license: openrail++
tags:
- mlx
- apple-silicon
- diffusion
- stable-diffusion-xl
- sdxl
- text-to-image
base_model: stabilityai/stable-diffusion-xl-base-1.0
library_name: mlx-gen
pipeline_tag: text-to-image
Stable Diffusion XL base 1.0 — MLX pre-quantized tiers
Pre-quantized, packed-load tiers of
stabilityai/stable-diffusion-xl-base-1.0
for on-device Apple-Silicon inference with SceneWorks / mlx-gen
(the sdxl generator). Each tier is a self-contained diffusers turnkey snapshot (U-Net + both
CLIP text encoders + VAE + tokenizers + scheduler + model_index.json) that loads directly — no
in-app quantization pass, no dense transient.
Dual CLIP-L + OpenCLIP-bigG text encoders, real classifier-free guidance + negative prompt, sdxl-family LoRA support. ~30 steps at guidance 7.0, native 1024×1024.
Tiers
| dir | precision | what's quantized |
|---|---|---|
q4/ (default) |
group-wise affine Q4, group size 64 | U-Net Linears + both CLIP encoders |
q8/ |
group-wise affine Q8, group size 64 | U-Net Linears + both CLIP encoders |
bf16/ |
dense (full-precision master) | nothing — verbatim source mirror |
The VAE stays dense (f32) in every tier (the SDXL VAE is int8/fp16-unstable). Convolutions,
GroupNorms, and the CLIP token/position embeddings also stay dense; only the true Linear projections
are packed. Quantization is byte-identical to mlx-gen's load-time nn.quantize (bf16 cast, group
64).
Usage
use mlx_gen::{LoadSpec, WeightsSource, Quant};
let spec = LoadSpec::new(WeightsSource::Dir("…/sdxl-base-mlx/q4".into())).with_quant(Quant::Q4);
let g = mlx_gen::load("sdxl", &spec)?;
License
openrail++ (CreativeML Open RAIL++-M) — inherited from the source model
stabilityai/stable-diffusion-xl-base-1.0. See LICENSE.