---
license: openrail++
base_model: SG161222/RealVisXL_V5.0_Lightning
library_name: coreml
tags:
- coreml
- stable-diffusion-xl
- text-to-image
- image-to-image
- ios
- localmuse
---

# RealVisXL V5.0 Lightning — exact-source 6-bit split Core ML

Self-contained SDXL package prepared for on-device use by the LocalMuse iOS
app. Unlike the previous LocalMuse artifact, every learned component in this
revision comes from the same pinned RealVisXL snapshot: UNet, both text
encoders, VAE encoder and VAE decoder. The tokenizer files are also copied
from that snapshot.

## Authenticated source

- Repository: `SG161222/RealVisXL_V5.0_Lightning`
- Revision: `f4454158cedaab9f0688c199561d6c92525f3a85`
- Snapshot manifest SHA-256: `b82b09421cb3cf593f0f57e3a3fa5858ec75409f2830e779f0184efb735d33ee`
- Civitai/Hugging Face fp16 checkpoint SHA-256: `fabcadd9330dcc4f9702063428d40b9d4d07168d8acefc819b8d1d9db466b3ec`
- UNet fp16 SHA-256: `1143cd2aaf65d24af34b5699d090aed724f6c0978c2ec5a5f56821ccb36260ce`
- TextEncoder fp16 SHA-256: `0a873801e35a008b17e228189a83a8b41e068ffe7bde7c1105e8c6e947758bc5`
- TextEncoder2 fp16 SHA-256: `dfa429b268cd3f6297927f1fd3eacac04781b17ab4caa97892a461ff41400a5e`
- VAE fp16 SHA-256: `6353737672c94b96174cb590f711eac6edf2fcce5b6e91aa9d73c5adc589ee48`
- License: CreativeML Open RAIL++-M (`LICENSE.md`)

The source checkpoint hash is identical to Civitai RealVisXL V5.0 Lightning
(BakedVAE), model version `798204`. No checkpoint merge or component
substitution is performed by this conversion.

## Conversion

- Apple converter revision: `e12202c1f6405b83918b58a5d097cd61e3e1f702`
- PyTorch `2.4.0`, coremltools `8.0`, Diffusers `0.30.2`
- Fixed resolution: `1024 × 1024` (`128 × 128` latent)
- Classifier-free-guidance UNet batch: `2`
- Attention: `SPLIT_EINSUM`
- UNet: 6-bit palettized, then split into two chunks below 1 GiB
- CLIP-L TextEncoder: FP16
- OpenCLIP-bigG TextEncoder2: 8-bit palettized
- VAE encoder and decoder: converted from the pinned RealVisXL VAE
- Minimum deployment target: iOS 17

## Author-aligned runtime profile

- Sampler: DPM++ SDE Karras (single-step SDE with midpoint evaluation)
- Steps: `5` by default; `4–6` recommended
- CFG: `2.0` by default; `1.0–2.0` recommended
- Native generation: `1024 × 1024`

Five requested scheduler steps execute nine UNet evaluations. This is not the
ordinary DPM-Solver++ multistep scheduler and not DPM++ 2M SDE.

The author's reference images may include a separate Hi-Res pass. That pass is
not baked into these model files and must be implemented by the client when
enabled.

## Validation

- VAE decoder parity: `106.3 dB`
- VAE encoder parity: `101.5 dB`
- TextEncoder parity: `81.1 dB`
- TextEncoder2 parity before 8-bit storage conversion: `55.2 dB`
- UNet Core ML parity before 6-bit storage conversion: `45.7 dB`
- Compiled contracts: UNet `[2, 4, 128, 128] → [2, 4, 128, 128]`, VAE
  `1024 × 1024`, both text encoders `77` tokens
- Every compiled component loads successfully through Core ML on macOS with
  CPU-only compute. Final Neural Engine quality, memory and thermal validation
  must be performed on a supported 8 GiB iPhone before release.