The weights being open is the part that matters operationally. The model runs on your own hardware, the images never leave it, there is no per-image fee, and the whole generation graph can be pinned so that a result produced today can be reproduced next year — none of which is true of a hosted API.
That is also what makes a consistent house style achievable. Combined with a trained adapter and a fixed pipeline, the same look can be held across hundreds of assets, which is the actual requirement in commercial work and the thing prompting alone never quite delivers.
Related terms
LoRA (low-rank adaptation)
A way of fine-tuning that trains a small add-on layer instead of the whole model, producing a file of a few megabytes rather than a few gigabytes.
Fine-tuning
Continuing to train an existing model on your own examples, so it adopts a behaviour or a style it did not have.
ComfyUI
A node-based interface for image generation, where the pipeline is an explicit graph rather than a text box with hidden defaults.
The bench this belongs to
Generative AIStable Diffusion and ComfyUI wired into the place where your content actually gets made, with a model fine-tuned so everything comes out looking like you.
