What Is the Best Cloud Provider for Stable Diffusion?

Find out which is the best cloud provider for Stable Diffusion AI image generation using pre-trained models or for training your own.
What Is the Best Cloud Provider for Stable Diffusion?

With AI image generation becoming increasingly popular, millions of users are looking for cost-efficient and reliable ways to run Stable Diffusion. While AI technology advanced rapidly in the last two years, its system requirements are still quite demanding. For this reason, many individuals, small businesses and startups are turning to cloud computing for their AI needs.

Because of its scalability and affordability, the cloud offers solutions that can help you use Stable Diffusion and its many functions without having to invest in costly hardware solutions. But with so many options available, a list of cloud service providers can help you choose the right one for your needs and your budget.

In this article, we’ll explore the various cloud providers and provide tips on how to select the best one for Stable Diffusion. Whether you're looking to use pre-trained models or train your own one, these solutions will help you achieve the best AI image you can imagine.

Table of Contents

  1. Stable Diffusion System Requirements
  2. How to Pick a Cloud Provider for Stable Diffusion
  3. Best Cloud Providers for Running Stable Diffusion
  4. Google Colab Pro
  5. RunPod
  6. Vast.ai
  7. RunDiffusion
  8. AWS

Stable Diffusion System Requirements

Stable Diffusion is continuously evolving and improving as its AI technology grows. That means that the system requirements for it are also constantly changing. Thanks to recent improvements such as "--medvram" and "--lowvram" arguments and "--xformers" for GPUs that don't support half-precision, Stable Diffusion has become more accessible to users.

Ultimately, to run Stable Diffusion locally, you’d need to have a GPU with at least 4GB of VRAM. If you want to generate large images fast, the recommended VRAM is 16 GB or more. These requirements mean that you need to have a GPU on par with NVIDIA's RTX 3090, which starts at a whopping $1499. Otherwise, you will need to find a secure cloud hosting provider to ensure everything works seamlessly. 

If you don't have the budget or space for a dedicated machine to run Stable Diffusion, the cloud is an attractive option. It offers the same benefits as running Stable Diffusion on your own hardware with less of the overhead costs and risks.

Another viable solution is to rent a VPS hosting server, which can provide the necessary resources and flexibility for running Stable Diffusion effectively. This option allows you to scale your resources as needed without the upfront investment in high-end hardware, making it a practical choice for many users.

How to Pick a Cloud Provider for Stable Diffusion

Every cloud provider is different in terms of features and capabilities, so it’s important to research and understand which one will be best suited for your needs. Here are some considerations when choosing a cloud provider:

  • Pricing – Many providers offer discounts if you pay upfront or have more resources available than you need.
  • Security – Some providers offer extra security measures such as encrypting data at rest and ensuring that your information is properly stored and secured.
  • Hardware – Always check what hardware you'll get, as different providers can offer better GPUs than others.
  • Support – Some providers offer customer support for your AI projects. Having a knowledgeable team of engineers to turn to can be invaluable in getting the most out of Stable Diffusion and its features.
  • Availability – The best cloud provider will have servers available in multiple regions so that you can access your data vaults quickly anywhere.
  • Storage – Some cloud providers require you to purchase additional storage for storing models, LoRa, VAE, and other files.

In addition, you should also think about the types of services they offer such as GPU instances, machine learning frameworks, storage options and more.

Best Cloud Providers for Running Stable Diffusion

Let’s take a look at some of the best cloud providers perfect for setting up and using Stable Diffusion. We gathered various loud service providers  to compare their features and capabilities:

Google Colab Pro

google colab
  • Accessible from virtually any device
  • Convenient Google Drive mounting and great free storage
  • The Pro version offers more resources at an affordable price

Google Colaboratory - better known as "Colab" - is an online Jupyter notebook platform accessible through your web browser. Everyone with internet access can now explore machine learning and AI coding, even on a Chromebook or smartphone. Unlock the potential of this powerful resource to discover what you are capable of doing in just minutes.

Google Colab is one of the most popular cloud services when it comes to AI thanks to its accessibility and affordable pricing. You can use Colab for around 12 hours for free, depending on how much computing power you need. The free tier offers Nvidia K80 GPUs with ample VRAM to run even large, complex generations using Stable Diffusion.

The Pro version of the service offers more resources, like more powerful T4 and P100 GPUs and around 50 hours of usage, depending on how many credits you consume. Subscribing to Colab Pro costs $9.99 a month, but don't worry - after your Pro hours are up, you can keep using the service on the free tier until your next month.

Running Stable Diffusion on Colab offers the convenience of Google Drive and a hassle-free setup with notebooks like TheLastBen's AUTOMATIC1111 notebook and the Kohya Trainer for creating your own models. As long as you have enough Drive storage, you can keep your models, extensions, and embeddings in the cloud and use them in your notebooks with ease.

One possible drawback of Google Colab is speed. While it's more than enough for most users, if you need to run generations with higher-resolution models, then the speed may not be up to par. However, if you're looking for a cheap and easy way to get started with Stable Diffusion, Google Colab and its Pro tier is an ideal choice.


  • Fast GPU speeds with a range of options from Nvidia A4000 to RTX 4090
  • Pay-as-you-go usage with affordable pricing
  • Excellent customer support with helpful tutorials for easy setup

RunPod offers some of the fastest GPU speeds on any cloud service, with options ranging from Nvidia A4000 to RTX 3090 and even RTX 4090. Its pricing scheme is credit-based, which allows you pay-as-you-go usage on a per-hour basis. Many AI-art enthusiasts praise RunPod for its powerful hardware and affordable pricing, with the option to upscale your setup if needed.

