Stable Cascade, local installation.

Vladimir Chopine [GeekatPlay]
20 Feb 202415:38

TLDRIn this video, Vadir introduces Stability Cascade, a new text-to-image architecture from Stability AI. The software is designed for non-commercial use and offers faster and more accurate image generation compared to previous models. Vadir provides a step-by-step guide for local installation, including using Pinocchio for easier setup. The video demonstrates the software's capabilities with various prompts, showcasing impressive image quality and rendering speed. Despite some minor issues like the 'alien hand' problem, which can be fixed with negative prompts, Stability Cascade is praised for its performance and potential for future commercial applications. The video concludes with a call to action for viewers to subscribe, like, and share for more content.


  • 🎉 Stable Cascade is a new release from Stability AI that uses the Worchester architecture for large-scale text-to-image generation.
  • ⚠️ It is intended for non-commercial use only, meaning you cannot resell or use it for commercial purposes.
  • 📚 The code is available on Stability AI's GitHub, which is also where the installation will be sourced from.
  • 🚀 The model is optimized for faster performance and can establish better connections, requiring fewer steps compared to other models like SDXL.
  • 📈 In speed comparisons, Stable Cascade performs faster than SDXL with only 20 plus 10 additional steps.
  • 📘 It creates a larger library with 1.4 billion parameters, which allows for more accurate work with the prompts provided.
  • 🧩 The model works with training using Fun Tune Control Net Laura and is capable of both in-painting and out-painting.
  • 💻 Local installation is possible, with options for manual installation from GitHub or using package managers like Pinocchio.
  • 🖥️ The interface is simplified, with options for prompt generation and advanced settings including negative prompts and seeds.
  • 🔍 The model is resource-efficient, utilizing less memory and GPU power, making it suitable for machines without high-end specifications.
  • 🖼️ The output quality is impressive, with the ability to render high-detail images quickly, even at increased resolutions.
  • 🛠️ Common issues like 'alien hands' can be fixed with negative prompts, although it's noted that the model sometimes struggles with rendering fingers correctly.

Q & A

  • What is the name of the new release from Stability AI discussed in the video?

    -The new release from Stability AI discussed in the video is called Stability Cascade.

  • What type of architecture does Stability Cascade use?

    -Stability Cascade uses the Worcester architecture.

  • What are the limitations regarding the use of Stability Cascade?

    -Stability Cascade is for non-commercial use only, meaning it cannot be used for reselling or as part of commercial work.

  • Where can the code for Stability Cascade be found?

    -The code for Stability Cascade is available on Stability AI's GitHub.

  • How does Stability Cascade compare to SDXL in terms of speed and performance?

    -Stability Cascade requires only 20 plus 10 additional steps, making it a bit faster than SDXL, which uses 50 steps. However, SDXL Turbo can perform faster with just one step but may lack coherence in animations.

  • What is the size of the model used in Stability Cascade?

    -Stability Cascade uses a large-scale model with approximately 1.5 to 1.4 billion parameters.

  • What are the additional features provided by Stability Cascade?

    -Stability Cascade offers optional image variations and works with both in-painting and out-painting.

  • How does Stability Cascade handle training and fine-tuning?

    -Stability Cascade works with a fun tune control net called Laura, which allows it to work with various elements and perform better with the prompts.

  • What is the recommended system requirement for running Stability Cascade locally?

    -While the video does not specify the exact requirements, it is implied that a powerful GPU, such as an RTX 3090, is suitable for running Stability Cascade locally.

  • How can Stability Cascade be installed on a local machine?

    -Stability Cascade can be installed locally by following the instructions on the Stability AI GitHub repository or by using a package manager like Pinocchio.

  • What are the steps involved in using Stability Cascade after installation?

    -After installation, users can input prompts and use advanced options to generate images. They can adjust settings like negative prompts, seed, and image height to refine the output.

  • What are some common issues encountered when using Stability Cascade and how can they be resolved?

    -One common issue is the creation of 'alien hands' with incorrect numbers of fingers. This can be resolved by refining negative prompts to better exclude unwanted elements like extra fingers or broken limbs.



📢 Introduction to Stability Cascade - Noncommercial Use and Overview

The video begins with the host, Vadir, welcoming viewers to the channel and introducing a new release from Stability AI called Stability Cascade. This tool utilizes the Worchester architecture for a large-scale text-to-image application, promising faster and more accurate performance. Vadir emphasizes that Stability Cascade is for noncommercial use only, meaning that creations cannot be resold or used in commercial work. The code for Stability Cascade is available on Stability's GitHub, and Vadir provides a link for viewers to explore. The video also includes a speed comparison with other models, highlighting Stability Cascade's efficiency with fewer steps required for coherence in animations. The model operates with 1.5 to 1.4 billion parameters and works with fun tune control net Laura, offering both in-painting and out-painting capabilities. Vadir also discusses the importance of negative prompts and seed settings for generating images.


💻 Installing Stability Cascade with Pinocchio - A Step-by-Step Guide

The host guides viewers through the process of installing Stability Cascade using Pinocchio, an application that supports Stability Cascade, although it's not yet available in Stability Matrix. The installation process involves downloading and unzipping the software, which the host assures is safe despite warnings from the system about unverified software. After unzipping, the host changes the installation path to a drive with more space and proceeds with the installation. The video pauses while the models and packages are downloaded. Once completed, the host launches the application and navigates through the settings before starting the installation of Stability Cascade from the Discover section within Pinocchio. The host also mentions the need to install additional requirements and to possibly rerun the installation if it times out or encounters errors. The video concludes with the successful installation and launch of Stability Cascade.


