Wan2.2-I2V-A14B — MLX (bf16)
Native MLX (Apple Silicon) conversion of Wan-AI/Wan2.2-I2V-A14B, packaged as a turnkey, self-contained snapshot for the SceneWorks app. Downloading this repo replaces the previous "download the native checkpoint and convert on-device" first-run step.
Wan2.2 A14B is a high/low-noise mixture-of-experts image-to-video model — two transformers switched at the noise boundary.
Contents (self-contained, bf16)
| file | what |
|---|---|
high_noise_model.safetensors |
high-noise expert DiT (~28.6 GB) |
low_noise_model.safetensors |
low-noise expert DiT (~28.6 GB) |
t5_encoder.safetensors |
UMT5-XXL text encoder (~11.4 GB) |
vae.safetensors |
Wan z16 VAE |
tokenizer.json |
UMT5 tokenizer |
config.json |
architecture config (dual_model: true, in_dim: 36 image-concat) |
Quantization (Q4/Q8) is applied at load by the engine — these weights are full bf16.
Provenance
- Source:
Wan-AI/Wan2.2-I2V-A14B(Apache-2.0). - Converted with: the SceneWorks native Rust MLX converter (
mlx-gen-wan, converter idwan_i2v_14b), dtypebfloat16, dense (no baked-in quant). - Lean snapshot — only the files the MLX engine loads.
License
Apache-2.0, inherited from the upstream model. This repository redistributes a converted copy of the upstream Apache-2.0 weights, with attribution, as permitted by that license. See the source model card.