Stable Diffusion 3 IS FINALLY HERE!

Sebastian Kamph
12 Jun 202416:08

TLDRStable Diffusion 3 (SD3) has been released, promising improved text prompt understanding and higher resolution capabilities. While it may not outperform its predecessors immediately, it offers a 16-channel VAE for finer detail retention and output. Suitable for most users with its 2B model, SD3 is expected to shine with community fine-tuning. It's a versatile upgrade, supporting various image sizes and offering better control for artists, with the potential to match or exceed the quality of previous models over time.


  • ๐ŸŽ‰ Stable Diffusion 3 (SD3) has been released and is ready for use.
  • ๐Ÿš€ Users can expect improved text prompt understanding and better control over image generation with SD3.
  • ๐Ÿ” SD3 features a 16-channel VAE, which allows for more detailed image output and training.
  • ๐ŸŒŸ The model is capable of generating high-resolution images, with a base resolution of 1024x1024 pixels.
  • ๐Ÿ’ป SD3 is designed to work well on a range of hardware, including less powerful GPUs, making it accessible to more users.
  • ๐Ÿ”ง While SD3 may not provide optimal results on the first day, it is expected to improve with community fine-tuning.
  • ๐Ÿ‘Œ SD3 is considered safe to use and does not require the more resource-intensive 8B model for most users.
  • ๐Ÿ“ˆ The model's performance is expected to outperform previous versions like 1.5 and SDXL, especially after community fine-tuning.
  • ๐Ÿ“š Research papers indicate that increasing the number of latent channels significantly boosts image quality and performance.
  • ๐Ÿ”— SD3 includes features like ControlNet and high-resolution support, which were previously only available in other models.
  • ๐Ÿ›  Users can download SD3 from Hugging Face and agree to terms to access files and example workflows.

Q & A

  • What is the main topic of the video transcript?

    -The main topic of the video transcript is the release of Stable Diffusion 3 (SD3), a new model for AI-generated art, and its features, improvements, and how to get started with it.

  • Is it recommended to start using SD3 from day one?

    -Yes, it is suggested to start using SD3 from day one, although it may need fine-tuning to provide better results initially.

  • What are the improvements in text prompt understanding in SD3 compared to previous models?

    -SD3 has improved text prompt understanding with a 16-channel VAE, which allows for better detail retention and output during training and generation of images.

  • Does SD3 come with any control net setup?

    -Yes, SD3 comes with a control net setup, which includes features like high-resolution image generation and high-quality fixes and upscales.

  • What is the resolution capability of SD3?

    -SD3 is a 1024x1024 pixel model, which can also work well with 512x512 images, making it versatile and less resource-intensive compared to previous models.

  • Is the SD3 model fine-tuned already?

    -No, the SD3 model is not fine-tuned yet, but the community is expected to contribute to its fine-tuning process.

  • What are the key architectural features that make SD3 stand out from other models?

    -SD3 stands out due to its use of a 16-channel VAE, improved text prompt understanding, and the ability to generate higher resolution images with more detail.

  • How does the increased number of latent channels in SD3 affect its performance?

    -Increasing the number of latent channels in SD3 significantly boosts its performance, as evidenced by lower FID scores and higher perceptual similarity, indicating better image quality.

  • What should users expect in terms of quality when using the 2B model of SD3 compared to the 8B model?

    -Users can expect the 2B model to be faster and require fewer resources than the 8B model. While the 8B model offers slightly higher quality in some areas, the 2B model is considered sufficient for most users' needs.

  • How can users get started with SD3 and where can they download it?

    -Users can get started with SD3 by downloading it from Hugging Face's stable AI page. They can choose between different versions, including one with or without the CLIP models, depending on their requirements.

  • What are the system requirements for running SD3?

    -SD3 can be run on most machines, with the 2B model being less resource-intensive than the 8B model. Users with powerful GPUs, like the 4090, can generate high-quality images, but the model is designed to be accessible to a wide range of users.



๐Ÿš€ Introduction to Stable Diffusion 3.0

This paragraph introduces the release of Stable Diffusion 3.0 (SD3), emphasizing its immediate usability and potential for superior results with some fine-tuning. It highlights the model's text prompt understanding and its capabilities in generating high-resolution images, including the comparison with the 8B model. The speaker asserts that SD3 is a medium-sized 2B model that will likely be the focus of most fine-tuning efforts due to its balance between quality and resource requirements. The paragraph also touches on the model's ability to generate text and images, its safety, and the expectation that the community will enhance its performance over time.


๐Ÿ” Deep Dive into SD3's Architectural Features

The second paragraph delves into the technical aspects of SD3, particularly the use of a 16-channel VAE compared to the previous 4-channel VAE, which allows for greater detail retention during training and image output. It discusses the model's resolution capabilities, being a 1024x1024 pixel model that can also work efficiently at 512x512, making it accessible for users with less powerful hardware. The paragraph references a research paper, indicating that increased latent channel capacity significantly improves image quality, and compares SD3's performance with other models like Mid Journey and Dolly 3, using examples from the paper to illustrate the differences.


