Kasucast #23 - Stable Diffusion 3 Early Preview

14 Apr 202433:03

TLDRIn the Kasucast #23 video, the host shares an in-depth preview of Stable Diffusion 3, highlighting its improvements in multi-prompt handling, image quality, and spelling capabilities. The video showcases various tests conducted using SD3, including creating images for product design, semantic object placement, and generating scenes from media. The host also explores SD3's ability to understand natural language prompts and its potential impact on the creative and design community.


  • 🎉 The video discusses the preview version of Stable Diffusion 3 (SD3), highlighting improvements in multi-prompt inputs, image quality, and spelling abilities.
  • 🔍 The SD3 server interface is familiar to users of mid-Journey, with additional options for high-resolution, aspect ratio, and negative prompts.
  • 📈 Output resolution sizes are similar to SDXL, with potential for larger resolutions in future releases.
  • 🎨 The creator tests SD3's capabilities by attempting to recreate a scene from Dune Part 2 and designing a futuristic communication device.
  • 📝 SD3's text functionality is tested, with mixed results in generating text accurately within images.
  • 🧍‍♂️ Multi-prompt capabilities are explored, showing potential for generating images with multiple subjects, though with some limitations.
  • 🤖 The video touches on challenges in semantic object placement and product design renders, indicating areas for future improvement.
  • 🌐 Additional features like UI/HUD design, vector graphics, fashion photography, and architecture visualization are briefly examined.
  • 📸 A test of SD3's ability to recreate a real-world event (cargo ship incident) shows limitations in perspective and scale, but also safety against misinformation.
  • 🌐 The creator also experiments with generating thumbnails and using the Cinematic Styler, which introduces a vignette and split toning to images.
  • 📚 Natural language prompting is demonstrated, showing that while not perfect, it offers a promising direction for generating images from descriptive text.

Q & A

  • What is the main focus of Stable Diffusion 3 (SD3) that Stability AI has improved upon from previous versions?

    -Stability AI has focused on improving multi-prompt inputs, image quality, and spelling abilities in Stable Diffusion 3.

  • How does the user interact with the SD3 bot on the Discord server?

    -The user joins an SD3 bot channel, types 'slash dream' in the message box, and then selects additional options that appear to customize their prompt.

  • What new aspect ratios are available for image output in SD3 that were not present in previous models?

    -SD3 introduces new aspect ratios, including 21x9 and 2.35:1, which are cinematic aspect ratios, in addition to the standard 1:1 and 4:3.

  • What challenges did the creator face when trying to generate a futuristic communication device with SD3?

    -The creator struggled to get SD3 to generate a device that folded out laterally as desired, indicating that complex产品设计 (product designs) can be difficult for the AI to interpret correctly.

  • How did the creator test the text functionality of SD3?

    -The creator used the text functionality to generate images with the text 'welcome to dtown', testing the AI's ability to create text within images accurately.

  • What is the significance of multi-prompt improvements in SD3 for creators?

    -Multi-prompt improvements allow creators to include more elements in a single prompt, which can enhance the complexity and detail of the generated images without needing additional tools or steps.

  • How did the creator approach testing SD3's capabilities for semantic object placement and product design renders?

    -The creator attempted to generate images with specific object placement, such as a futuristic heart in the top left corner of an image, to evaluate the AI's ability to understand and execute detailed compositional requests.

  • What feature of SD3 did the creator use to generate establishing shots and product design photography?

    -The creator utilized the 'Cinematic Styler' feature to generate images with a more stylized and professional look, suitable for establishing shots and product design photography.

  • How did the creator experiment with natural language prompting in SD3?

    -The creator used natural language prompts based on descriptions from the shot deck website and compared the results with traditional tag-based prompts to evaluate the effectiveness of natural language in generating images.

  • What challenges did the creator encounter when generating UI or HUD designs with SD3?

    -The creator found it difficult to get SD3 to generate UI or HUD elements in a first-person view from inside a helmet, suggesting that the AI may have challenges understanding certain perspectives or complex UI layouts.

  • How did the creator's experience with generating fashion photography and architecture visualization with SD3?

    -The creator was able to generate a variety of fashion and architecture images, exploring different styles and aesthetics, but noted that the AI sometimes skewed towards certain aesthetics or styles, such as the 'Russian influencer' look.



