SDXL Lightning For Stable Diffusion ComfyUI - How To Use And What We Should Know

Future Thinker @Benji
5 Mar 202414:01

TLDRThe video discusses the SDXL Lightning, a tool created by Bite Den, which was launched 12 days prior to the video. The presenter emphasizes the importance of waiting for AI models to stabilize before discussing them to avoid misinformation and crashes. The SDXL Lightning is showcased with a demo page and is highlighted for its low sampling steps and CFG number settings for image generation. The video explains the process of downloading and using the tool with Comfy UI, including the all-in-one checkpoint models and the separate UNet checkpoint models for Diffuser. The presenter tests the tool using four steps and explains the optimal settings for performance. The video also demonstrates how to integrate SDXL Lightning into a workflow diagram for Comfy UI, noting the simplicity compared to SDXL Turbo. The presenter shares their preferred method of using SDXL Lightning with Laura models for faster image generation and the flexibility it offers. The video concludes with a mention of the limitations of using SDXL Lightning for animation workflows.


  • 🌟 SDXL Lightning is a new model created by Bite Den, designed for fast and stable AI image generation.
  • πŸ“… The model was launched 12 days prior to the video, with a caution to wait for stability due to the fast pace of AI updates.
  • πŸ”— A demo page is available for SDXL Lightning where users can input text prompts for image generation.
  • πŸ“ˆ Two-step, four-step, and eight-step models are available, each optimized for their respective step counts.
  • πŸ“ All-in-one checkpoint models are provided for Comfy UI, and separate UNet checkpoint models for Diffuser.
  • πŸ“š Laura's files are also available for both Diffuser and Comfy UI to enhance the image generation process.
  • πŸ”§ For Comfy UI users, placing the checkpoint models in the correct folders and setting the sampling step to four with a CFG of one is recommended.
  • ⚑ SDXL Lightning is fast, with the ability to generate images in less than a second using the four-step model.
  • πŸŽ›οΈ The model can be connected without extra custom nodes, simplifying the image generation process compared to SDXL Turbo.
  • πŸ–ΌοΈ Image quality is good for the low sampling steps and CFG used, though not excellent, making it suitable for initial idea generation.
  • ➑️ For animation workflows, SDXL Lightning may not be the best choice, as it did not perform well in detailed animations even at higher settings.
  • πŸš€ The flexibility of using SDXL Lightning with Laura models allows for fine-tuning and faster image generation, making it ideal for quick concept development.

Q & A

  • What is SDXL Lightning?

    -SDXL Lightning is a tool created by Bite Den for stable diffusion in ComfyUI, which allows for fast and efficient image generation with low sampling steps and CFG number settings.

  • Why did the speaker wait to discuss SDXL Lightning?

    -The speaker waited to discuss SDXL Lightning to allow it to become more stable, as AI models can change rapidly in the first few days or weeks after release.

  • What are the different models released by Bite Den for SDXL Lightning?

    -Bite Den released two-step, four-step, and eight-step models individually, as well as all-in-one checkpoint models for ComfyUI and unet checkpoint models for Diffuser.

  • How does one use SDXL Lightning with ComfyUI?

    -To use SDXL Lightning with ComfyUI, one needs to download the checkpoint models and place them in the models checkpoint folder, and place the Laura files in the Laura subfolders. Then, set the sampling step to four and CFG to one for optimal performance.

  • What is the recommended sampling step and CFG setting for SDXL Lightning?

    -The recommended sampling step is four, and the CFG setting should be one for the best performance with SDXL Lightning.

  • How does SDXL Lightning compare to SDXL Turbo in terms of speed and complexity?

    -SDXL Lightning is similar to SDXL Turbo in speed, with images generated almost in real time. However, it is simpler to connect as it does not require extra custom nodes to generate images.

  • What is the best sampling scheduler to use with SDXL Lightning?

    -The speaker found that using the SGM (Superposition Guided Method) uniform scheduler performs better for image generation with SDXL Lightning.

  • How long does it typically take to generate an image with SDXL Lightning?

    -With SDXL Lightning, an image can be generated in less than one second, even for larger images.

  • What is the speaker's preferred method for using SDXL Lightning?

    -The speaker prefers to use SDXL Lightning by incorporating more Laura Styles along with the checkpoint styles and other additional Laura Styles before passing it to SDXL Lightning, allowing for lower sampling steps and faster generation.

  • Is SDXL Lightning suitable for animation workflows?

    -The speaker mentions that SDXL Lightning may not be the best choice for animation workflows, as it did not perform well in detail and clarity even with higher settings.

  • What are the advantages of using SDXL Lightning for initial image generation?

    -SDXL Lightning is advantageous for quick initial image generation, allowing users to get initial ideas rapidly. Once a base image is generated, it can be further enhanced using other samplers or incorporated into another workflow for more detailed refinement.



πŸš€ Introduction to SdxL Lightning by Bite Den

The video begins with an introduction to SdxL Lightning, a new AI model created by Bite Den. The speaker chose to discuss it after a 12-day stabilization period to ensure its reliability. They caution against following AI developments too closely due to rapid changes. A demo page is mentioned, where viewers can experiment with text prompts for image generation using low sampling steps and CFG numbers. The video outlines the availability of two-step, four-step, and eight-step models, as well as all-in-one checkpoint models for Comfy UI and Unet checkpoint models for Diffuser. The speaker plans to test these models using Comfy UI with a focus on the four-step process, emphasizing the model's optimal performance at four sampling steps.


