Cloud GPU Rental — Rent GPUs to Build & Train AI/ML models

Choose GPUs and system resources. Select software you use: Docker, Jupyter, Tensorflow, pyTorch, ubuntu or anything else.
You can now rent both GPU-powered Docker instances and full Virtual Private Servers (VPS). Our platform ensures access to high-performance AI GPU hosting.

We pride ourselves on offering competitive pricing for our GPU cloud services. Whether you are working on a small project or scaling up a massive AI workload, we have options to suit your budget:

GPU models

RTX A2000

6 GB

from 0.05$/hour

RTX 3060

12 GB

from 0.05$/hour

RTX A4000

16 GB

from 0.09$/hour

RTX 4060Ti

16 GB

from 0.09$/hour

RTX 4090

24 GB

from 0.30$/hour

RTX 5090

32 GB

from 0.45$/hour

RTX PRO 6000 blackwell

96 GB

from 1.50$/hour

Other models, contact us

With a pay-as-you-go model, you only pay for the time your GPU server is running. No hidden fees, no long-term commitments — just flexible GPU rental that grows with your needs.

Need a different GPU or big quantity? Just reach out to our support team!

Learn more about our GPUs

	VPS GPU (Early Access)	Docker GPU
Type of Virtualization	Full (just like server/PC)	Container with limited access
Ubuntu OS	Yes (full)	Yes (container with limited access to services)
Windows OS	Very soon
Ability to stop/start anytime		Data is lost except files in network storage
Persistent system drive		Deleted when rent has ended
Easy to switch between GPU models and GPU count
Additional persistent network storage	Soon
Dedicated Public IP address	Yes (all ports open)	No (only random forwarded ports)
Run any software		Limited (docker templates)
SSH access
Can run GUI apps (via RDP/VNC)
Docker inside Docker (nested Docker)
Faster startup time	Fast (with previous state)	Depends on template (usually slower)
Ideal for production workloads	Yes (in case of hardware failure you can run it on any other server)	No (in case of hardware failure, there is no backup)

Renting a Virtual Private Server GPU (VPS GPU) on SimplePod.ai is few clicks away - Just select the GPU type and quantity, one of predefined images, SSH key, disk size, click Run and enjoy your rented VPS GPU.

You need to install your tools and environment just like on a regular PC

Full operating system (Ubuntu, with Windows coming soon)

Start and stop server at any time - your drive is preserved!

When the server is stopped, you only pay for the disk

Change the GPU model or number of GPUs at any time

Public IP address with all ports open
(note: IP may change on each start — static IP support is coming)

Renting GPU instances on SimplePod.ai is quick and straightforward. Follow this video to get started with your Docker GPU rental.See written guide

Run pre-configured environments like Jupyter or PyTorch, and get straight to work.

Docker containers start instantly — no waiting for an entire OS to boot.

Use images with preinstalled frameworks like TensorFlow, PyTorch, and Jupyter.

Docker containers use fewer resources, giving more GPU power to your workloads.

Ideal for quick runs, testing, or one-off jobs that don’t need persistent storage.

Run anything that works in a container — from Jupyter notebooks to full AI pipelines.

Our platform is designed to make renting GPU servers as seamless and efficient as possible. Here is what you will get when you choose SimplePod.ai:

Find Instances section in the SimplePod dashboard, where you can purchase instances.

Browse Available Cloud GPU Servers

Our clean and intuitive interface allows you to browse through available GPUs quickly. Use advanced filters to select:

Desired GPU model.
Memory size.
System performance specifications.
Pricing options.

This ensures you find the ideal setup for your AI in cloud projects in seconds.

Form for creating a new image template, accessed from the My Instances section in the SimplePod dashboard.

Pre‑Configured System Software for AI/ML Environments on GPU Cloud

Get started quickly by choosing from a selection of pre-configured system software, ideal for various AI and development tasks:

TensorFlow: Ideal for training machine learning models.
PyTorch: A go-to tool for deep learning.
Stable-Diffusion: Ideal for generating high-quality images from text descriptions.
LLama: A powerful language model designed for natural language understanding and generation.
Ollama: Run large language models locally on your machine.
Koboldcpp: Efficiently operate AI language models using minimal system resources.

Pre‑Configured System Software for AI/ML Environments on GPU Cloud

Additional Tools and Features

Enhance your workflow with additional software options:

Ubuntu: A reliable and stable operating system.
Jupyter Notebook: Perfect for interactive coding and data visualization.
Text-to-Speech Tools: Convert written text into spoken words with ease.
A diverse range of other applications built on Docker, providing flexibility and adaptability.

With just a few clicks, you can deploy any of these environments to streamline your projects.

My Instances section in the SimplePod dashboard, where you can monitor your instances.

Monitor & Manage Your Cloud GPU Servers

Our platform provides all the tools you need to stay in control of your GPU cloud environment:

Execute batch commands directly through the interface.
Open integrated tabs for detailed instance monitoring.
Check real-time system usage, including memory and processing power, to optimize your resources.

Instance Details section in the SimplePod dashboard, where you can manage your server.

Manage Your Rented GPU Server

Control your rented GPU server effortlessly:

Access the web console for detailed configuration and management.
Stop or restart your instance anytime.
Keep track of active servers and resource consumption via the dashboard.

This flexibility ensures your GPU rental experience is smooth and adaptable.

Integrated Jupyter Notebook on GPU Cloud

For developers and data scientists, Jupyter Notebook is fully integrated into our platform. Here is how it simplifies your work:

Run and test machine learning code interactively.
Visualize data in real-time while working in your GPU cloud environment.
Combine code, text, and visuals in a single, user-friendly workspace.

Jupyter Notebook is perfect for streamlining your cloud AI workflows and boosting productivity.

Image of Persistence Volumes list and Persistence Volume section in Edit Template form the SimplePod dashboard

High-Speed Persistent Network Storage

Store your large models in one place with fast network storage delivering up to 25 Gb/s read/write performance:

Mount on one or multiple instances simultaneously
25 Gb/s high-speed read/write network storage
Access your storage even when instances are stopped

Image of Instances/Hosts details subpage in Simplepod dashboard showing chart with chart data tooltip on top

Graphical Stats of Your Cloud GPU Usage

Easily monitor how your resources are being used with real-time and historical statistics, including GPU utilization, VRAM, system memory, CPU, and disk activity:

Real-time usage charts
Tooltips with precise values at each point
Multiple chart timescales

New Cloud GPU Features Coming Soon

We are working hard on new features! Expect the most requested ones soon:

Ability to stop instance and not pay for GPUs
Backup and restore instance on any other GPUs

Missing a feature? Let us know!

Check all features

SimplePod makes GPU rentals easy. Whatever your needs, we provide the tools to harness cloud AI. Choose your GPU servers, set up your software, and launch projects in minutes. Join us today and discover how effortless AI in cloud can be.

Cloud GPU Rental — Rent GPUs to Build & Train AI/ML models

Flexible GPU Rental Pricing

Compare VPS GPU vs Docker GPU

How to Rent a Virtual Private Server GPU (VPS GPU)

Benefits of a VPS GPUs

Choose your OS

Start & Stop Anytime

Pay Only for Disk

Change GPU Anytime

Public IP Address

How to Rent a Docker GPU for Your AI/ML Projects

Benefits of Docker GPUs

Instant Start

Preinstalled Environments

Lightweight & Efficient

Perfect for Short Tasks

Flexible Software Options

Cloud GPU Computing Platform Features