🎨 Introduction to Stable Diffusion 3

The video begins with an introduction to the creator's experience at Stability AI, where they have been working for two weeks and have access to the preview version of Stable Diffusion 3 (SD3) through the SD3 Launchpad server on Discord. The creator has permission to share images generated from SD3 and plans to test its functionalities, focusing on multi-prompt inputs, image quality, and spelling abilities. The video will approach the usage of SD3 from the perspective of a creator and a member of the generative AI community, heavily stress testing SD3 through various prompts and real-world creative scenarios. The creator also provides an overview of the SD3 server interface on Discord and discusses the prompt settings and new aspect ratios available for output images.


📱 Prototyping a Futuristic Communication Device

The creator attempts to prototype a futuristic communication device that resembles an 'L' shape and folds out laterally with a holographic screen. Despite several attempts and detailed prompts, SD3 struggles to generate the desired design. The creator then compares the results with quick sketches they made, which were then processed through a different AI model, ControlNet, and upscaled with Superior. The sketches served as a basis for a design that folds out with a telescoping mechanism, inspired by the creator's experience with a butterfly knife.


🔠 Testing Text Generation and Multi-Prompt Features

The video showcases tests on SD3's text generation capabilities and its ability to handle multi-prompt inputs. The creator experiments with generating text in the sky, with varying levels of success. They also test SD3's multi-prompt feature by attempting to generate images with multiple characters, such as a group shot of three friends with specific characteristics. The results are mixed, with some images closely matching the prompts and others not meeting the desired outcome. The creator also discusses the potential of multi-prompt inputs for anime-style images and the importance of specificity in prompts for better results.


🎭 Challenges in Animation and Scene Composition

The creator explores SD3's ability to generate complex scenes, such as an animation depicting two people fighting in a dynamic environment. They use a scene from the anime 'Fate/stay night: Heaven's Feel III' as a reference and input detailed prompts to achieve the desired composition. The results are promising, with some images closely resembling the intended scene. The creator also discusses the limitations of SD3 in controlling the placement of subjects within the generated images and the need for further training and improvements.


🌆 Generating Futuristic Cityscapes and Industrial Designs

The creator experiments with generating futuristic cityscapes and industrial designs. They envision a city on the water, with each petal of a lotus housing a different ward, and attempt to generate establishing shots and product design photography. The results include a variety of images, some of which capture the desired aesthetic. The creator also discusses the challenges of product placement and semantic object positioning in SD3, noting that the model still struggles with these aspects.


📹 Cinematic Style and Natural Language Prompting

The creator tests SD3's 'Cinematic' styler and its ability to understand natural language prompts. They use references from the website 'Shot Deck' to recreate impactful scenes from various media. The results show that SD3 can generate images close to the desired scenes when provided with detailed natural language prompts or tags from Shot Deck. The creator also discusses the limitations and potential of natural language prompting in SD3 and its comparison with other methods of generating images.


🖼️ Exploring UI/HUD Design and Real World Applications

The creator delves into generating UI/HUD designs and other real-world applications with SD3. They attempt to recreate the Pokémon UI, generate Magic: The Gathering cardbacks, and design futuristic helmets with integrated displays. The results are varied, with some designs closely aligning with the prompts and others requiring further refinement. The creator also generates vector assets for motion graphics and explores generating fashion runway images, architecture visualizations, and abstract designs, showcasing the versatility of SD3 in various creative fields.

📈 Conclusion and Future Prospects of SD3

In conclusion, the creator reflects on their experience with SD3, acknowledging its natural evolution from previous diffusion models and its ability to deliver on its claims, despite some imperfections. They highlight areas where SD3 struggles, such as controlling subject placement and object complexity, but express optimism for future improvements by the community. The creator thanks the viewers for watching and looks forward to sharing more in the future.



💡Stable Diffusion 3

Stable Diffusion 3 (SD3) is an advanced version of a generative AI model developed by Stability AI. It is designed to improve upon previous models by enhancing functionalities such as multi-prompt inputs, image quality, and text-to-image capabilities. In the video, the creator explores SD3's features through various tests and real-world creative scenarios, demonstrating its potential for artists and designers.


