Get Free Cloud GPUs — To Train Your AI Models

Introduction

When training large deep learning models, you often need a GPU (Graphics Processing Unit) known for its ability to handle complex mathematical computations efficiently and quickly. While GPUs were initially designed for the gaming industry, they have become essential in deep learning to significantly accelerate the training process of neural networks. However, GPUs are often expensive and not easily accessible. Fortunately, several platforms now offer cloud-based GPUs for free, allowing AI developers to leverage their power without the hefty price tag or even a credit card for sign-up.

In this article, I’ll explore the Top 5 platforms that provide free cloud GPUs, ideal for deep learning, machine learning, or AI projects. These platforms not only offer powerful GPU access but also make it easy for anyone, From beginners to experts—to get started without financial barriers.

Key Comparison Factors:

Before diving into the list, here are the factors we’ve considered in our rankings:

• GPU Model & Memory: The type of GPU and its memory capacity.
• GPU Access: How we access the gpu machine.
• Usage Limits: Are there any restrictions on usage?
• Runtime per Session: How long can your code run before timing out?
• Background Execution: The ability to run code in the background, even when the browser or notebook is closed.
• Notebook Privacy: Can you keep your notebooks private and secure?

Table of Contents:

Top 5 Platforms for Free Cloud GPU Access

1. Dataoorts GPU Cloud
2. Google Colab
3. Kaggle
4. Amazon Sagemaker
5. Lightning AI

Top 5 Free GPU Platforms for Deep Learning and AI Projects

1. Dataoorts GPU Cloud

1. Dataoorts GPU Cloud | AI Developer's Paradise

Dataoorts GPU Cloud is designed for AI developers seeking high-performance GPU resources without the hassle. No complex setups or lengthy sign-ups needed.

Dataoorts Cloud Is Build By AI Developers For Next Gen AI Developers!

Free GPU Models Available: Various models, including NVIDIA GH200, H100, A100, A40 and so on...

Get up to 22 hours of free compute, equivalent to $10 in credit.

Pros:

• No Complex Setup: Start using the service with minimal effort. No Card Required Prepaid services.
• GPU Instance Type: Lite Virtual Machine
• High-Performance GPUs: Access powerful GPUs optimized for AI tasks. X-Series and GC2 GPU Instances.
• Guaranteed 99.99% uptime: Instances are consistently available with DDRA Cluster.
• Supports Background Execution: Run/Train/Fine-Tune your AI models continuously without interruption.

Cons:

• Approval Needed: Accessing initial free credits may require a brief, one-time approval.

Visit Dataoorts GPU Cloud: https://dataoorts.com

2. Google Colaboratory (Google Colab) | Free GPU Access

Google Colaboratory, commonly known as Google Colab, is a product from Google Research that's incredibly popular in the Data Science and Deep Learning community. You only need a Google Account to get started.

Free GPU Models Available:

• Tesla K80 (subject to availability)
• Tesla T4 (16GB GPU memory)

Pros:

• Free Access to High-Performance GPUs: Easily access Tesla K80 or T4 without any setup.
• Seamless Integration with Google Drive: You get 15GB of free storage on Google Drive.
• 12-Hour Runtime per Session: Ideal for long experiments.
• Notebooks can be kept private for added security and collaboration.
• Easy Setup and Use: No complex installation required.

Cons:

• No Background Execution: Once you close your browser or disconnect, execution stops.
• Limited GPU Availability: Access to GPUs depends on availability, which may fluctuate.
• Lower GPU Performance: Compared to some other free platforms like SageMaker Studio Lab.

Paid Options:

Google Colab also offers premium subscriptions:

• Colab Pro and Colab Pro+ provide faster GPUs (like: P100, A100) and longer runtimes, making it ideal for larger, more complex deep learning models.

Visit Google Colab: https://colab.research.google.com

3. Kaggle | Free GPU for Data Science Competitions

Kaggle, owned by Google, is a data science competition platform that also offers free access to GPUs. With over 50,000 public datasets and 400,000 public notebooks, it's a treasure trove for data science enthusiasts and professionals alike.

