Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Amazon EC2 P4d instances are designed for optimal performance in machine learning training and high-performance computing (HPC) applications within the cloud environment. Equipped with NVIDIA A100 Tensor Core GPUs, these instances provide exceptional throughput and low-latency networking capabilities, boasting 400 Gbps instance networking. P4d instances are remarkably cost-effective, offering up to a 60% reduction in expenses for training machine learning models, while also delivering an impressive 2.5 times better performance for deep learning tasks compared to the older P3 and P3dn models. They are deployed within expansive clusters known as Amazon EC2 UltraClusters, which allow for the seamless integration of high-performance computing, networking, and storage resources. This flexibility enables users to scale their operations from a handful to thousands of NVIDIA A100 GPUs depending on their specific project requirements. Researchers, data scientists, and developers can leverage P4d instances to train machine learning models for diverse applications, including natural language processing, object detection and classification, and recommendation systems, in addition to executing HPC tasks such as pharmaceutical discovery and other complex computations. These capabilities collectively empower teams to innovate and accelerate their projects with greater efficiency and effectiveness.

Description

GPUBank serves as a cloud-based platform where developers, machine-learning experts, and research groups can rent GPU resources to enhance their AI and GPU-intensive workloads. Users can easily navigate the web console to select either NVIDIA or AMD GPU instances, pick a deployment location, and initiate pre-configured setups for a variety of purposes, including model training, inference, fine-tuning, image generation, and framework development. The platform offers a range of templates, such as PyTorch, vLLM, ComfyUI, and Ollama, catering to diverse project needs. Additionally, GPUBank provides an API, a command-line interface, a Python SDK, and a Terraform provider to facilitate easy provisioning and management of usage. Pricing for GPU compute is calculated per second and encompasses the costs for the chosen instance's CPU, memory, local NVMe storage, public IPv4, and network traffic as part of the hourly rate; however, persistent disks incur additional charges. Customers have the flexibility to opt for on-demand, interruptible, or reserved capacity across various data center locations, ensuring they can tailor their resources to fit specific project requirements effectively. This versatility makes GPUBank an appealing choice for those looking to optimize their computational needs in a cost-effective manner.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

No images available

Integrations

AWS Batch Yes 
AWS Deep Learning AMIs Yes 
AWS Deep Learning Containers Yes 
AWS Neuron Yes 
AWS Nitro System Yes 
AWS Trainium Yes 
Amazon EC2 Yes 
Amazon EC2 Capacity Blocks for ML Yes 
Amazon EC2 G5 Instances Yes 
Amazon EC2 P5 Instances Yes 
Amazon EC2 Trn1 Instances Yes 
Amazon EC2 Trn2 Instances Yes 
Amazon EC2 UltraClusters Yes 
Amazon EKS Yes 
Amazon Elastic Container Service (Amazon ECS) Yes 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
MXNet Yes 
PyTorch Yes 
TensorFlow Yes 

Integrations

AWS Batch No 
AWS Deep Learning AMIs No 
AWS Deep Learning Containers No 
AWS Neuron No 
AWS Nitro System No 
AWS Trainium No 
Amazon EC2 No 
Amazon EC2 Capacity Blocks for ML No 
Amazon EC2 G5 Instances No 
Amazon EC2 P5 Instances No 
Amazon EC2 Trn1 Instances No 
Amazon EC2 Trn2 Instances No 
Amazon EC2 UltraClusters No 
Amazon EKS No 
Amazon Elastic Container Service (Amazon ECS) No 
Amazon SageMaker No 
Amazon Web Services (AWS) No 
MXNet No 
PyTorch No 
TensorFlow No 

Pricing Details

$11.57 per hour
Free Trial No 
Free Version No 

Pricing Details

$0.23/GPU/hour
On-demand RTX 4090 compute starts at $0.23 per GPU-hour, billed by the second with no minimum compute duration. Prices are in USD and exclude VAT. Customers add funds to a prepaid balance using cryptocurrency, with a $25 minimum top-up. Compute price includes vCPU, RAM, local NVMe, one public IPv4 address, and traffic. Persistent disk is $0.03 per GB-month. Interruptible and reserved rates are available at discounts from on-demand pricing.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/ec2/instance-types/p4/

Vendor Details

Company Name

GPU Compute

Founded

2026

Country

Estonia

Website

gpubank.io

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

HPC

Product Features

Alternatives

Alternatives

gpu.nz Reviews

gpu.nz

Transtrade
Nextify Reviews

Nextify

Nextify Now