Getting Started With DreamStudio Website Beta, Part Three: CFG Scale, Steps, and Seeds

21 Aug 202204:54

TLDRIn this informative video, Cal Yuga delves into the advanced features of DreamStudio, focusing on CFG Scale, Steps, and Seeds. He explains how CFG Scale influences the match between the output image and the input text, with higher values leading to more detailed results but potentially overdoing it. Steps determine the number of iterations for image generation, affecting both the quality and resource usage. Seeds allow for consistent image generation from a specific prompt, enabling users to tweak prompts for variations while maintaining the same structure. The video showcases the impact of adjusting these settings on image output, encouraging viewers to experiment and find the optimal balance for their creative projects.


  • 🎨 The CFG scale adjusts how closely the output image matches the input text, with higher values providing more detailed results.
  • 🚀 Increasing the number of steps in the generation process can lead to more refined images but also increases computation time and resource usage.
  • 🔒 Locking the seed allows for the consistent generation of the same image structure across different settings and prompt variations.
  • 🌐 Experimenting with different CFG scales and steps is essential to finding a balance that works best for specific prompts and desired image outcomes.
  • 🔄 Raising the CFG scale too high can result in a 'deep-fried' appearance with pixelated edges and excessive detail.
  • 🌈 Changing the prompt while keeping the seed constant introduces variations in color and shape while maintaining the same underlying image structure.
  • 📈 A higher CFG scale is generally recommended for more complex prompts, with a range of 10 to 14 being a good starting point.
  • ⏱️ The default settings of 50 steps and a CFG scale of 7 are suitable for most prompts, providing a good balance between detail and computation efficiency.
  • 📊 Both CFG scale and steps impact the generation time and resource consumption, so it's important to adjust them strategically.
  • 💡 The combination of locked seed and altered prompts can lead to a variety of creative outputs with similar structures, offering endless possibilities for artistic exploration.

Q & A

  • What is CFG scale in DreamStudio's context and how does it affect image generation?

    -CFG scale in DreamStudio controls how closely the output image matches the text input by the user. Adjusting the CFG scale can vary the adherence of the generated image to the prompt. A default CFG scale is considered effective for most prompts, but for detailed or complex prompts, increasing the CFG scale might be beneficial to capture more nuances as described.

  • What does the term 'steps' refer to in the DreamStudio image generation process?

    -In DreamStudio, 'steps' refers to the number of iterations the model uses to generate or diffuse an image. More steps generally allow for more detail and refinement in the image, though it also increases the generation time and resource use. The default setting is 50 steps, but this can be increased to refine the image further.

  • How does changing the CFG scale and steps settings impact the time and resources needed for image generation?

    -Increasing both the CFG scale and the number of steps in DreamStudio results in longer generation times and higher resource utilization. This is because the model performs more calculations to either adhere more closely to the input text or refine the image in greater detail.

  • What is a 'seed' in the context of image generation with DreamStudio?

    -A seed in DreamStudio acts like a unique code that enables the generation of the same image repeatedly with a specific prompt. This allows for consistency when experimenting with different settings on the same base image.

  • How can one 'lock' a seed and what advantage does this provide?

    -Locking a seed in DreamStudio ensures that the same base image is used when different parameters are modified. This is particularly useful for comparing the effects of changes in CFG scale or steps on a consistent image, allowing for more controlled experimentation.

  • What happens when you increase the number of steps from the default in DreamStudio?

    -Increasing the number of steps from the default in DreamStudio can potentially enhance the image detail and quality as it allows the model more iterations to refine the image. However, the actual impact can vary depending on the complexity of the prompt and other settings like CFG scale.

  • What are the consequences of setting the CFG scale too high?

    -Setting the CFG scale too high in DreamStudio can lead to an over-processed or 'deep fried' image where details may become overly exaggerated and pixelated, often distorting the image rather than enhancing it.

  • Can changing the prompt with a locked seed affect the generated image?

    -Yes, changing the prompt with a locked seed can still affect the generated image in DreamStudio. While the underlying structure remains the same due to the locked seed, alterations in the prompt can introduce variations in themes, colors, and details, providing a different visual vibe.

  • What does a 'deep fried' image mean in this context?

    -A 'deep fried' image in the context of DreamStudio refers to an image that has been overly processed due to high CFG scale settings. This results in extreme detail that can appear pixelated or distorted, losing the natural aesthetics of the image.

  • How can one use the feature of locked seeds to explore different artistic variations?

    -By locking the seed and slightly modifying the prompt, users can experiment with various artistic interpretations of the same fundamental image structure in DreamStudio. This allows for creative variations while maintaining certain base elements consistent, enabling a diverse exploration of artistic ideas.



🎥 Introduction to Dream Studio and CFG Scale

The video begins with Cal Yuga introducing part three of the Dream Studio website beta explainer video series. The focus of this segment is on the CFG scale and steps, which are essential in controlling the output image's similarity to the input text and the image generation process. The default CFG scale is noted to be effective for most purposes, but it can be adjusted for more detailed or complex prompts. The video also mentions the importance of experimenting with these settings to find a personalized system.



💡CFG Scale

CFG Scale, or Context-Free Grammar Scale, is a parameter that controls the degree to which the generated image adheres to the input text provided by the user. A higher CFG Scale value results in an image that more closely matches the textual description, with more detailed and accurate representation. In the video, it is mentioned that the default value is good for most situations, but for more detailed or complex prompts, increasing the CFG Scale can enhance the output. For instance, the video illustrates how increasing the CFG Scale from the default to 11 and then to 14 results in more detailed cloud and landscape features in the generated image.


