---
license: apache-2.0
language:
- en
pipeline_tag: text-to-image
library_name: mlx
tags:
- mlx
- apple-silicon
- diffusion
- z-image
- text-to-image
- quantized
base_model: Tongyi-MAI/Z-Image
---

# Z-Image — MLX quant-matrix (SceneWorks re-host)

Pre-built **MLX** (Apple Silicon) quantization tiers of [`Tongyi-MAI/Z-Image`](https://huggingface.co/Tongyi-MAI/Z-Image), hosted by [SceneWorks](https://github.com/SceneWorks) for direct, ready-to-run loading in the SceneWorks desktop app (no install-time conversion, no gated download).

## Tiers

Each subdirectory is a complete, self-contained snapshot (transformer + Qwen3 text encoder + VAE + tokenizer + scheduler) that the SceneWorks `z_image` engine loads directly:

| Tier | Subdir | Precision | Use |
|------|--------|-----------|-----|
| Q4 (default) | `q4/` | 4-bit group-affine (group 64) weights; dense norms | smallest footprint (undistilled base, real CFG) |
| Q8 | `q8/` | 8-bit group-affine weights | higher fidelity |
| bf16 | `bf16/` | dense bf16 | maximum fidelity |

The transformer, text encoder, and VAE attention are quantized in the Q4/Q8 tiers; the bf16 tier is the full dense model. The packed weights auto-detect their quantization on load (no manifest needed).

## License

Apache-2.0, inherited from the upstream `Tongyi-MAI/Z-Image`. This is an unmodified-weights re-host (re-quantized for MLX). All credit to the Tongyi-MAI team.