🖼️ Testing Stability Cascade's Image Generation - Interface and Results

After installation, the host explores the simplified interface of Stability Cascade, which includes options for prompt generation and advanced settings. The host discusses the use of negative prompts and seed settings, then proceeds to test different prompts, comparing the results. The video demonstrates the creation of images with varying prompts, noting the speed and quality of the output. The host also monitors system resources during the process, noting the efficient use of memory and GPU. The results are impressive in terms of detail and speed, with the host expressing satisfaction with the image quality. The host also experiments with increasing the height parameter and observes the impact on the rendering process. A common issue with fingers in generated hands is noted and discussed, with the host suggesting the use of negative prompts to correct such anomalies.


🎉 Conclusion and Viewer Engagement - Impressions of Stability Cascade

The host concludes the video by expressing admiration for Stability Cascade's rendering speed and the quality of the images it produces. They highlight the model's ability to create large images efficiently and with minimal resource usage. The host looks forward to future models that may be suitable for commercial use and encourages viewers to subscribe, like, and share the video for support. The video ends on a positive note, with the host thanking viewers and wishing them a great day.



💡Stable Cascade

Stable Cascade is a new release from Stability AI, which is a large-scale architecture for text-to-image generation. It is designed to perform faster and more accurately with prompts, allowing for quicker image generation. In the video, it is compared to other models like SDXL and showcased for its speed and quality in image creation.

💡Worchester Architecture

The Worchester architecture is mentioned as the underlying framework for Stable Cascade. While the video does not go into detail about the architecture itself, it implies that it is a significant factor in the performance and capabilities of Stable Cascade.

💡Noncommercial Use

The video emphasizes that Stable Cascade is intended for noncommercial use only. This means that any creations made with the tool cannot be resold or used as part of commercial work. This limitation is an important consideration for users interested in using the technology.


GitHub is referenced as the platform where the code for Stable Cascade is made available. It is the source from which the software can be downloaded and installed, as demonstrated in the video. GitHub is a web-based hosting service for version control using Git, commonly used for software development.

💡Optimized Model

An optimized model in the context of the video refers to a version of Stable Cascade that can perform faster and more efficiently. The video discusses how this model can establish connections and withdraw information more effectively, leading to better performance in generating images from text prompts.

💡Speed Comparison

The term 'speed comparison' is used to contrast the performance of Stable Cascade with that of SDXL and SDXL Turbo. The video shows that Stable Cascade requires fewer steps to achieve similar results, making it faster and more efficient for image generation tasks.

💡Image Variations

Image variations refer to the ability of Stable Cascade to generate multiple versions of an image from a single prompt. This feature allows for a range of creative outputs and is demonstrated in the video as an optional feature within the software.


Parameters in the context of Stable Cascade refer to the variables that define the model's behavior. The video mentions that the model has 1.4 billion parameters, which contribute to its accuracy and ability to work effectively with prompts.

💡Fun Tune Control Net Laura

Fun Tune Control Net Laura is mentioned as a component that Stable Cascade works with. While the video does not provide a detailed explanation, it suggests that this is part of the training process for the model, likely related to fine-tuning its performance.

💡In-Painting and Out-Painting

In-painting and out-painting are techniques used in image editing. In the context of the video, Stable Cascade is capable of both, allowing it to fill in missing parts of an image (in-painting) and to generate new parts that were not originally present (out-painting).

💡Local Installation

Local installation is the process of installing and running Stable Cascade on a personal computer rather than using it through an online platform. The video provides a step-by-step guide on how to perform a local installation, which is useful for users with powerful hardware who wish to use the software offline.


Introduction to Stability Cascade, a new release from Stability AI.

Stability Cascade uses the Worchester architecture for large-scale text-to-image generation.

The model allows for faster and more accurate performance to the prompt.

Stability Cascade is for non-commercial use only, cannot be used for commercial work or reselling.

All code is available on Stability AI's GitHub for installation.

The model is optimized for faster performance with a big model that establishes more connections.

Speed comparison shows Stability Cascade is faster than SDXL with fewer steps required.

Stability Cascade can handle image variations, both in and out of painting.

Technical information reveals a library with 1.5 billion parameters for more accurate work.

The model works with fun tune control net Laura and is provided with optional image variations.

Local machine installation is possible with options for manual installation or using a package manager like Pinocchio.

RTX 3090 is recommended for running Stability Cascade due to its computational requirements.

Pinocchio is a package manager that supports Stability Cascade and offers an easy installation process.

The installation process includes downloading models and packages, which may take some time.

After installation, Stability Cascade provides a simplified interface for prompt generation.

The model is capable of creating high-quality images with impressive detail and speed.

Stability Cascade uses less memory and GPU resources compared to other models, making it more efficient.

The model can render images with high resolution and detail, even when pushing the limits of the interface settings.

Common issues like alien hands can be fixed with negative prompts, although it's preferable if the model handles them internally.

The video concludes with an impressive demonstration of Stability Cascade's capabilities and potential for future commercial use.