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 id wan_i2v_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.

SceneWorks/wan2.2-i2v-a14b-mlx

Wan2.2-I2V-A14B — MLX (bf16)

Contents (self-contained, bf16)

Provenance

License

SceneWorks/
wan2.2-i2v-a14b-mlx