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license: mit
library_name: mlx
tags:
- text-to-image
- image-to-image
- mlx
- quantized
base_model: microsoft/Mage-Flow-Base
---
# Mage-Flow — shared components (MLX, per-tier)
The **Qwen3-VL-4B text encoder** and **Mage-VAE** shared by every
[Mage-Flow](https://huggingface.co/microsoft/Mage-Flow) variant, re-hosted for
[SceneWorks](https://github.com/SceneWorks/SceneWorks) as physically distinct MLX quantization tiers.
## Why this repo exists
Microsoft publishes six Mage-Flow checkpoints (`Base`, RL, `Turbo`, and the three `Edit` twins). The
text encoder (8.875 GB) and VAE (0.345 GB) are **bit-identical across all six** — only the 8.232 GB
DiT differs. Mirroring each variant as a complete snapshot would cost **105.04 GB** for a full
install. Hosting the shared components once here, and only the per-tier DiT in each variant mirror,
brings that to **58.65 GB**, and makes a second variant an ~8.2 GB delta rather than another 17.5 GB.
## Layout
Each tier directory is self-contained:
```
<tier>/text_encoder/ Qwen3-VL-4B — config, tokenizer/processor assets, model.safetensors
<tier>/vae/ Mage-VAE
```
| tier | text_encoder | vae | total |
|---|---|---|---|
| `bf16` | 8.876 GB | 0.345 GB | 9.232 GB |
| `q8` | 4.720 GB | 0.345 GB | 5.076 GB |
| `q4` | 2.503 GB | 0.345 GB | 2.860 GB |
**The VAE is dense in every tier, deliberately.** 59 of its 60 quantizable 2-D weights are
`adaLN_modulation` projections that the decoder *folds away at load* (adaLN depends only on `t`, and
the one-step decode always runs `t = 0`). Packing them on disk would fold quantized codes and
silently corrupt the decode. The disk cost of that correctness is ~0 — the VAE is conv-dominated, and
the comparable Z-Image VAE shrinks only 1.8% under q4.
Quantization is MLX `q4`/`q8` at group size 64, packed with the same
`mlx_rs::ops::quantize(bf16, 64)` call the load-time path uses — a pre-quantized tier is
**bit-identical** to quantizing the dense weights at load.
## Provenance
Converted from `microsoft/Mage-Flow-Base` at revision
`59a9cfd58cf6ecef28245852c6bdace3f12428a2` with
[`mlx-gen-mage`](https://github.com/SceneWorks/inference)'s `examples/mage_prequant.rs`. The text
encoder and VAE tensors are identical in all six upstream repos, so the choice of source variant is
immaterial.
Upstream: [microsoft/Mage](https://github.com/microsoft/Mage) · arXiv:2607.19064 · MIT.
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