Free GPU Models Available:

• Tesla P100 (16GB GPU memory)
• Dual Tesla T4 (15GB GPU memory each)

Pros:

• Free Persistent Storage (20GB): Ideal for storing your datasets and project files.
• Background Execution: You can let your code run even after closing the notebook.
• Public and Private Notebooks: Collaborate with teams or work solo while keeping your projects private.
• Access to Rich Datasets: Thousands of public datasets are available for quick experimentation.
• Ideal for Competitions: Great for practicing and competing in machine learning challenges.

Cons:

• Weekly Usage Limit: Limited to 33 hours of GPU use per week, which may restrict longer projects.
• No Upgrade for Higher GPUs: Free tier users are limited to the P100 and T4, without an option to pay for more resources.

Visit Kaggle Platform: https://kaggle.com

4. Amazon SageMaker Studio Lab | Free GPU Access

Recently launched by Amazon, SageMaker Studio Lab is a free alternative to AWS-powered services, and it comes without the need for an AWS account or a credit card.

Free GPU Model Available:

• Tesla T4 (16GB GPU memory)

Pros:

• No AWS Account or Credit Card Required: Simple signup using just your email address.
• Powerful GPU for Free: Offers access to one of the most powerful GPUs in the free-tier GPU platforms.
• 15GB Persistent Storage: Keep your files safe even after the session ends.
• Background Execution Supported: Allows you to run your models in the background.

Cons:

• Limited Runtime: Each session lasts 4 hours, and you’re capped at 8 hours of GPU use per day.
• Access Not Instantaneous: You need to request access and wait for Amazon's approval, which may take a few days.
• GPU Unavailability Issues: Since it's new, there might be occasional bottlenecks.

Visit AWS SageMaker: https://aws.amazon.com/pm/sagemaker

5. Lightning AI | Free GPU Access

Recently launched, Lightning AI offers an innovative alternative for those in need of powerful GPU resources. No need for lengthy sign-ups or credit card details to get started.

GPU Model Available: All users on Lightning get 1 Studio running free 24/7 and 22 GPU hours per month ($15 credits).

Pros:

• No Complex Setup: Get started with just an email address.
• High-Performance GPU: Access one of the most advanced GPUs available.
• Supports Background Execution: Allows continuous operation of your models.

Cons:

• Limited Session Time: Each session is capped at 6 hours.
• Access May Require Approval: Initial access might require approval, leading to potential delays.
• Availability Constraints: Due to high demand, there might be occasional delays in GPU availability.

Visit Lightning AI: https://lightning.ai

Bonus: Azure for Students, Free GPU Access for Students Only

If you’re a student, Microsoft Azure offers a free plan that includes $100 worth of credit, which can be used to access their powerful GPU resources. You don’t need a credit card, but you will need to verify your student status.

Free GPU Model Available:

• Tesla T4 (same as in Amazon SageMaker Studio Lab)

Pros:

• Free $100 Credit: This allows students to access a range of GPU resources.
• Background Execution: Like Kaggle, Azure allows background execution of notebooks.
• 50GB Persistent Storage: Much more storage compared to other free platforms.
• Private Notebooks Supported: Work in private without exposing your projects to the public.

Cons:

• Limited by Credits: Once the $100 credit is used up, you'll need to either pay for more or wait for new promotions.
• Monitoring for Promotions Required: Keep an eye on Azure offers for additional free credits.

Visit Microsoft Azure Cloud: https://azure.microsoft.com

Conclusion: Which Free GPU Platform Should You Choose?

If you’re looking for free GPU access for deep learning, each platform offers something different based on your needs:

• Dataoorts GPU Cloud best choice for AI/DL developers and engineers.
• Google Colab is ideal for beginners or those who are already part of the Google ecosystem.
• Kaggle is perfect for competition-driven learning with rich datasets.
• Amazon SageMaker Studio Lab offers the most powerful GPU (Tesla T4) but comes with usage restrictions.
• Lightning AI is perfect for ML projects if you prefer a local IDE-like experience.
• Microsoft Azure for Students is an excellent option if you're a student, offering powerful GPUs.

Choose the one that best fits your needs and workflow!

Thank you for reading. See you next time!