RunPod's setup process is simple - all you have to do is choose a template and upload any desired customizations to your pod. RunPod is also praised for its excellent customer support and helpful tutorials that make it easy to get up and running with Stable Diffusion. The company's customer support team is knowledgeable and helpful, making it easy to get help when needed.

RunPod's biggest downside is that it requires some technical knowledge in order to set up your environment properly. You'll need some knowledge to pull models from Google Drive and other cloud storage. On top of this, you'll have to pay $0.1/GB/month for all storage on your running pods and $0.2/GB/month for volume storage on stopped pods.

runpod unavailable

If you plan on utilizing the same pod for an extended period of time, you might experience certain limitations, too. If your designated GPU becomes unavailable because of high demand or errors from RunPod itself, you'll have to opt for different hardware, which means starting a new pod from scratch. Consequently, this could lead you to use more credits on more pricey GPU options, or sacrifice resources and settle for a less powerful GPU.

However, this shouldn't deter you from considering RunPod – if you need high-end hardware and are willing to pay for it, then Runpod is an ideal choice for using Stable Diffusion.


  • Low-cost cloud GPU rental service offering a wide range of powerful Nvidia GPUs
  • User-friendly interface to manage instances and upload model checkpoints
  • Constantly updated list of available GPUs to access the most advanced hardware

Running resource-intensive tasks such as machine learning and deep learning models requires a lot of computing power. However, not everyone has the luxury of owning high-end GPUs for their computing needs. This is where cloud GPU rental services come in handy. Among the many players in the market, Vast.ai has established itself as the leader in low-cost cloud GPU rental services.

Vast.ai offers a wide range of GPU types and sizes, including powerful Nvidia RTX 3090 and 4090 GPUs. The list of GPUs available for rental is constantly updated with the latest models, ensuring that users have access to the most advanced hardware at an affordable price.

Vast.ai's platform is designed to be user-friendly, providing a straightforward and intuitive interface for users to book and manage their instances easily. Unlike some other services, this doesn't sacrifice the ability to upload your own model checkpoints. All you have to do is use the recommended template, open Jupyter, and then upload your desired .ckpt file.

Users have brought up that Vast.ai is slightly on the costly side, as the cost increases significantly when you opt for higher-end GPUs. However, the availability, convenience and customer service more than make up for those extra bucks if you're looking to use Stable Diffusion extensively.


  • Charges by the hour for on-demand GPU power
  • Wide range of hardware options from affordable to extremely powerful
  • ControlNet, InvokeAI and Automatic1111 are all included

If you're looking for a powerful service that charges by the hour as opposed to a subscription or credit model, then RunDiffusion is an ideal choice. RunDiffusion offers a wide selection of hardware, from affordable GPUs with 8GB VRAM all the way to extremely powerful 24 GB VRAM options, all at an affordable price point.

RunDiffusion also offers ControlNet, an unparalleled and remarkable tool to take your AI generations to the next level. The service offers you comfort in knowing you have somewhere dependable where Automatic1111 or InvokeAI will effortlessly boot up with no issues, ControlNet included.

A possible drawback with RunDiffusion is that some find it slightly more expensive than other services, but the convenience and reliability makes up for the additional cost. Additionally, users may experience a slight lack of information and tutorials compared to other similar services.

Overall, RunDiffusion offers an excellent service for those who need reliable hardware on demand or want to use Stable Diffusion for their AI projects. The service's reasonable pricing and ControlNet make it an appealing option for any user looking for powerful GPUs at an affordable price point.


  • Advanced solution for high-demand users
  • Powerful GPUs
  • Access to the Libraire.ai library

Amazon Web Services (AWS) is the largest cloud-computing platform in the world, and for good reason — it's highly reliable, fast, and secure. For those looking to use Stable Diffusion on AWS, it's worth noting that you'll need some experience in setting up your own cloud instances.

However, once you're comfortable with the process, AWS offers a wide range of GPU options to choose from. NI SP offers support for Nvidia T4 GPUs with 16 GB of VRAM (g4dn family) and the more powerful A10 GPUs with 24 GB (g5 family) to power your Stable Diffusion generations.

This AWS setup also gives you access to the huge prompt and image library of Libraire.ai to get ideas for your own prompts and create new impressive images. This is perfect for both beginners who want to try out Stable Diffusion, and experienced users who know exactly what they want to get out of AI images.

Something to note regarding this AWS setup is that it's slightly costlier than other options, and you may not get the customer service assistance you need right away. However, if you're an expert at setting up cloud-based instances, then this could be a suitable option for you.


Ultimately, choosing the best service to run Stable Diffusion depends on your needs and budget. All of the incredible providers we reviewed today offer powerful GPUs with exceptional performance at an affordable price point; each option is ideal for different types of users.

Whichever platform you decide to use for your Stable Diffusion projects, make sure it suits both your requirements and expectations. With careful selection, you can make the most out of these fantastic services and get the most out of AI generations.

With Stable Diffusion becoming more accessible than ever thanks to the cloud, you have a wide range of options for setting up and running your AI projects. With the pros and cons of each provider in mind, you can make an informed decision on which one is best suited for your needs.

Have fun creating amazing images with Stable Diffusion!

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