1 Verified Studios Using Stable Diffusion

Stable Diffusion is the open-source image generation model that studios choose when they need maximum control over their AI-generated imagery. Unlike cloud-based tools like Midjourney or DALL-E, Stable Diffusion can be run locally, fine-tuned on custom datasets, and modified at every level of the generation process. Studios use it for brand-consistent asset generation, style transfer, custom visual systems, and any work where off-the-shelf AI imagery is not specific enough.

Studios gravitate towards Stable Diffusion for its flexibility. They can train custom models on a client's existing brand assets to generate new imagery that matches the established visual language exactly. They can control the generation process at a granular level - adjusting style, composition, colour palette, and detail independently. For studios doing high-volume visual asset production or working with brands that have strict visual guidelines, this level of control is essential.

The workflow differs from other image generation tools because Stable Diffusion requires more technical setup and expertise to use effectively. Studios running it typically have dedicated hardware, custom model configurations, and established workflows for training, generating, and post-processing images. This investment pays off in output that is more consistent, more controllable, and more aligned with specific creative requirements than what cloud-based tools can produce.

When looking at studios that use Stable Diffusion, ask about their infrastructure and fine-tuning process. Studios that run their own models and have experience fine-tuning on custom datasets are demonstrating a level of AI capability that goes well beyond simply prompting a cloud service. This matters if your project requires brand-consistent imagery, specific visual styles, or high-volume asset generation where every image needs to feel cohesive. Stable Diffusion expertise is relatively rare among design studios, so those that have invested in it tend to offer genuinely differentiated visual output.