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How to use stable diffusion? AI-Generated Images

How to use stable diffusion? AI-Generated Images

Product design
8 min read

A designer unfamiliar with at least one AI tool is more of an exception than a rule. So, understanding how to use Stable Diffusion AI – an artificial intelligence tool able to create images – is a must-have. The more you know about various tools, the more efficiently and swiftly you can employ them.

At Arounda, a design agency with over seven years of experience, we've witnessed how the rise of generative artificial intelligence has transformed the game in our industry. We regularly incorporate AI into our work, enhancing our thinking and decision-making and increasing productivity.

This article closely examines the essential aspects of using Stable Diffusion. We've compiled key information to assist you in getting started with this tool. Join us as we unravel these details together!

Stable Diffusion: What It Is and How It Works?

Stable Diffusion is a generative model falling under the broader category of diffusion models, designed explicitly for unsupervised learning and pattern recognition. As a generative model, it autonomously identifies and learns patterns from input data, creating new instances resembling those in the original dataset. 

The term "diffusion" in Stable Diffusion stems from its mathematical formulation, mirroring the concept of diffusion in physics. This model initiates the generation process with a simple distribution, gradually transforming it through controlled diffusion steps. 

The training phase involves optimizing the model to minimize the difference between the generated and actual data distribution, typically using maximum likelihood estimation. Once trained, Stable Diffusion can generate new samples by iteratively applying the learned diffusion process. 

The "Stable" aspect signifies the careful control and stability of the diffusion transformations. Notably, the diffusion process is reversible, allowing the model to move backward from a sample in the complex distribution to the simple initial distribution. 

Benefits of Stable Diffusion

The Stable Diffusion model offers several advantages, making it a compelling choice, especially compared to similar AI in graphic design


One of the significant advantages of Stable Diffusion is its open-source nature. Being open-source means the model's architecture, code, and associated tools are available for public access and modification. 

It encourages collaboration, transparency, and community development around the model. Many enthusiasts have contributed to improving Stable Diffusion by creating free tools and models, fostering a collaborative and evolving ecosystem.

Designed for Low-Power Computers

Stable Diffusion is optimized for efficient performance on low-power computers. This design consideration makes it a cost-effective and accessible solution for users with limited computational resources. 

By being free or inexpensive to run, Stable Diffusion addresses the practical constraints associated with deploying and utilizing sophisticated AI models, making it more widely applicable and inclusive.

What Does Stable Diffusion Cost?

Stable Diffusion operates open-source and free-to-use, providing accessibility to a broad user base. Nevertheless, monthly subscription plans are available for developers and businesses seeking enhanced features. These plans offer additional capabilities, reflecting Stable Diffusion's commitment to catering to diverse user needs.

The platform offers a variety of APIs carefully crafted to empower a broad spectrum of applications. Engineered for user-friendly interaction, these APIs tap into the full potential of Stable Diffusion's AI capabilities. To optimize how to use Stable Diffusion APIs, users may explore and understand the available subscription plans

Stable Diffusion How to Use

For users new to Stable Diffusion, we recommend initiating your exploration with the fundamental features to build a robust foundation. Begin by delving into the essential text-to-image and image-to-image transformations. These core functionalities serve as the cornerstone for comprehending Stable Diffusion's capabilities.

As a first step, familiarize yourself with the full spectrum of functionalities available. This initial phase ensures a gradual and thorough introduction to the tool's potential, paving the way for a more in-depth understanding of its capabilities.

Text-to-Image Generation

Stable Diffusion introduces a significant advancement in text-to-image model generation, providing users with a versatile tool for creative image creation. The application involves generating images based on textual prompts. 

Users can achieve various effects by adjusting the seed number for the random generator or modifying the denoising schedule. This flexibility allows for the creation of diverse images, offering a powerful avenue for artistic expression.

Image-to-Image Generation

Stable Diffusion extends its capabilities to image-to-image generation, enabling users to create images based on an input image and a text prompt. 

For instance, users can input a sketch and an appropriate prompt to generate images that evolve from the characteristics of the initial sketch. This functionality proves helpful in scenarios where users seek to derive images guided by specific prompts and existing visual elements.

Creation of Graphics, Artwork, and Logos

Stable Diffusion stands out in its ability to facilitate the creation of graphics, artwork, and logos in various styles. Users can explore a broad spectrum of artistic expressions by using a selection of prompts. 

While the output may not be predetermined, users can guide the logo creation process by incorporating a sketch or other guiding elements. This feature enhances the tool's applicability in creative design scenarios.

Image Editing and Retouching

Stable Diffusion extends its utility to image editing and retouching, offering an AI Editor feature. Users can load an image, employ an eraser brush to mask specific areas for editing, and generate prompts that define desired changes. 

This functionality enables users to repair old photos, remove objects, alter subject features, and introduce new elements into an image. The tool proves invaluable in enhancing and refining visual content.

Video Creation

Stable Diffusion showcases its versatility in video creation by supporting the generation of short video clips and animations. Some tools can harness Stable Diffusion's capabilities for adding different styles to a movie. 

Additionally, users can animate photos to create impressions of motion, such as simulating flowing water. This feature expands Stable Diffusion's applications into the dynamic realm of video content creation.


There is a wide range of possibilities for how to use stable diffusion AI. It is open to users with different requirements, capabilities, and financial plans. Thanks to its open-source nature, It caters to individual users and enterprises, making it adaptable to various needs.

At Arounda, we leverage the latest technologies and trends to ensure our client's designs are always up to date.

Stay up to date with the latest trends and build collaboration with progressive partners. Contact us, and let's collaborate on your projects using top-notch technologies.


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What is Stable Diffusion?

Stable Diffusion is an advanced deep learning model developed by Stability AI, a tech startup.Categorized as a generative model in deep learning, Stable Diffusion is designed to create new data resembling what it has learned. A distinctive feature of Stable Diffusion is its capability to run locally on personal computers, setting it apart from other AI image generators that typically operate in the cloud. It allows users to generate numerous images directly on their own machines.

How to use Stable Diffusion locally?

Before using Stable Diffusion, have Python and Git installed on your machine. Clone the Stable Diffusion repository in your preferred directory. Download and extract the latest Stable Diffusion model to a chosen location. Set up the Web UI by navigating to the cloned repository directory and installing the necessary Python packages. Then, run Stable Diffusion by starting the Web-UI with python Access it through a web browser.

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