Sign up

SceneWorks/wan2.2-t2v-a14b-mlx

🤗 Hugging Face sourcetext-to-videoapache-2.0209 GBsafetensors✓ HF checksums availableupdated today
No torrent yet →

Wan2.2-T2V-A14B — MLX (bf16)

Native MLX (Apple Silicon) conversion of Wan-AI/Wan2.2-T2V-A14B, packaged as a turnkey, self-contained snapshot for the SceneWorks app.

Wan2.2 A14B is a high/low-noise mixture-of-experts text-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

Quantization (Q4/Q8) is applied at load by the engine — these weights are full bf16.

Provenance

  • Source: Wan-AI/Wan2.2-T2V-A14B (Apache-2.0).
  • Converted with: the SceneWorks native Rust MLX converter (mlx-gen-wan, converter id wan_t2v_14b), dtype bfloat16, 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.