🎨 Setting Up and Testing SdxL Lightning Workflow

The speaker proceeds to demonstrate how to set up and use SdxL Lightning within Comfy UI. They guide viewers on how to modify the default workflow to incorporate SdxL Lightning checkpoint models, highlighting the ease of setup without the need for custom nodes as required with SdxL Turbo. The video showcases the speed of image generation using the model, with a focus on the Sgm Uniform sampling scheduler for better performance. The speaker also discusses the process of using two Samplers for faster image generation and the potential for upscaling images while maintaining quality. They conclude this section with a demonstration of the model's ability to generate detailed images even with low sampling steps and CFG.


πŸ” Enhancing Image Generation with Laura Models

The final paragraph focuses on enhancing image generation using Laura models in conjunction with SdxL Lightning. The speaker prefers this method for its flexibility and speed, allowing for the incorporation of various Laura styles and checkpoint models for improved image quality. They demonstrate the process of using a futuristic text prompt and generating images with increased speed by reducing sampling steps. The video also touches on the limitations of using SdxL Lightning for animation, suggesting that it may not be the best choice for detailed work. The speaker concludes by encouraging viewers to explore this approach for quick image generation and as a base for further refinement in other workflows.



πŸ’‘SDXL Lightning

SDXL Lightning is a model created by Bite Den, which is designed for image generation using Stable Diffusion ComfyUI. It is noted for its fast processing speed and relatively low sampling steps and CFG (Control Flow Graph) settings. In the video, it is discussed as a tool for quickly generating images with good average quality, making it suitable for initial idea generation.


ComfyUI is a user interface for interacting with AI models, such as SDXL Lightning, for image generation. It allows users to input text prompts and generate images based on those prompts. In the context of the video, ComfyUI is used to demonstrate the ease of use and the speed at which SDXL Lightning can generate images.

πŸ’‘Checkpoint Models

Checkpoint models refer to saved states of a neural network that can be loaded to continue training or to use for inference. In the video, the presenter discusses using checkpoint models for SDXL Lightning and how they can be downloaded and used within ComfyUI for image generation.

πŸ’‘U-Net Checkpoint Models

U-Net is a type of convolutional neural network architecture that is commonly used in image segmentation tasks. In the context of the video, U-Net checkpoint models are mentioned as an alternative to the all-in-one checkpoint models for users of the Diffusers interface, which is different from ComfyUI.

πŸ’‘Lora's Files

Lora's files are specific configurations or models that can be used to enhance or modify the behavior of an AI system. In the video, they are used in conjunction with checkpoint models to improve the performance of SDXL Lightning, particularly when using ComfyUI.

πŸ’‘Sampling Steps

Sampling steps refer to the number of iterations or steps taken during the image generation process. The video emphasizes the use of very low sampling steps with SDXL Lightning to achieve faster image generation without compromising too much on quality.

πŸ’‘CFG (Control Flow Graph)

CFG is a representation of the flow of computations within a system, and in the context of AI image generation, it can affect the output quality and style. The video discusses setting low CFG numbers for SDXL Lightning to balance speed and image quality.


In the context of AI and neural networks, a scheduler is an algorithm that adjusts the learning rate or other parameters over time. The video mentions using different schedulers like 'sgm uniform' and 'e ancestral' for optimizing the image generation process with SDXL Lightning.

πŸ’‘Latent Upscale

Latent upscale refers to the process of increasing the resolution or detail of a generated image by enhancing its latent representation. The video demonstrates using latent upscale to improve the quality of images generated with SDXL Lightning.


Denoising is the process of reducing noise or artifacts in an image to improve its clarity. In the video, the presenter discusses adjusting denoising levels to refine the quality of the generated images with SDXL Lightning.

πŸ’‘Animation Workflow

An animation workflow refers to the sequence of steps or processes involved in creating animated content. The video briefly touches on the use of SDXL Lightning within an animation workflow, noting that it may not perform as well for detailed animation as for static image generation.


SDXL Lightning is a new AI model created by Bite Den, launched 12 days ago.

The model is designed for fast and stable image generation with low sampling steps and CFG number settings.

SDXL Lightning has a demo page available for users to try out text prompts and natural language style text prompts.

Two-step, four-step, and eight-step models have been released, each with separate files for download.

An all-in-one checkpoint model and a UNet checkpoint model are available for Comfy UI and Diffuser respectively.

Laura's files are also provided for both Diffuser and Comfy UI to enhance the AI's performance.

For optimal performance, the four-step model is recommended with a CFG of 1.

SDXL Lightning is similar to SDXL Turbo but simpler to connect without extra custom nodes.

The model generates images almost in real-time, with the first sampler taking less than a second.

The SGM uniform sampling scheduler is found to be the best performer with SDXL Lightning.

A new workflow diagram is introduced for easy setup and use of SDXL Lightning in Comfy UI.

Loading the checkpoint models may take some time initially, but subsequent loads are fast.

The model can generate large images quickly, even at 1024 resolution in under a second.

VAE (Variational AutoEncoder) can be used with SDXL Lightning for better image performance.

The method of using checkpoint models with SDXL Lightning is straightforward and does not require complex setup.

Using Laura models in conjunction with SDXL Lightning allows for faster and more flexible image generation.

The model is suitable for quickly generating images for initial ideas, which can then be refined using other tools.

SDXL Lightning is not recommended for animation due to performance issues, similar to SDXL Turbo.

The video provides a comprehensive guide on how to use SDXL Lightning for fast and efficient image generation.