:
Introduction:
This instance family allows you to select instance types that provide different numbers of GPUs and CPUs to meet your business requirements in AI use cases.
This instance family uses the third-generation SHENLONG architecture and doubles the average bandwidths of virtual private clouds (VPCs), networks, and disks compared with instance families of the previous generation.
Supported scenarios:
Small- and medium-scale AI training
High-performance computing (HPC) business accelerated by using Compute Unified Device Architecture (CUDA)
AI inference tasks that require high GPU processing capabilities or large amounts of GPU memory
Deep learning applications, such as training applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
Scientific computing applications that require robust GPU computing capabilities, such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics
ImportantWhen you use AI training services that feature a high communication load, such as transformer models, you must enable NVLink for GPU-to-GPU communication. Otherwise, data may be damaged due to unpredictable failures that are caused by large-scale data transmission over Peripheral Component Interconnect Express (PCIe) links. If you do not understand the topology of the communication links that are used for AI training services, submit a ticket to obtain technical support.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.gn7e-c16g1.4xlarge | 16 | 125 | 80GB * 1 | 8 | 3,000,000 | 8 | 8 | 10 | 1 |
ecs.gn7e-c16g1.8xlarge | 32 | 250 | 80GB * 2 | 16 | 6,000,000 | 16 | 8 | 10 | 1 |
ecs.gn7e-c16g1.16xlarge | 64 | 500 | 80GB * 4 | 32 | 12,000,000 | 32 | 8 | 10 | 1 |
ecs.gn7e-c16g1.32xlarge | 128 | 1000 | 80GB * 8 | 64 | 24,000,000 | 32 | 16 | 15 | 1 |
gn7i, GPU-accelerated compute-optimized instance family
Introduction: This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips to improve storage performance, network performance, and computing stability by an order of magnitude.
Supported scenarios:
Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification
Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming
Compute:
Uses NVIDIA A10 GPUs that have the following features:
Innovative NVIDIA Ampere architecture
Support for acceleration features, such as RTX and TensorRT
Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
Provides up to 752 GiB of memory, which is much larger than the memory sizes of the gn6i instance family.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.gn7i-c8g1.2xlarge | 8 | 30 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 1,600,000 | 8 | 4 | 15 | 15 |
ecs.gn7i-c16g1.4xlarge | 16 | 60 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 3,000,000 | 8 | 8 | 30 | 30 |
ecs.gn7i-c32g1.8xlarge | 32 | 188 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 6,000,000 | 12 | 8 | 30 | 30 |
ecs.gn7i-c32g1.16xlarge | 64 | 376 | NVIDIA A10 * 2 | 24GB * 2 | 32 | 12,000,000 | 16 | 15 | 30 | 30 |
ecs.gn7i-c32g1.32xlarge | 128 | 752 | NVIDIA A10 * 4 | 24GB * 4 | 64 | 24,000,000 | 32 | 15 | 30 | 30 |
ecs.gn7i-c48g1.12xlarge | 48 | 310 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 9,000,000 | 16 | 8 | 30 | 30 |
ecs.gn7i-c56g1.14xlarge | 56 | 346 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 12,000,000 | 16 | 12 | 30 | 30 |
ecs.gn7i-2x.8xlarge | 32 | 128 | NVIDIA A10 * 2 | 24GB * 2 | 16 | 6,000,000 | 16 | 8 | 30 | 30 |
ecs.gn7i-4x.8xlarge | 32 | 128 | NVIDIA A10 * 4 | 24GB * 4 | 16 | 6,000,000 | 16 | 8 | 30 | 30 |
ecs.gn7i-4x.16xlarge | 64 | 256 | NVIDIA A10 * 4 | 24GB * 4 | 32 | 12,000,000 | 32 | 8 | 30 | 30 |
ecs.gn7i-8x.32xlarge | 128 | 512 | NVIDIA A10 * 8 | 24GB * 8 | 64 | 24,000,000 | 32 | 16 | 30 | 30 |
ecs.gn7i-8x.16xlarge | 64 | 256 | NVIDIA A10 * 8 | 24GB * 8 | 32 | 12,000,000 | 32 | 8 | 30 | 30 |
You can change the following instance types only to ecs.gn7i-c8g1.2xlarge or ecs.gn7i-c16g1.4xlarge: ecs.gn7i-2x.8xlarge, ecs.gn7i-4x.8xlarge, ecs.gn7i-4x.16xlarge, ecs.gn7i-8x.32xlarge, and ecs.gn7i-8x.16xlarge.
gn7s, GPU-accelerated compute-optimized instance family
To use the gn7s instance family, submit a ticket.
