Dev runs SDXL fine-tune fully on iPhone Neural Engine: 6-bit, 8 steps, offline
NovaDevCodeStudio · reddit · 2026-09-08
A developer converted the SDXL fine-tune Juggernaut XL Lightning to Core ML and got it running entirely on-device on iPhone/iPad's Neural Engine: 768x768, 8 steps, 6-bit palettized, split-einsum, 3 GB one-time download, 6 GB+ RAM required, fully offline (tested in airplane mode), plus InstructPix2Pix img2img and a Real-ESRGAN upscale to 4096.
Key gotchas shared:
- Core ML can't build an execution plan for the SDXL UNet even at 6-bit, so the UNet must be split into two chunks;
- Lightning needs guidance 1.5 with DPM++ at 8 steps, otherwise the default sampler outputs noise.
The author is soliciting feedback on open questions: is 768 enough vs 1024 (big memory/speed cost), whether a 3 GB download is acceptable, and whether the 2-minute iOS Neural Engine compile on first launch is a dealbreaker.
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