Provenance
Exact checkpoint
- Creator: KandooAI / RunDiffusion
- Civitai model: Juggernaut XL (133005)
- Civitai version: Jugg_XI_Lightning_by_RD (920957)
- File:
juggernautXL_juggXILightningByRD.safetensors - Size:
7,105,348,616bytes - SHA-256:
609fde646e7fc60a259ad67351e02258ac7929a0a1f5040049dfec6a15f37b1a - Tensor validation: 2,515 tensors; no NaN or Infinity values
Architecture configuration
The checkpoint is a single-file SDXL model. Only architecture configuration and tokenizer assets were taken from the creator reference repository:
- Repository:
RunDiffusion/Juggernaut-XL-Lightning - Revision:
9c35e7ca1112b7e567ae7b24400b83935909916d - Config snapshot manifest SHA-256:
4b05f6a337bcdf1a319054b9ad4493021993aea6d2760c774b7944e865d59481
All learned UNet, VAE, text encoder 1, and text encoder 2 tensors came from the authenticated Civitai checkpoint above. No learned weights were copied from the different checkpoint hosted in the reference repository.
Reproducible conversion
- Apple converter:
apple/ml-stable-diffusion - Converter revision:
e12202c1f6405b83918b58a5d097cd61e3e1f702 - LocalMuse wrappers:
Tools/CoreML/convert_sdxl_unet.pyandTools/CoreML/convert_sdxl_text_encoders.py - Resolution: 1024×1024 (
128×128latent) - UNet: 6-bit palettized,
SPLIT_EINSUM, two chunks - Text encoder 1: FP16
- Text encoder 2: 8-bit palettized
- VAE encoder/decoder: checkpoint-specific FP16 weights
- Minimum target: iOS 17
Conversion parity checks (PSNR): VAE decoder 106.3 dB, VAE encoder 101.5 dB,
FP16 Core ML UNet 47.4 dB, text encoder 1 78.9 dB, text encoder 2 75.4 dB.
All exceeded the 35 dB acceptance threshold. Every compiled component was
loaded sequentially with Core ML using CPU_ONLY after compilation.
Tensor contracts
- UNet input:
[2, 4, 128, 128] - UNet output:
[2, 4, 128, 128] - VAE encoder input:
[1, 3, 1024, 1024] - VAE encoder output:
[1, 8, 128, 128] - VAE decoder input:
[1, 4, 128, 128] - VAE decoder output:
[1, 3, 1024, 1024] - Text encoder token input:
[1, 77]