Steps refer to the number of iterations or stages the AI goes through to generate or diffuse an image. The default number of steps is 50, which works well for initial concept refinement without consuming too much computational resources. However, increasing the number of steps, such as to 100, can result in a more refined image with sharper details, as long as the underlying structure is consistent, which is ensured by locking the seed. The video demonstrates this by using the same seed with different step counts to show the impact on the image's detail and structure.


Seeds in the context of image generation are like unique identifiers or starting points that determine the base structure of the generated image. Locking a seed ensures that the same image can be regenerated consistently with the same prompt. The video explains that while the seed is locked, users can still alter the prompt slightly to produce variations of the image with the same overall structure but with different colors, shapes, or vibes. This allows for creative exploration and manipulation of the generated content without losing the essence of the original concept.

💡Locking Seeds

Locking seeds in the process of image generation means fixing the random starting point to ensure the reproduction of the same image structure every time. This is particularly useful for detailed comparisons and adjustments in the image generation process, as it allows the user to focus on tweaking other parameters like CFG Scale and Steps, confident in the knowledge that the base image structure will remain constant. In the video, the author locks the seed to demonstrate how changes in steps and CFG Scale affect the final image, keeping the overall structure familiar for comparison.

💡Changing Prompts

Changing prompts refers to the act of altering the textual description or command given to the AI to generate an image. While the seed is locked, the user can change the prompt to explore different variations of the same image structure. This can result in images with different colors, shapes, and overall aesthetics, while maintaining the same underlying theme or structure. The video provides an example of changing the prompt from 'dream of a distant galaxy' to 'dream of a distant vaporwave spiral galaxy', showcasing how the essence of the image remains the same, but the vibe changes with the new prompt.

💡Output Image

The output image is the final visual result produced by the AI after processing the input text and parameters like CFG Scale and Steps. It is the tangible representation of the user's prompt and the AI's interpretation of it. In the context of the video, the output image is a critical aspect, as the author experiments with different settings to demonstrate how they affect the quality, detail, and overall appearance of the generated image. The video shows how tweaking the AI's parameters can lead to a more detailed or 'deep-fried' output, depending on the balance between CFG Scale and Steps.

💡Deep Fried Image

A 'deep-fried' image is a term used to describe an output that has been overprocessed, resulting in a loss of quality, often characterized by pixelation or excessive detail that distorts the image. In the video, the author increases the CFG Scale to 20 to illustrate how overdoing the parameters can lead to an image that starts to look 'deep-fried', with pixelated edges and an over-saturated level of detail. This serves as a cautionary example of how important it is to find the right balance when generating images.

💡Resource Usage

Resource usage refers to the computational power and time required to generate an image. As the video explains, increasing the CFG Scale and the number of Steps increases the resource usage, leading to longer generation times. This means that the AI needs more power and time to process the complex instructions and produce a detailed image. The video advises users to be strategic about these settings to balance the quality of the output with the resources available.

💡Stable Diffusion

Stable Diffusion is a term mentioned in the video that refers to a model or method used for generating images. It is likely an AI-based technology that allows for the creation of images from textual prompts. The video discusses how the seed of an image generated by Stable Diffusion remains consistent, allowing for the same image to be regenerated every time with the same prompt. This technology seems to be the basis for the creative exploration and manipulation of image generation discussed in the video.

💡Dream Studio Website Beta

The Dream Studio Website Beta is the platform or tool being discussed in the video. It is a website that allows users to generate images through AI, based on textual prompts. The video is part of an explainer series that delves into the features and parameters of this beta version, aiming to educate users on how to optimize their use of the platform. The author, Cal Yuga, uses this platform to demonstrate the effects of various settings on the image generation process.

💡Image Generation

Image generation is the process of creating visual content using AI technology, as detailed in the video. It involves inputting text prompts and using parameters like CFG Scale and Steps to guide the AI in producing the desired image. The video focuses on the nuances of this process, such as how different settings can impact the quality, detail, and overall appearance of the generated images. Image generation is the core activity explored in the video, with the aim of helping users understand how to use the Dream Studio Website Beta effectively.


CFG Scale controls how closely the output image matches the input text.

The default CFG Scale is 7, but it can be adjusted for more detailed prompts.

Experiment with CFG Scale to find a system that works best for you.

Steps determine how many steps are spent generating or diffusing the image.

The default number of steps is 50, which is generally good for most images.

Increasing both CFG Scale and Steps will increase generation time and resource usage.

Locking the seed allows for consistent image generation for a specific prompt.

With a locked seed, changing the prompt slightly yields variations on the same image structure.

Increasing the number of steps to 100 from 50 can enhance the image detail.

Raising the CFG Scale to 11 introduces more detail and sharper relief in the image.

Too high of a CFG Scale can result in a pixelated or 'deep-fried' image.

Reducing steps can exacerbate the 'deep-fried' effect and introduce artifacts.

Blue nebulous blobs in the image can indicate issues with CFG Scale or Steps.

Changing the prompt while keeping the seed the same produces different themed variations.

Dream Studio and Stable Diffusion offer limitless possibilities for creative image generation.

The video provides a guide for exploring advanced settings in Dream Studio Website Beta.