We use essential cookies and similar tools that are necessary to provide our site and services. We use performance cookies to collect anonymous statistics, so we can understand how customers use our site and make improvements. Essential cookies cannot be deactivated, but you can choose “Customize” or “Decline” to decline performance cookies.
If you agree, AWS and approved third parties will also use cookies to provide useful site features, remember your preferences, and display relevant content, including relevant advertising. To accept or decline all non-essential cookies, choose “Accept” or “Decline.” To make more detailed choices, choose “Customize.”
Customize cookie preferences
We use cookies and similar tools (collectively, "cookies") for the following purposes.
Essential
Essential cookies are necessary to provide our site and services and cannot be deactivated. They are usually set in response to your actions on the site, such as setting your privacy preferences, signing in, or filling in forms.
Performance
Performance cookies provide anonymous statistics about how customers navigate our site so we can improve site experience and performance. Approved third parties may perform analytics on our behalf, but they cannot use the data for their own purposes.
Allowed
Functional
Functional cookies help us provide useful site features, remember your preferences, and display relevant content. Approved third parties may set these cookies to provide certain site features. If you do not allow these cookies, then some or all of these services may not function properly.
Allowed
Advertising
Advertising cookies may be set through our site by us or our advertising partners and help us deliver relevant marketing content. If you do not allow these cookies, you will experience less relevant advertising.
Allowed
Blocking some types of cookies may impact your experience of our sites. You may review and change your choices at any time by selecting Cookie preferences in the footer of this site. We and selected third-parties use cookies or similar technologies as specified in the AWS Cookie Notice.
Your privacy choices
We display ads relevant to your interests on AWS sites and on other properties, including cross-context behavioral advertising. Cross-context behavioral advertising uses data from one site or app to advertise to you on a different company’s site or app.
To not allow AWS cross-context behavioral advertising based on cookies or similar technologies, select “Don't allow” and “Save privacy choices” below, or visit an AWS site with a legally-recognized decline signal enabled, such as the Global Privacy Control. If you delete your cookies or visit this site from a different browser or device, you will need to make your selection again. For more information about cookies and how we use them, please read our AWS Cookie Notice.
Amazon EC2 G5 instances are the latest generation of NVIDIA GPU-based instances that can be used for a wide range of graphics-intensive and machine learning use cases. They deliver up to 3x better performance for graphics-intensive applications and machine learning inference and up to 3.3x higher performance for machine learning training compared to Amazon EC2 G4dn instances.
Customers can use G5 instances for graphics-intensive applications such as remote workstations, video rendering, and gaming to produce high fidelity graphics in real time. With G5 instances, machine learning customers get high performance and cost-efficient infrastructure to train and deploy larger and more sophisticated models for natural language processing, computer vision, and recommender engine use cases.
G5 instances feature up to 8 NVIDIA A10G Tensor Core GPUs and second generation AMD EPYC processors. They also support up to 192 vCPUs, up to 100 Gbps of network bandwidth, and up to 7.6 TB of local NVMe SSD storage.
Benefits
High performance for graphics-intensive applications
G5 instances deliver up to 3x higher graphics performance and up to 40% better price performance than G4dn instances. They have more ray tracing cores than any other GPU-based EC2 instance, feature 24 GB of memory per GPU, and support NVIDIA RTX technology. This makes them ideal for rendering realistic scenes faster, running powerful virtual workstations, and supporting graphics heavy applications at higher fidelity.
High performance and cost-efficiency for ML inference
G5 instances deliver up to 3x higher performance and up to 40% better price performance for machine learning inference compared to G4dn instances. They are a highly performant and cost-efficient solution for customers who want to use NVIDIA libraries such as TensorRT, CUDA, and cuDNN to run their ML applications.
Cost-efficient training for moderately complex ML models
G5 instances offer up to 15% lower cost-to-train than Amazon EC2 P3 instances. They also deliver up to 3.3x higher performance for ML training compared to G4dn instances. This makes them a cost-efficient solution for training moderately complex and single node machine learning models for natural language processing, computer vision, and recommender engine use cases.
Maximized resource efficiency
G5 instances are built on the AWS Nitro System, a combination of dedicated hardware and lightweight hypervisor which delivers practically all of the compute and memory resources of the host hardware to your instances for better overall performance and security. With G5 instances, the Nitro system provisions the GPUs in a pass-through mode, providing performance comparable to bare-metal.
Features
AWS NVIDIA A10G Tensor Core GPU
G5 instances are the first in the cloud to feature NVIDIA A10G Tensor Core GPUs that deliver high performance for graphics-intensive and machine learning applications. Each instance features up to 8 A10G Tensor Core GPUs that come with 80 ray tracing cores and 24 GB of memory per GPU. They also offer 320 third-generation NVIDIA Tensor Cores delivering up to 250 TOPS resulting in high performance for ML workloads.
NVIDIA drivers
G5 instances offer NVIDIA RTX Enterprise and gaming drivers to customers at no additional cost. NVIDIA RTX Enterprise drivers can be used to provide high quality virtual workstations for a wide range of graphics-intensive workloads. NVIDIA gaming drivers provide unparalleled graphics and compute support for game development. G5 instances also support CUDA, cuDNN, NVENC, TensorRT, cuBLAS, OpenCL, DirectX 11/12, Vulkan 1.1, and OpenGL 4.5 libraries.
High performance networking and storage
G5 instances come with up to 100 Gbps of networking throughput enabling them to support the low latency needs of machine learning inference and graphics-intensive applications. 24 GB of memory per GPU along with support for up to 7.6 TB of local NVMe SSD storage enable local storage of large models and datasets for high performance machine learning training and inference. G5 instances can also store large video files locally resulting in increased graphics performance and the ability to render larger and more complex video files.
Built on AWS Nitro System
G5 instances are built on the AWS Nitro System, which is a rich collection of building blocks that offloads many of the traditional virtualization functions to dedicated hardware and software to deliver high performance, high availability, and high security while also reducing virtualization overhead.
Product details
Instance Size
GPU
GPU Memory (GiB)
vCPUs
Memory (GiB)
Storage (GB)
Network Bandwidth (Gbps)
EBS Bandwidth (Gbps)
On Demand Price/hr*
1-yr ISP Effective Hourly (Linux)
3-yr ISP Effective Hourly (Linux)
Single GPU VMs
g5.xlarge
1
24
4
16
1x250
Up to 10
Up to 3.5
$1.006
$0.604
$0.402
g5.2xlarge
1
24
8
32
1x450
Up to 10
Up to 3.5
$1.212
$0.727
$0.485
g5.4xlarge
1
24
16
64
1x600
Up to 25
8
$1.624
$0.974
$0.650
g5.8xlarge
1
24
32
128
1x900
25
16
$2.448
$1.469
$0.979
g5.16xlarge
1
24
64
256
1x1900
25
16
$4.096
$2.458
$1.638
Multi GPU VMs
g5.12xlarge
4
96
48
192
1x3800
40
16
$5.672
$3.403
$2.269
g5.24xlarge
4
96
96
384
1x3800
50
19
$8.144
$4.886
$3.258
g5.48xlarge
8
192
192
768
2x3800
100
19
$16.288
$9.773
$6.515
* Prices shown are for US East (Northern Virginia) AWS Region. Prices for 1-year and 3-year reserved instances are for "Partial Upfront" payment options or "No Upfront" for instances without the Partial Upfront option.
Customer and Partner testimonials
Here are some examples of how customers and partners have achieved their business goals with Amazon EC2 G5 instances.
Athenascope
Athenascope uses cutting-edge developments in computer vision and artificial intelligence to analyze gameplay and automatically surface the most compelling gameplay moments to create highlight videos for gamers and content creators.
To create a seamless video experience, low latency video analysis using our CV models is a foundational goal for us. Amazon EC2 G5 instances offer a 30% improvement in price/performance over previous deployments with G4dn instances.
Chris Kirmse, CEO & Founder, Athenascope
Netflix
Netflix is one of the world's leading streaming entertainment services with 214 million paid memberships in over 190 countries enjoying TV series, documentaries, and feature films across a wide variety of genres and languages.
With the new Amazon EC2 G5 instances, we can provision higher-end graphics workstations that offer up to 3x higher performance compared to workstations with EC2 G4dn instances. With G5 instances, content creators have the freedom to create more complex and realistic content for our viewers.
Ben Tucker, Technical Lead, Animation Production Systems Engineering, Netflix
For high-end VR/XR applications, Amazon EC2 G5 instances are a game-changer. We’re able to run professional applications in Varjo’s signature human-eye resolution with three times the frame rate compared to G4dn instances used before, providing our customers with never-before-seen experience quality when streaming from server.
Urho Konttori, Founder and Chief Technology Officer, Varjo
Getting started with G5 instances
Using DLAMI or Deep Learning Containers
DLAMI provides ML practitioners and researchers with the infrastructure and tools to accelerate DL in the cloud, at any scale. Deep Learning Containers are Docker images preinstalled with DL frameworks to streamline the deployment of custom ML environments by letting you skip the complicated process of building and optimizing your environments from scratch.
Using Amazon EKS or Amazon ECS
If you prefer to manage your own containerized workloads through container orchestration services, you can deploy G5 instances with Amazon EKS or Amazon ECS.