Browse Models
The simplest way to self-host MajicMIX Realistic. Launch a dedicated cloud GPU server running Lab Station OS to download and serve the model using any compatible app or framework.
Download model weights for local inference. Must be used with a compatible app, notebook, or codebase. May run slowly, or not work at all, depending on your system resources, particularly GPU(s) and available VRAM.
MajicMIX Realistic is a Stable Diffusion 1.5 derivative that merges KanPiroMix, XSMix, and ChikMix models, optimized for Asian facial features. It uses Dynamic Thresholding for CFG control and works best with Euler samplers. The model excels at facial detail rendering and dark area handling.
MajicMIX Realistic is a Stable Diffusion checkpoint model designed for generating photorealistic images, with particular strength in rendering Asian faces and features. Built upon a Stable Diffusion 1.5 base model and verified by SafeTensor, it represents version 7 in the MajicMIX model family.
The model employs specific recommended parameters for optimal results. Users should utilize Euler a or Euler samplers with 20-40 steps. For high-resolution upscaling, several options are recommended:
When upscaling, users should implement:
The creator strongly advises against using face restoration features, instead recommending the adetailer
tool for facial refinement. Dynamic Thresholding is suggested for CFG control, with a recommended range of 1-20.
The MajicMIX family includes several versions, each with distinct characteristics:
Earlier versions utilized Lora block weighting, which made replication challenging. Newer versions have moved away from this approach to improve consistency and reproducibility.
For best results, recommended positive prompts include:
Best quality, masterpiece, ultra high res, (photorealistic:1.4), 1girl
Negative prompts should incorporate:
ng_deepnegative_v1_75t
badhandv4
The model incorporates elements from several other models: