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What is GPUBank?

GPUBank operates as a cloud-based service that allows developers, machine-learning professionals, and research teams to lease GPU resources, thereby improving their AI and GPU-heavy tasks. The user-friendly web console enables users to choose between NVIDIA or AMD GPU instances, select a preferred deployment region, and launch pre-set configurations for diverse applications such as model training, inference, fine-tuning, image generation, and framework development. With an array of templates like PyTorch, vLLM, ComfyUI, and Ollama, GPUBank caters to varying project requirements effectively. Furthermore, the platform enhances usability by offering an API, a command-line interface, a Python SDK, and a Terraform provider to streamline resource management and provisioning. GPU compute pricing is billed by the second and includes charges for the CPU, memory, local NVMe storage, public IPv4, and network traffic associated with the selected instance's hourly rate, while additional fees apply for persistent disks. Users can choose from on-demand, interruptible, or reserved capacities across multiple data center locations, allowing them to customize their resource allocation based on specific project needs. This flexibility not only ensures efficiency but also positions GPUBank as an attractive solution for those aiming to manage their computational expenses strategically. As a result, it significantly enhances the overall productivity and effectiveness of various computational projects.

What is Amazon EC2 Capacity Blocks for ML?

Amazon EC2 Capacity Blocks are designed for machine learning, allowing users to secure accelerated compute instances within Amazon EC2 UltraClusters that are specifically optimized for their ML tasks. This service encompasses a variety of instance types, including P5en, P5e, P5, and P4d, which leverage NVIDIA's H200, H100, and A100 Tensor Core GPUs, along with Trn2 and Trn1 instances that utilize AWS Trainium. Users can reserve these instances for periods of up to six months, with flexible cluster sizes ranging from a single instance to as many as 64 instances, accommodating a maximum of 512 GPUs or 1,024 Trainium chips to meet a wide array of machine learning needs. Reservations can be conveniently made as much as eight weeks in advance. By employing Amazon EC2 UltraClusters, Capacity Blocks deliver a low-latency and high-throughput network, significantly improving the efficiency of distributed training processes. This setup ensures dependable access to superior computing resources, empowering you to plan your machine learning projects strategically, run experiments, develop prototypes, and manage anticipated surges in demand for machine learning applications. Ultimately, this service is crafted to enhance the machine learning workflow while promoting both scalability and performance, thereby allowing users to focus more on innovation and less on infrastructure. It stands as a pivotal tool for organizations looking to advance their machine learning initiatives effectively.

Media

No images available

Media

Integrations Supported

Terraform

Integrations Supported

AWS Neuron
AWS Nitro System
AWS Trainium
Amazon EC2
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
Greenovative
PyTorch
TensorFlow

API Availability

Has API

API Availability

Pricing Information

$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.

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

GPU Compute

Date Founded

2026

Company Location

Estonia

Company Website

gpubank.io

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/capacityblocks/

Categories and Features

Cloud GPU

Not specified

Categories and Features

AI Fine-Tuning

Not specified

AI Inference

Not specified

Cloud GPU

Not specified

Machine Learning

Not specified

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