Table of Contents for What is Stable Diffusion and How Does it Work?:
- What is Stable Diffusion?
- Step-by-step guide for Stable Diffusion
- Pros and Cons of the Stable Diffusion AI Image Generator
- Copyright in AI-Generated Content
- Alternatives to Stable Diffusion?
- Stable Diffusion vs. AI Midjourney
- Conclusion
- FAQ
What is Stable Diffusion?
Stable Diffusion is an AI image generator that creates images from text prompts. The model is being developed within the Stability AI ecosystem and advanced in collaboration with research partners such as LMU Munich/CompVis and Runway. A key component is the open-source LAION-5B dataset.
Read more: Overview of Stable Diffusion 3 - Stable Diffusion 3.5 (Models & Highlights) - CompVis (LMU) - GitHub - LAION-5B (Paper)
Stable Diffusion is freely available: You can use the models, for example, via the Hugging Face Hub or the Diffusers library. For SDXL generation, you can find a good developer guide here: Using SDXL with Diffusers.
How it works in a nutshell: Diffusion models gradually “denoise” their way from latent noise to an image. The prompt, seed, guidance/steps, and, if applicable, reference images guide this process—which is why prompting is so crucial. The official Prompt Guide for SD 3.5 provides a concise introduction.
Models of Stable Diffusion 3.5
The 3.5 family addresses various use cases:
- 3.5 Large – high level of detail, up to ~1 MP output, for quality.
- 3.5 Large Turbo - significantly faster for sketches & variants, slight loss of quality possible.
- 3.5 Medium – a solid balance between speed and quality.
- Official Overview: SD 3.5 – Models.
Step-by-Step Guide to Stable Diffusion
How To Access Stable Diffusion?
Stable Diffusion can be accessed in several ways. You can open the tool as follows:
- Dream Studio: Dream Studio by Stability AI is based on Stable Diffusion and can be used as an image generation tool. This way, you can easily access Stable Diffusion without having to install the software or connect to a third-party provider. The first 100 credits are free.
- Hugging Face Hub: You can also use Stable Diffusion for free via Hugging Face.
- Other third-party providers: There are also other third-party providers, such as Feuerwerk-KI, DeepInfra, Stability AI API, that offer access to Stable Diffusion.
- API-based use: If you are familiar with programming, you can connect the Stable Diffusion API to a software or web service.
- Manual Installation: Alternatively , you can download the software from GitHub and install it on your device.
How Does Stable Diffusion Work?
As you can see, there are several ways to generate images with Stable Diffusion. For this guide, we will show you how to use Stable Diffusion with DreamStudio.
Step 1:
Open Dream Studio.
Step 2:
Click "Try Dream Studio Beta."
Dream Studio Home Page
Step 3:
Register with your email address. You will then automatically receive 100 free credits. To generate more images, you can also pay a fee for a monthly subscription.
Dream Studio's Subscription Models
Step 4:
After registering your e-mail address, you can start generating images. Enter your prompt, i.e. the text command, in the text field provided. You can also specify how many images should be generated and in what ratio.
Text Entry
Step 5:
Important to know: The quality of the prompt is directly related to the quality of the result. The more precisely you phrase your prompt, the more accurate the output you’ll receive. Since not everyone is a gifted prompt engineer, Stability AI has published a prompt guide.
The prompts should be as detailed as possible. However, keep in mind that keywords achieve better results than fully formulated sentences.
Once you've entered your prompt, the tool will provide you with four image variations. You can use these variations to continue working on your project.
Results from Stable Diffusion
AI-generated image by Danthree Studio
Want to dive even deeper? Check out our guide to Midjourney—How It Works , we explain many basic prompt principles that can be applied to SD. And if you’re interested in this career field: Prompt Engineer Explained.
Pros and Cons of the Stable Diffusion AI Image Generator
First of all, it sounds relatively easy to generate usable images with this tool. And it is. You just need to be able to write clear prompts that the tool understands. This way you can generate image material in sufficient resolution for free and with a manageable amount of time.
