stable-diffusion-docker and docker-stable-diffusion-webui
These are competitors—both provide Docker containerization for Stable Diffusion WebUI, but A offers an extensible all-in-one image with multiple plugins (ControlNet, ComfyUI, etc.), while B prioritizes minimalism and following Docker best practices.
About stable-diffusion-docker
ashleykleynhans/stable-diffusion-docker
Docker image for Stable Diffusion WebUI with ControlNet, After Detailer, Dreambooth, Deforum and ReActor extensions, as well as Kohya_ss and ComfyUI
Bundles A1111 WebUI, Kohya_ss, ComfyUI, and InvokeAI in a single CUDA 12.4 + Python 3.11 container with pre-cached SDXL models and multiple utility extensions (CivitAI Browser, Inpaint Anything, Dynamic Thresholding). Designed for RunPod GPU instances with multi-port exposure (3000-9090) enabling simultaneous access to all four UI frameworks plus Jupyter Lab and code-server for development workflows.
About docker-stable-diffusion-webui
jim60105/docker-stable-diffusion-webui
Dockerfile for stable-diffusion-webui with the goal of keeping it small and follow best practices. (Dockerfile, CI image build)
Optimized for GPU acceleration with NVIDIA CUDA support across Windows (WSL2), Linux, and macOS via the NVIDIA Container Toolkit. Provides pre-built images across multiple upstream versions (AUTOMATIC1111 stable releases, dev branch, and alternative forks like Forge) with automated weekly rebuilds, enabling quick deployment via docker-compose without local compilation. Maintains persistent model and output data in mounted volumes while keeping the entire image footprint to ~10GB through multi-stage build optimization.
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