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features
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support

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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.

Description

In the past, tasks such as deep learning, 3D modeling, simulations, distributed analytics, and molecular modeling could take several days or even weeks to complete. Thanks to GPUonCLOUD’s specialized GPU servers, these processes can now be accomplished in just a few hours. You can choose from a range of pre-configured systems or ready-to-use instances equipped with GPUs that support popular deep learning frameworks like TensorFlow, PyTorch, MXNet, and TensorRT, along with libraries such as the real-time computer vision library OpenCV, all of which enhance your AI/ML model-building journey. Among the diverse selection of GPUs available, certain servers are particularly well-suited for graphics-intensive tasks and multiplayer accelerated gaming experiences. Furthermore, instant jumpstart frameworks significantly boost the speed and flexibility of the AI/ML environment while ensuring effective and efficient management of the entire lifecycle. This advancement not only streamlines workflows but also empowers users to innovate at an unprecedented pace.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

No images available

Screenshots View All

Integrations

MXNet No 
PyTorch No 
TensorFlow No 
Terraform Yes 

Integrations

MXNet Yes 
PyTorch Yes 
TensorFlow Yes 
Terraform 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 

Pricing Details

$1 per hour
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 No 
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 No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

GPU Compute

Founded

2026

Country

Estonia

Website

gpubank.io

Vendor Details

Company Name

GPUonCLOUD

Country

India

Website

gpuoncloud.com/gpu-as-a-service/

Product Features

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