README.md

---
license: apache-2.0
base_model: Wan-AI/Wan2.2-T2V-A14B-Diffusers
pipeline_tag: text-to-video
library_name: mlx-gen
tags:
- mlx
- mlx-gen
- mflux
- apple-silicon
- 8-bit
- mixed-q8-bf16
- wan
- wan2.2
- video-generation
- text-to-video
- wan-a14b
---
# wan2.2-t2v-a14b-diffusers-8bit

This repository contains mixed q8/BF16 MLX-Gen saved weights for
[`Wan-AI/Wan2.2-T2V-A14B-Diffusers`](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B-Diffusers).
It is designed for local Apple Silicon inference with
[`mlx-gen`](https://github.com/lpalbou/mlx-gen).

It uses the mflux/MLX saved-weight layout with MLX quantization tensors. It is not a Diffusers or Transformers
`from_pretrained()` checkpoint.

## Source Model

Original model: [`Wan-AI/Wan2.2-T2V-A14B-Diffusers`](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B-Diffusers).

This quantized derivative follows the Apache 2.0 license of the source model.

## Quantization

This is a mixed q8/BF16 checkpoint:

- q8 for quantizable Wan transformer block attention and feed-forward linears.
- BF16 for the Wan VAE.
- BF16 for Wan transformer conditioning/output projection linears, the UMT5 text encoder, scheduler metadata, tokenizer files, norms, convolutions, and other non-quantizable parameters.

This mixed policy is used because fully quantizing sensitive Wan A14B paths produced invalid or low-quality video in local validation.

## Validation

Measured on 2026-06-04 with `mlx-gen 0.18.9` on Apple Silicon. The upstream Diffusers source snapshot measured about 118 GiB in the local Hugging Face cache before preparing these packages. The table below reports prepared-package generation from model init through MP4 save and post-save video-health validation.

Validation profile: `384x224`, 33 frames, 12 denoising steps, guidance `4`, guidance-2 `3`, 8 fps, seed `4242`, `--low-ram`.

| Package | Disk | Full-Process Physical Peak | Max RSS | MLX Peak | Total Time | Video Health |
|---|---:|---:|---:|---:|---:|---|
| BF16 package | 64.3 GiB | 33.0 GiB | 31.8 GiB | 27.7 GiB | 152.7 s | 33/33 frames, 384x224, 8 fps, temporal delta 1.3 |
| This mixed q8/BF16 package | 39.7 GiB | 20.7 GiB | 19.5 GiB | 15.5 GiB | 154.8 s | 33/33 frames, 384x224, 8 fps, temporal delta 1.4 |

Compared with the BF16 prepared package at the same validation profile, this mixed q8/BF16 package reduces disk usage by about 38% and full-process physical peak memory by about 37%. Total time was about 1% slower in this run.

Physical peak is Darwin `ri_phys_footprint` sampled for the full process. The validation is intentionally small and repeatable; it is not a claim that every full-size `1280x720`, 81-frame, 40-step job has the same memory or timing profile.

## Usage

```bash
python -m pip install -U mlx-gen

mlxgen download --model AbstractFramework/wan2.2-t2v-a14b-diffusers-8bit

mlxgen generate \
  --model AbstractFramework/wan2.2-t2v-a14b-diffusers-8bit \
  --task text-to-video \
  --prompt "A cinematic scene of a scientist working on agentic AI through the night, monitors glowing, papers shifting in a slow dolly shot." \
  --width 384 \
  --height 224 \
  --frames 33 \
  --steps 12 \
  --guidance 4 \
  --guidance-2 3 \
  --fps 8 \
  --seed 4242 \
  --low-ram \
  --metadata \
  --output video.mp4
```

## Compatibility

Requires `mlx-gen >= 0.18.9`.

Generated with `mlx-gen 0.18.9`.

Use the `mlxgen` command and Python import path for new MLX-Gen projects.

## Attribution

MLX-Gen is based on [mflux](https://github.com/filipstrand/mflux) by Filip Strand and the original mflux contributors.

Quantized and contributed by [@lpalbou](https://huggingface.co/lpalbou).