๐Ÿ“ˆ Comparing SD3 with Other AI Models

This paragraph presents a comparative analysis of SD3 against other AI models like Mid Journey and Dolly, focusing on their ability to interpret and render complex prompts accurately. It discusses the results of generating images based on specific scenarios, such as a frog in a diner or a translucent pig containing a smaller pig, and evaluates the models' performance in terms of text accuracy, image realism, and adherence to the prompt. The speaker acknowledges the variability in results and the need for community fine-tuning to optimize SD3's capabilities.


๐Ÿ“˜ Getting Started with SD3 and Community Expectations

The final paragraph provides guidance on how to get started with SD3, including downloading the model and setting up the necessary components like the text encoders. It mentions the different options available for download and the importance of choosing the right model based on the user's system capabilities. The speaker also discusses the default settings for image generation and the potential for community-driven enhancements to improve SD3's performance. The paragraph concludes with an invitation for the audience to share their experiences and thoughts on SD3's initial performance.



๐Ÿ’กStable Diffusion 3

Stable Diffusion 3, often abbreviated as SD3, is the latest iteration of a text-to-image AI model that has gained significant attention for its ability to generate high-quality images from textual descriptions. In the video, it's highlighted as an upgrade with improved features over its predecessors. The script mentions that it offers better text prompt understanding and higher resolution images, making it a superior model for generating anime art and other detailed images.


Fine-tuning refers to the process of adjusting and optimizing a pre-trained AI model to perform better on a specific task or dataset. In the context of the video, the speaker suggests that while SD3 may not provide optimal results on the first day of its release, it has the potential to yield better results once the community begins fine-tuning it. This process is crucial for adapting the model to generate images that align more closely with user expectations.

๐Ÿ’ก2B model

The term '2B model' in the script refers to a medium-sized version of the AI model, which is contrasted with an '8B model' that is larger and more resource-intensive. The 2B model is said to be sufficient for most users and is expected to be the primary choice for fine-tuning due to its balance between performance and resource requirements.

๐Ÿ’กControl net

A control net is a feature in AI image generation models that allows for more precise control over the elements and composition of the generated images. The script mentions that SD3 has an 'amazing control net setup,' suggesting that it provides users with greater control over the generation process, enabling the creation of more complex and detailed images.


Resolution in the context of image generation refers to the number of pixels in an image, which determines its clarity and detail. The script emphasizes that SD3 supports higher resolutions, specifically mentioning 1024x1024 pixels, which is an improvement over previous models that were limited to 512x512 pixels.

๐Ÿ’กVAE (Variational Autoencoder)

VAE, or Variational Autoencoder, is a type of neural network architecture used in deep learning for dimensionality reduction and feature learning. In the video, the speaker discusses the upgrade from a 4-channel VAE to a 16-channel VAE in SD3, which allows for more detailed image generation and training, retaining more information and producing higher quality outputs.

๐Ÿ’กFID Score

FID Score, or Frรฉchet Inception Distance, is a metric used to evaluate the quality of generated images by comparing them to real images. A lower FID score indicates more realistic images. The script cites research showing that the 16-channel VAE in SD3 significantly improves the FID score, demonstrating its ability to generate more realistic images compared to models with fewer channels.

๐Ÿ’กPrompt Understanding

Prompt understanding is the ability of an AI model to correctly interpret and act upon the textual prompts given by users to generate images. The video highlights that SD3 has improved prompt understanding, allowing it to generate images that more accurately reflect the textual descriptions provided by users.

๐Ÿ’กAnime Art

Anime Art refers to the style of art commonly found in Japanese animated productions. The script mentions that SD3 is particularly good at generating anime art, indicating that the model has been trained or is particularly adept at handling the stylized and expressive nature of this art form.


High-resolution images contain more pixels and therefore offer greater detail and clarity. The script notes that SD3 can generate high-resolution images, which is an important feature for users who require detailed and clear images for various applications.

๐Ÿ’กHugging Face

Hugging Face is a company that provides a platform for developers to share and collaborate on machine learning models. In the video, the speaker guides viewers on how to download and use SD3 through Hugging Face's platform, indicating that it is one of the sources where the model can be accessed.


Stable Diffusion 3 (SD3) is released and is ready for use.

SD3 may not provide better results on the first day without fine-tuning.

SD3 is a medium-sized 2B model, adequate for most users until they upgrade their GPU.

SD3's text prompt understanding is improved with 16 channel VAE.

SD3 includes features like control net and high-resolution capabilities.

SD3 can generate text with better prompt understanding and improved facial and hand depictions.

SD3 is not yet fine-tuned but the community is expected to make improvements.

SD3 is safe to use and offers unlimited control for image generation.

SD3 is expected to outperform previous models like 1.5 and sdlx, but may require community fine-tuning.

SD3 uses a 16 channel VAE for better detail retention and output quality.

SD3 is a 1024x1024 pixel model, versatile and less resource-intensive than previous models.

The 2B model of SD3 is recommended for most users due to its balance between quality and resource requirements.

SD3's increased latent channel capacity significantly boosts reconstruction performance.

SD3's research paper confirms higher image quality with increased model capacity.

SD3 allows for the generation of images with complex prompts, such as pixel art and scenes with text.

Comparisons between SD3 and other models show SD3's potential for better text and image generation.

SD3 can be used on various backend systems, including Comfy and Stable Swarm.

Instructions for downloading and setting up SD3 are provided.