How to Install & Use Stable Diffusion on Windows in 2024 (Easy Way)

AI Andy
7 Feb 202413:07

TLDRThe video script offers a step-by-step guide on installing and using Stable Diffusion for image generation through Comfy UI, an easier alternative to the traditional Python method. It covers downloading Comfy UI, installing Stable Diffusion models, using custom nodes to enhance functionality, and accessing high-quality models for ultimate control. The tutorial also introduces the use of TLD.DV for meeting summaries and emphasizes the importance of checking system requirements before proceeding.


  • 🚀 **Easy Installation**: The video outlines an easy method to install Stable Diffusion through Comfy UI, which is more accessible than using Python for users with low technical knowledge.
  • 🔍 **Google Search**: To find Comfy UI, simply search for it on Google and click the first link provided.
  • 📂 **File Management**: Extract the downloaded ZIP file and move the extracted folder to a suitable location, such as a new 'AI' folder in Documents for better organization.
  • 💻 **Hardware Requirements**: Check your GPU's VRAM capacity to ensure it meets the requirements (8 GB recommended). Instructions are provided for checking VRAM on Windows.
  • 🔗 **Downloading Models**: The script provides a step-by-step guide to download necessary models like Stable Diffusion XL base and refiner, with links in the description for easy access.
  • 📂 **Model Placement**: Explains where to place the downloaded models within the AI folder for Comfy UI to recognize and use them.
  • 🖌️ **Image Generation**: Details on how to generate images using the Stable Diffusion model through Comfy UI, including setting up prompts and parameters.
  • 🔄 **Custom Nodes**: Introduces the Comfy UI manager for installing custom nodes to enhance the functionality of Stable Diffusion, with a guide on how to install and use them.
  • 🔍 **Finding Custom Models**: Directs users to Civit AI for downloading high-quality custom models and testing them before installation to ensure desired output quality.
  • 🌐 **Sponsor Mention**: The video is sponsored by TLD.DV, an AI tool for summarizing meeting notes and generating reports, which can be integrated with platforms like Zoom, Google Meet, and Teams.
  • 🎥 **Video Content**: The video serves as a tutorial for installing and using Stable Diffusion for image generation, with a focus on simplifying the process for beginners.

Q & A

  • What are the two methods mentioned for installing and using Stable Diffusion?

    -The two methods mentioned are the hard way through Python, which requires more technical knowledge, and the easy way through Comfy UI, which is more user-friendly.

  • Why is Comfy UI recommended for installing Stable Diffusion?

    -Comfy UI is recommended because it simplifies the installation process, making it accessible to users with low technical knowledge. It eliminates the need to download through Python, which can be complex for non-technical users.

  • What is the first step in installing and using Stable Diffusion as per the video?

    -The first step is to install Comfy UI by searching for it on Google and downloading it from the provided link.

  • How large is the Comfy UI download file and what is the recommended action after downloading?

    -The Comfy UI download file is around 1.4 GB. After downloading, it should be extracted from the ZIP file and moved to a folder in the Documents named 'AI' for easier access in later steps.

  • What are the two run files to look out for in the extracted Comfy UI folder?

    -The two run files are 'run CPU' and 'run Nvidia GPU'. The appropriate one should be chosen based on the user's graphics card.

  • How can you check your GPU's VRAM?

    -To check your GPU's VRAM, press Windows + R, type 'dxdiag', click OK, click on 'Yes', and then click on 'Display' at the top. The information will be displayed, including the VRAM size.

  • What is the next step after installing Comfy UI?

    -The next step is to download the Stable Diffusion models, which include the stable diffusion XL base, the refiner, and the V file.

  • Where should the downloaded Stable Diffusion models be placed?

    -The downloaded models should be placed in the 'models' and 'checkpoints' folders within the Comfy UI directory.

  • How does one generate an image using the installed Stable Diffusion models?

    -To generate an image, run the 'Nvidia GPU' file again, open the interface in a web browser, load a checkpoint, and enter a prompt in the CLIP text encode prompt box. Adjust the settings and click 'Q prompt' to generate the image.

  • What is Comfy UI Manager and how does it enhance the Stable Diffusion experience?

    -Comfy UI Manager is a tool installed from GitHub that allows users to add custom nodes to the Comfy UI interface. These nodes can perform various functions, enhancing the capabilities of Stable Diffusion and allowing for more customization.

  • How can users find and test custom models before installing them?

    -Users can visit to find and test custom models. They can use the 'run model' feature to test a model without downloading it, which helps in determining the quality and suitability of the model before installation.



🖥️ Installing Comfy UI for Stable Diffusion

This paragraph introduces the process of installing Comfy UI, an easier alternative to the traditional Python installation for Stable Diffusion. It explains the steps to download Comfy UI, extract the ZIP file, and organize the files in a dedicated AI folder for easier access. The paragraph also highlights the importance of checking the system's VRAM capacity, especially for those with Nvidia graphics cards, and provides a link for Mac users. Additionally, it touches on the installation of necessary packages and the initial setup of the UI.


📦 Downloading Stable Diffusion Models

The second paragraph focuses on downloading the necessary Stable Diffusion models, including the Stable Diffusion XL base and refiner models. It provides instructions on where to find these files and the approximate file sizes, emphasizing the need for patience due to potentially long download times. The paragraph also mentions the additional 'sdxl V' model and the importance of placing the downloaded files in the correct folders within the AI directory. It concludes with a brief mention of generating images using the installed models.


🎨 Generating Images with Stable Diffusion

This paragraph delves into the actual image generation process using the installed Stable Diffusion models. It guides the user through the steps of loading checkpoints, setting up prompts, and configuring image parameters such as resolution and batch size. The paragraph explains the role of the K sampler in creating the image and the expected waiting time for the first image due to data fetching. It also provides examples of prompts and the resulting images, highlighting the differences in quality between the base model and refined models.

🔧 Customizing with Comfy UI Manager and Civit AI

The final paragraph discusses the customization of the Comfy UI experience through the installation of additional nodes and the use of Civit AI for downloading high-quality models. It explains how to access the Comfy UI manager on GitHub, install custom nodes, and utilize them in the image generation process. The paragraph also suggests testing models on Civit AI before downloading to ensure desired output quality. It concludes with a recommendation for a specific model and instructions on where to place downloaded models for future use.



💡Stable Diffusion

Stable Diffusion is a type of artificial intelligence model that generates images from textual descriptions. It is a core component of the video's content, as the tutorial focuses on installing and using this model to create images. The video provides a step-by-step guide on how to install Stable Diffusion models through Comfy UI, which simplifies the process for users with low technical knowledge.

💡Comfy UI

Comfy UI is a user-friendly interface designed to facilitate the use of Stable Diffusion models without the need for extensive technical skills. It is highlighted in the video as an easier alternative to the traditional Python installation method. The tutorial emphasizes the simplicity of using Comfy UI to download and operate the Stable Diffusion models.


Installation refers to the process of setting up and preparing software or applications for use. In the context of the video, it involves downloading and configuring Comfy UI and Stable Diffusion models. The video provides detailed instructions on how to install these components, making it a key concept for users to successfully follow the tutorial.

💡Custom Nodes

Custom Nodes are additional features or extensions that can be installed within Comfy UI to enhance the functionality and capabilities of the Stable Diffusion models. They allow users to perform more complex tasks and achieve better results in their image generation. The video introduces the concept of custom nodes and demonstrates how to install them to make Stable Diffusion more powerful.


Video RAM (VRAM) is the memory used to store图像 data for the graphics card. In the video, VRAM is an important consideration when running the Stable Diffusion models, as certain models require a significant amount of VRAM (like 8 GB) to operate effectively. The video instructs users on how to check their VRAM capacity to ensure compatibility with the software.


Checkpoints in the context of the video refer to the saved states or points in the training process of the Stable Diffusion models. These checkpoints are used to resume or continue the training process from where it left off, or to load pre-trained models for immediate use in generating images. The video guides users on where to place these checkpoint files for the Stable Diffusion models.


Prompts are the textual descriptions or inputs provided to the Stable Diffusion model to guide the generation of specific images. The video emphasizes the importance of crafting effective prompts to achieve desired outcomes. It also discusses the use of positive and negative prompts to refine the image generation process.

💡K Sampler

The K Sampler is a component of the Stable Diffusion process responsible for creating the image based on the prompts and other parameters set by the user. It is a critical part of the image generation workflow, and the video explains the recommended settings for the K Sampler to optimize image creation.

💡Image Generation

Image Generation is the process of creating visual content using AI models like Stable Diffusion. It involves inputting textual prompts and adjusting parameters to produce images that match the user's description. The video tutorial focuses on guiding users through this process using the Comfy UI and Stable Diffusion models.

💡Civit AI

Civit AI is a platform mentioned in the video where users can download custom models and access additional resources to enhance their Stable Diffusion experience. It serves as a repository for various models, allowing users to find and test different models before installing them for higher quality image generation.


The introduction of an easy method to install and use stable diffusion models through Comfy UI, which simplifies the process for users with low technical knowledge.

The comparison between the hard way (installing through Python) and the easy way (using Comfy UI) for installing stable diffusion, highlighting the benefits of the latter.

A step-by-step tutorial on how to install Comfy UI, including searching on Google and downloading the application.

The importance of checking the VRAM capacity of your GPU before proceeding with the installation, especially for those using an Nvidia graphics card.

The process of downloading and installing the stable diffusion models, including the stable diffusion XL base and refiner.

Instructions on where to place the downloaded models within the AI documents folder for Comfy UI to recognize and use them.

A demonstration of generating an image using Comfy UI, including setting up the positive and negative prompts and configuring the image parameters.

The explanation of the K sampler and its role in creating the image, along with recommended settings for optimal results.

The use of the Comfy UI manager to install custom nodes, which enhances the functionality and capabilities of stable diffusion.

A practical example of using a custom node for face swapping, showcasing the versatility of the installed nodes.

The recommendation to test custom models on Civit AI before downloading them to ensure they meet the desired quality standards.

The availability of high-quality models on Civit AI, which can be filtered by highest rated and most downloaded for users to find the best fit for their needs.

A guide on how to replace the base and refiner models with higher quality ones, such as the think diffusion XL model, for improved image generation.

The overall goal of the tutorial is to empower users to install and use stable diffusion models effectively, providing them with ultimate control over image generation.

The tutorial's aim to make complex AI tools accessible and straightforward for users, regardless of their technical expertise.