Introduction:
This instance family uses the latest Intel Ice Lake processors and NVIDIA A30 GPUs that are based on NVIDIA Ampere architecture. You can select instance types that comprise appropriate mixes of GPUs and vCPUs to meet your business requirements in AI scenarios.
This instance family uses the third-generation SHENLONG architecture and doubles the average bandwidths of VPCs, networks, and disks compared with instance families of the previous generation.
Supported scenarios: concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification.
Compute:
Uses NVIDIA A30 GPUs that have the following features:
Innovative NVIDIA Ampere architecture
Support for the multi-instance GPU (MIG) feature and acceleration features (based on second-generation Tensor cores) to provide diversified business support
Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
Improves memory sizes significantly from instance families of the previous generation.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | Private IPv4 addresses per ENI | IPv6 addresses per ENI | NIC queues | ENIs |
ecs.gn7s-c8g1.2xlarge | 8 | 60 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 5 | 1 | 12 | 8 |
ecs.gn7s-c16g1.4xlarge | 16 | 120 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 5 | 1 | 12 | 8 |
ecs.gn7s-c32g1.8xlarge | 32 | 250 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 5 | 1 | 12 | 8 |
ecs.gn7s-c32g1.16xlarge | 64 | 500 | NVIDIA A30 * 2 | 24GB * 2 | 32 | 12,000,000 | 5 | 1 | 16 | 15 |
ecs.gn7s-c32g1.32xlarge | 128 | 1000 | NVIDIA A30 * 4 | 24GB * 4 | 64 | 24,000,000 | 10 | 1 | 32 | 15 |
ecs.gn7s-c48g1.12xlarge | 48 | 380 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 8 | 1 | 12 | 8 |
ecs.gn7s-c56g1.14xlarge | 56 | 440 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 8 | 1 | 12 | 8 |
gn7, GPU-accelerated compute-optimized instance family
Supported scenarios:
Deep learning applications, such as training applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
Scientific computing applications that require robust GPU computing capabilities, such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.gn7-c12g1.3xlarge | 12 | 94 | 40GB * 1 | 4 | 2,500,000 | 4 | 8 | 10 | 1 |
ecs.gn7-c13g1.13xlarge | 52 | 378 | 40GB * 4 | 16 | 9,000,000 | 16 | 8 | 30 | 30 |
ecs.gn7-c13g1.26xlarge | 104 | 756 | 40GB * 8 | 30 | 18,000,000 | 16 | 15 | 10 | 1 |
gn6i, GPU-accelerated compute-optimized instance family
Supported scenarios:
AI (deep learning and machine learning) inference for computer vision, speech recognition, speech synthesis, natural language processing (NLP), machine translation, and recommendation systems
Real-time rendering for cloud gaming
Real-time rendering for AR and VR applications
Graphics workstations or graphics-heavy computing
GPU-accelerated databases
High-performance computing
Compute:
Uses NVIDIA T4 GPUs that have the following features:
Innovative NVIDIA Turing architecture
16 GB of memory (320 GB/s bandwidth) per GPU
2,560 CUDA cores per GPU
Up to 320 Turing Tensor cores per GPU
Mixed-precision Tensor cores that support 65 FP16 TFLOPS, 130 INT8 TOPS, and 260 INT4 TOPS
Offers a CPU-to-memory ratio of 1:4.
Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs, ESSD AutoPL disks, standard SSDs, and ultra disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | Disk baseline IOPS | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.gn6i-c4g1.xlarge | 4 | 15 | NVIDIA T4 * 1 | 16GB * 1 | 4 | 500,000 | None | 2 | 2 | 10 | 1 |
ecs.gn6i-c8g1.2xlarge | 8 | 31 | NVIDIA T4 * 1 | 16GB * 1 | 5 | 800,000 | None | 2 | 2 | 10 | 1 |
ecs.gn6i-c16g1.4xlarge | 16 | 62 | NVIDIA T4 * 1 | 16GB * 1 | 6 | 1,000,000 | None | 4 | 3 | 10 | 1 |
ecs.gn6i-c24g1.6xlarge | 24 | 93 | NVIDIA T4 * 1 | 16GB * 1 | 7.5 | 1,200,000 | None | 6 | 4 | 10 | 1 |
ecs.gn6i-c40g1.10xlarge | 40 | 155 | NVIDIA T4 * 1 | 16GB * 1 | 10 | 1,600,000 | None | 16 | 10 | 10 | 1 |
ecs.gn6i-c24g1.12xlarge | 48 | 186 | NVIDIA T4 * 2 | 16GB * 2 | 15 | 2,400,000 | None | 12 | 6 | 10 | 1 |
ecs.gn6i-c24g1.24xlarge | 96 | 372 | NVIDIA T4 * 4 | 16GB * 4 | 30 | 4,800,000 | 250,000 | 24 | 8 | 10 | 1 |
gn6e, GPU-accelerated compute-optimized instance family
Supported scenarios:
Deep learning applications, such as training and inference applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
Scientific computing applications, such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics
Compute:
Uses NVIDIA V100 GPUs that each have 32 GB of GPU memory and support NVLink.
Uses NVIDIA V100 GPUs (SXM2-based) that have the following features:
Innovative NVIDIA Volta architecture.
32 GB of HBM2 memory (900 GB/s bandwidth) per GPU.
5,120 CUDA cores per GPU.
640 Tensor cores per GPU.
Support for up to six NVLink bidirectional connections per GPU. Each NVLink connection provides a bandwidth of 25 Gbit/s in each direction for a total bandwidth of 300 Gbit/s (6 × 25 × 2 = 300).
Offers a CPU-to-memory ratio of 1:8.
Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs, ESSD AutoPL disks, standard SSDs, and ultra disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.gn6e-c12g1.3xlarge | 12 | 92 | NVIDIA V100 * 1 | 32GB * 1 | 5 | 800,000 | 8 | 6 | 10 | 1 |
ecs.gn6e-c12g1.6xlarge | 24 | 182 | NVIDIA V100 * 2 | 32GB * 2 | 8 | 1,200,000 | 8 | 8 | 20 | 1 |
ecs.gn6e-c12g1.12xlarge | 48 | 368 | NVIDIA V100 * 4 | 32GB * 4 | 16 | 2,400,000 | 8 | 8 | 20 | 1 |
ecs.gn6e-c12g1.24xlarge | 96 | 736 | NVIDIA V100 * 8 | 32GB * 8 | 32 | 4,800,000 | 16 | 8 | 20 | 1 |
gn6v, GPU-accelerated compute-optimized instance family
Supported scenarios:
Deep learning applications, such as training and inference applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
Scientific computing applications, such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics
Compute:
Uses NVIDIA V100 GPUs.
Uses NVIDIA V100 GPUs (SXM2-based) that have the following features:
Innovative NVIDIA Volta architecture.
16 GB of HBM2 memory (900 GB/s bandwidth) per GPU.
5,120 CUDA cores per GPU.
640 Tensor cores per GPU.
Support for up to six NVLink bidirectional connections per GPU. Each NVLink connection provides a bandwidth of 25 Gbit/s in each direction for a total bandwidth of 300 Gbit/s (6 × 25 × 2 = 300).
Offers a CPU-to-memory ratio of 1:4.
Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports ESSDs, ESSD AutoPL disks, standard SSDs, and ultra disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | Disk baseline IOPS | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.gn6v-c8g1.2xlarge | 8 | 32 | NVIDIA V100 * 1 | 16GB * 1 | 2.5 | 800,000 | None | 4 | 4 | 10 | 1 |
ecs.gn6v-c8g1.4xlarge | 16 | 64 | NVIDIA V100 * 2 | 16GB * 2 | 5 | 1,000,000 | None | 4 | 8 | 20 | 1 |
ecs.gn6v-c8g1.8xlarge | 32 | 128 | NVIDIA V100 * 4 | 16GB * 4 | 10 | 2,000,000 | None | 8 | 8 | 20 | 1 |
ecs.gn6v-c8g1.16xlarge | 64 | 256 | NVIDIA V100 * 8 | 16GB * 8 | 20 | 2,500,000 | None | 16 | 8 | 20 | 1 |
ecs.gn6v-c10g1.20xlarge | 82 | 336 | NVIDIA V100 * 8 | 16GB * 8 | 32 | 4,500,000 | 250,000 | 16 | 8 | 20 | 1 |
gn5, GPU-accelerated compute-optimized instance family
Supported scenarios:
Deep learning
Scientific computing applications, such as computational fluid dynamics, computational finance, genomics, and environmental analytics
Server-side GPU compute workloads, such as high-performance computing, rendering, and multi-media encoding and decoding
Compute:
Uses NVIDIA P100 GPUs.
Offers multiple CPU-to-memory ratios.
Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.
Storage:
Supports high-performance local Non-Volatile Memory Express (NVMe) SSDs.
Is an instance family in which all instances are I/O optimized.
Supports standard SSDs and ultra disks.
Network:
Supports only IPv4.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | Local storage (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI |
ecs.gn5-c4g1.xlarge | 4 | 30 | 440 | NVIDIA P100 * 1 | 16GB * 1 | 3 | 300,000 | 1 | 3 | 10 |
ecs.gn5-c8g1.2xlarge | 8 | 60 | 440 | NVIDIA P100 * 1 | 16GB * 1 | 3 | 400,000 | 1 | 4 | 10 |
ecs.gn5-c4g1.2xlarge | 8 | 60 | 880 | NVIDIA P100 * 2 | 16GB * 2 | 5 | 1,000,000 | 2 | 4 | 10 |
ecs.gn5-c8g1.4xlarge | 16 | 120 | 880 | NVIDIA P100 * 2 | 16GB * 2 | 5 | 1,000,000 | 4 | 8 | 20 |
ecs.gn5-c28g1.7xlarge | 28 | 112 | 440 | NVIDIA P100 * 1 | 16GB * 1 | 5 | 1,000,000 | 8 | 8 | 20 |
ecs.gn5-c8g1.8xlarge | 32 | 240 | 1760 | NVIDIA P100 * 4 | 16GB * 4 | 10 | 2,000,000 | 8 | 8 | 20 |
ecs.gn5-c28g1.14xlarge | 56 | 224 | 880 | NVIDIA P100 * 2 | 16GB * 2 | 10 | 2,000,000 | 14 | 8 | 20 |
ecs.gn5-c8g1.14xlarge | 54 | 480 | 3520 | NVIDIA P100 * 8 | 16GB * 8 | 25 | 4,000,000 | 14 | 8 | 20 |
gn5i, GPU-accelerated compute-optimized instance family
Supported scenarios: server-side GPU compute workloads, such as deep learning inference and multi-media encoding and decoding.
Compute:
Uses NVIDIA P4 GPUs.
Offers a CPU-to-memory ratio of 1:4.
Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports standard SSDs and ultra disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
Instance types
Instance type | vCPU | Memory (GiB) | GPU | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.gn5i-c2g1.large | 2 | 8 | NVIDIA P4 * 1 | 8GB * 1 | 1 | 100,000 | 2 | 2 | 6 | 1 |
ecs.gn5i-c4g1.xlarge | 4 | 16 | NVIDIA P4 * 1 | 8GB * 1 | 1.5 | 200,000 | 2 | 3 | 10 | 1 |
ecs.gn5i-c8g1.2xlarge | 8 | 32 | NVIDIA P4 * 1 | 8GB * 1 | 2 | 400,000 | 4 | 4 | 10 | 1 |
ecs.gn5i-c16g1.4xlarge | 16 | 64 | NVIDIA P4 * 1 | 8GB * 1 | 3 | 800,000 | 4 | 8 | 20 | 1 |
ecs.gn5i-c16g1.8xlarge | 32 | 128 | NVIDIA P4 * 2 | 8GB * 2 | 6 | 1,200,000 | 8 | 8 | 20 | 1 |
ecs.gn5i-c28g1.14xlarge | 56 | 224 | NVIDIA P4 * 2 | 8GB * 2 | 10 | 2,000,000 | 14 | 8 | 20 | 1 |