coreml-juggernaut-xl-v9-8bit

Juggernaut XL v9 — Core ML (8-bit)

_{Reference image for this model. Curated from the model's own examples — not generated from this Core ML build; quantized output may differ slightly.}

Photorealism — photography, cinematic scenes and portraits.

Core ML conversion for Apple silicon (iOS / iPadOS / macOS, Neural Engine), built with Apple's ml-stable-diffusion for mindfire-image.

Original model

Converted from RunDiffusion/Juggernaut-XL-v9 — go there for the original weights, full model card and licence.

Demo prompt

The prompt and settings used for this model's demo image (also the reference example shipped in mindfire-image):

Prompt

Cinematic mid shot photo of an astronaut walking through a neon-lit Tokyo alley at night, hyperdetailed photography, skin details, shallow depth of field

Documented ranges: 30-40 steps, CFG 3-7. The model card advises starting with no negative prompt.

Modifications from the base model

Converted from PyTorch/diffusers to Core ML (.mlmodelc) and quantized to 8-bit palettized weights. No fine-tuning — behaviour tracks the base model, though quantization can shift outputs slightly.

Licence

Inherited from the base model: creativeml-openrail-m. This carries the OpenRAIL use-based restrictions (Attachment A), which bind you as a downstream user of this conversion exactly as they do for the base model. Read the base model's licence before use or redistribution.