Guide to Stable Diffusion Guidance Scale

November 26

Generative AI is the buzzword in Tech business today! Thanks to cutting-edge machine learning technologies, you can create any bizarre or unique image you want in under five minutes.

Generative Artificial Intelligence is an algorithm that allows a prompt to produce a new image, text, or audio. It has many applications in business, creative fields, and e-commerce. However, one of the problems that you may face as a user is the lack of a framework when generating images. The Stable Diffusion Guidance Scale(SDGS) helps to establish parameters that refine the generative process.

All about Generative Images

Generative AI is a gift that keeps on giving. There are plenty of avenues to use this tool. It works in the fields of image editing, asset creation in gaming, Apparel tryouts on fashion sites, product images on e-commerce sites, and character creation in VFX.

Stable Diffusion Model 

Before getting into SDGS, also known as Classifier-free Guidance Scale (CFG), understanding the Stable Diffusion Model and how it has revolutionized the AI space is essential. The Stable Diffusion Model is a unique machine-learning model that uses text to generate images. Unlike Midjourney, it works on introducing noise to images and then applying the concept of “denoising” to create realistic visualizations.

The Need for Stable Diffusion Guidance Scale 

Generative AI is churning out images at command, but several problems have been observed concerning the images.

  •  Inaccurate image generation

The image you get may differ from what you prompted.

  • Artifacts

Sometimes, images that have no factual base get created. For instance, the human hand may have eight fingers instead of five.

  • Harmful content creation 

Unfiltered data sets may create offensive visuals.

  • Generic Images

Overgeneralization of images with no specific details may be generated.

What Does a Stable Guidance Diffusion Scale Do?

  • The  Classifier-free Guidance Scale(CFG) scale controls and sets how much the generated image adheres to or follows the given prompt. 
  • It allows users to shift and adjust the generated image per their requirements.  
  • This extra setting in Stable Difusion allows creators to produce near-perfect, realistic visual representations.
  • More specifically, they can now produce images that closely follow the text prompt entered by them.  


How to Use SDGS for Image Creation?

The CFG or SDGS functionality in Stable Diffusion is a versatile balancing tool that elevates image generation to another level. This CFG scale is helpful for both text-image generation and image-image generation.

  • The scale allows for choices of only positive numbers ranging from 1 to 30, with 1 allowing maximum creative freedom to the generative model.
  • It is critical to note that merely setting the level to the maximum does not guarantee a perfect picture.
  • The higher the value on CFG, the more the picture will align with the given prompt. However, the quality may not meet your standards. 

Challenges in AI-generated Pictures

AI-generated pictures are pretty cool but they have some problems that can mess up how good they look or if they're okay to use:

Inaccurate Images: Sometimes, the AI doesn't get what you're asking for and makes the wrong picture. Like, you might want a picture of a beach, but it makes a desert instead. This happens because the AI can't always understand complicated instructions or small details.

Weird Pictures: Another issue is when pictures have things that shouldn't be there, like a person with too many arms or a place that looks all wrong. This happens when the AI gets confused by the information it learned from, especially if it didn't learn from a wide variety of stuff.

Bad Content Pictures: It's important to make sure AI doesn't make pictures that are offensive or not okay. This can happen if the AI learns from stuff on the internet that isn't good. People who make AI are trying to teach it to not make these kinds of pictures.

Too Generic: A lot of times, AI pictures don't have special details and can seem pretty plain. People who work with AI are always trying to make it better at picking up on the little things you ask for in your picture, so it turns out more unique and detailed.


What is the Optimal Setting for Images?

So, what is the key to getting a picture that follows the prompt and is superior in quality?

  • The primary advice that experts give is to steer clear of extreme values.
  • When the value is set to 1, the generated image is far from the prompt expectations. 
  • On the other hand, a value of 20 follows prompt instructions completely, but the picture quality may be subpar.
  • As a rule of thumb, most creators find that setting a value between 7 and 9 gives them results that perfectly balance the prompt text, creativity, and quality.
  •  An image with many minute details may require setting the value from 12  to 16. For more stylized and abstract pictures, a lower value will work.



Striking the Right Balance 

 As a beginner, starting with a lower value on the  Stable Diffusion Guidance Scale and moving up gradually so you can view and choose from the generated images is a good idea. Prompts that allow more creativity require lower values. Gaining mastery over using the scale is a matter of choice and practice. While the SDGS value is pertinent to the quality of the generated visuals, using this tool in harmony with other parameters, such as seed value and the number of iterations, is equally important.  

Below is a generated AI image illustrating the quality of a specific image at different levels on the CFG slider.

Prompt: Portrait of Tom Cruise in red suit, 4k, high-quality



💡Bonus Tips 

  • The increase in value on the SDGS /CFG scale increases contrast and color saturation.
  • Adding more steps to the creation process will likely improve the output quality.
  • Be cautious about copyright issues of image elements used in AI art. 



Diffusion models for Generative AI, like Stable Diffusion, have taken AI image generation to unimagined levels of realism and perfection. Using intuitive tools like the Stable Diffusion Guidance Scale within this diffusion model ensures the user controls all elements of the created images. Finding the optimal setting on the CFG scale may require tweaking and experimentation. This primer on CFG will help you get started with the process. However, you can perfect how

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