ByteDance SDXL-Lightning β€” Core ML (8-bit)

demo

Generated on-device from this exact Core ML build (4 steps, guidance 0, trailing timestep spacing, 1024x1024, seed 42 β€” 38 s on an M3 Ultra).

Not a style fine-tune β€” a few-step distillation of SDXL base, so it inherits base SDXL's look. Pick it for speed.

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 ByteDance/SDXL-Lightning β€” 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

A girl smiling
Setting Value
Steps 4
Guidance (CFG) 0.0
Size 1024x1024

Guidance must be 0 (CFG disabled) and the scheduler needs trailing timestep spacing. 2-8 steps.

Modifications from the base model

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

Licence

Inherited from the base model: openrail++. 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.

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