But this is where the problems begin: The 3D footage is usable, but don't be fooled and think it's outstanding image material. The resolution is good but not excellent. The more specific you want your results to be, the more time-consuming it becomes to generate the material. At a certain point, the time required is no longer manageable.
And then there is still the problem that Stable Diffusion can only create images based on existing content. It is therefore not possible to create something completely new.
The biggest advantages of Stable Diffusion are that the tool is free to use and intuitive.
Benefits at a Glance:
- High control & openness: Can be used locally, fine-grained parameters, custom pipelines; ideal for integrations/automations.
- Good quality for many use cases; broad model/checkpoint ecosystem.
- Cost Control: Often cheaper in person; credits are easy to calculate online.
Disadvantages at a Glance:
- Time required for tuning: Quality depends heavily on prompting, seeds, sampler & fine tuning.
- Prone to errors: Anatomy/details may be partially incorrect; requires revision.
- Legal situation & data origin: Training data is broad - bias & rights must be considered (see LAION paper and legal section).
If you need clearly brand-compliant product visuals (color values, material fidelity, detail macros), there is often no way around a precise 3D pipeline. See 3D product visualization for Home & Living.
Copyright in AI-Generated Content
United States: The U.S. Copyright Office guidelines emphasize that works generated purely by machines are not eligible for protection; what is eligible for protection are recognizable human contributions (concept, selection, arrangement, etc.). A good overview: USCO – Artificial Intelligence and Copyright (Part Two, 2025).
EU/Germany: The author is a natural person; purely AI-generated outputs are not eligible for protection without a human touch (see discussion at WIPO: Authorship and AI). In parallel, the EU AI Act (governance/transparency obligations for GPAI providers, among others) is gradually being applied - overview: European Commission - AI Act.
Stability-Lizenz (kommerzielle Nutzung): Die Community License erlaubt kostenlose kommerzielle Nutzung für Organisationen mit < 1 Mio. USD Jahresumsatz; darüber hinaus Enterprise-Lizenz erforderlich. Details: Stability AI – License Update und Stability AI – License Übersicht.
Practical Tip: For advertising materials and product web stores, we either manually refine AI-generated output or don’t use it at all—instead, we rely on our own CGI assets, including PBR-compliant materials. Examples: 3D Render Studio.
Alternatives to Stable Diffusion
- OpenAI (Images via API) – Real-time image generation using the OpenAI Images API.
- Adobe Firefly - generative images with commercially-safe stock foundation & content credentials: Adobe Firefly.
- Runway Gen-3 - strong on video & style control: Runway - Gen-3.
- Ideogram – great for typography/text in images: Ideogram.
Stable Diffusion vs. AI Midjourney
Midjourney is hosted & curated (Discord/Web), provides very consistent, aesthetic defaults and since V7 (June 2025) e.g. draft mode (faster/cheaper), better text/image understanding and omni reference(-oref, -ow) for consistent persons/objects. Official sources: Midjourney Docs - Parameters - Midjourney - Terms of Service - Uploads/Stealth notes.
Quick Comparison
- Control: SD (local/API) offers maximum control & integration; MJ is faster to good looks, but more closed.
- Privacy/Internal: SD can run on-premises; MJ runs in the cloud and displays content based on the plan or Stealth mode.
- Price/Scalability: Local SD is predictable (hardware + time); MJ is subscription/credit-based.
- Workflow: To ensure brand-consistent product and material accuracy in client projects, we rely on CGI pipelines rather than purely generative techniques—see AI vs. CGI: Differences.
Conclusion
AI image generators are powerful - but for reliable brand assets (correct materials, proportions, series motifs, legal certainty) there is usually no way around high-end CGI. Stable diffusion scores with openness & control, but is prompt and tuning-intensive and must be carefully embedded legally. For campaign assets, store images and animations, we recommend Generative AI where it brings speed - CGI where quality and consistency are crucial.
If you need photorealistic, CI-clean product visuals/animations, talk to us: 3D animations for products - Contact us.