A multi-prompt refers to the ability of the AI model to process and generate outputs based on multiple textual prompts simultaneously. This feature is significant for creators as it allows for more complex and nuanced image generation. The video discusses the improvements made to this feature in SD3, showcasing how it can handle prompts with multiple subjects or elements.

💡Image Quality

Image quality is a measure of the clarity, detail, and overall aesthetic appeal of a generated image. SD3 focuses on enhancing image quality, which is crucial for professional use in creative industries. The video script mentions testing SD3's image quality through various prompts and comparing the results with previous models.

💡Spelling Abilities

Referring to the AI's capability to understand and generate text accurately, spelling abilities are important for ensuring that text within generated images is correct and legible. The video demonstrates SD3's text generation features, noting that it has improved from previous models in creating images with embedded text.

💡Semantic Object Placement

Semantic object placement is the AI's ability to understand the context and desired composition of an image, placing objects in a way that makes logical sense. In the video, the creator attempts to challenge SD3 with prompts that specify the location of objects within the generated image, evaluating how well SD3 adheres to these specifications.

💡Natural Language Prompting

Natural language prompting involves the AI's capacity to interpret and respond to human-like, conversational text inputs. The video explores this feature by testing SD3's ability to generate images from more complex, descriptive prompts that resemble natural language, as opposed to structured, tag-based inputs.

💡UI/HUD Design

UI/HUD (User Interface/Heads-Up Display) design refers to the creation of graphical interfaces for digital devices or virtual environments. The video examines SD3's potential in generating 2D assets and layouts for UI/HUD elements, which are essential for various digital mediums, including video games, apps, and augmented reality experiences.

💡Vector Graphics

Vector graphics are images composed of points, lines, and curves that can be scaled without loss of quality, making them ideal for logos, icons, and illustrations. The script discusses using SD3 to generate vector assets, which can be a significant timesaver for designers working with scalable graphics.

💡Fashion Photography

Fashion photography involves capturing images that showcase clothing, accessories, and fashion trends. In the video, the creator experiments with prompts aimed at generating fashion photography styles, exploring SD3's ability to create images that could be used in the fashion industry.

💡Architecture Visualization

Architecture visualization is the process of creating visual representations of architectural designs. The video script includes attempts to generate images of architectural structures using SD3, evaluating the model's effectiveness in visualizing complex building designs and styles.

💡Cinematic Style

Cinematic style refers to the visual and narrative techniques used in filmmaking that can be applied to image generation to create a more dramatic or engaging aesthetic. The video discusses applying a 'cinematic filter' in SD3 to generate images that have a movie-like quality, enhancing their emotional impact and storytelling potential.


The video provides an early preview of Stable Diffusion 3 (SD3), showcasing its functionalities and improvements over previous models.

The host has been working at Stability AI for about two weeks and has access to the preview version of SD3 through the SD3 Launchpad server on Discord.

SD3 focuses on and improves multi-prompt inputs, image quality, and spelling abilities.

The video tests SD3's performance through various prompts and real-world creative situations, approaching the usage from a creator's and a generative AI community member's perspective.

The SD3 server interface is similar to Midjourney, with public bot channels and internal channels for Stability employees.

SD3 introduces new aspect ratios for output images, expanding creative possibilities beyond SD1.5 and SDXL.

The host attempts to recreate a key frame from 'Dune Part 2' using SD3, demonstrating the model's capabilities in generating cinematic images.

SD3 struggles with complex product design renderings, such as a futuristic communication device, indicating areas for further improvement.

The text functionality of SD3 is tested, showing potential in generating text within images, which could save time compared to using control nets.

Multi-prompt capabilities are explored, with SD3 generating images featuring multiple characters or subjects, a significant advancement.

The host discusses the limitations of SD3 in controlling the semantic placement of objects within images, a challenge for product designers.

SD3's ability to recreate scenes from media is tested using references from Shot Deck, with mixed results in accuracy and believability.

The video examines SD3's natural language prompting feature, which shows promise in understanding and generating images from descriptive text.

The host experiments with UI/HUD design using SD3, highlighting the potential for quickly generating vector assets for motion graphics.

SD3's capacity to generate fashion photography and architecture visualizations is tested, with some successful and abstract results.

The video concludes with a positive impression of SD3 as a natural evolution of diffusion models, acknowledging its current imperfections and potential for community-driven improvements.