Wan 2.2 T2V A14B Diffusers BF16
This repository contains BF16 MLX-Gen saved weights for Wan-AI/Wan2.2-T2V-A14B-Diffusers. It is designed for local Apple Silicon inference with mlx-gen.
Source du modèle
- Type
- Other
- Taille du fichier
- 242 MB–4,64 GB
- Modèle de base
- Wan-AI/Wan2.2-T2V-A14B-Diffusers
- Version
- vRevision 2061f00
- Mis à jour
- 3 nov. 2026
- Téléchargements
- 0
- Source
- Hugging Face
Description de la source
wan2.2-t2v-a14b-diffusers-bf16
This repository contains BF16 MLX-Gen saved weights for
Wan-AI/Wan2.2-T2V-A14B-Diffusers.
It is designed for local Apple Silicon inference with
mlx-gen.
It uses the mflux/MLX saved-weight layout. It is not a Diffusers or Transformers
from_pretrained() checkpoint.
Source Model
Original model: Wan-AI/Wan2.2-T2V-A14B-Diffusers.
This prepared derivative follows the Apache 2.0 license of the source model.
Precision
This package stores the Wan A14B T2V transformer and VAE weights for MLX-Gen BF16 runtime use. The UMT5 text encoder, scheduler metadata, tokenizer files, and model index are included in the prepared folder.
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 |
|---|---|---|---|---|---|---|
| This 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 |
| 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 |
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
python -m pip install -U mlx-gen
mlxgen download --model AbstractFramework/wan2.2-t2v-a14b-diffusers-bf16
mlxgen generate \
--model AbstractFramework/wan2.2-t2v-a14b-diffusers-bf16 \
--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 by Filip Strand and the original mflux contributors.
Prepared and contributed by @lpalbou.
Sources
1 source
Sources
1 sourceVérifié 3 nov.
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text_encoder · 3 weight files
All files listed in the provider index are present.
- text_encoder/model.safetensors.index.json · provider index
- text_encoder/config.json
- text_encoder/model-00001-of-00003.safetensors · individual shard
- text_encoder/model-00002-of-00003.safetensors · individual shard
- text_encoder/model-00003-of-00003.safetensors · individual shard
transformer · 14 weight files
All files listed in the provider index are present.
- transformer/model.safetensors.index.json · provider index
- transformer/0.safetensors · individual shard
- transformer/1.safetensors · individual shard
- transformer/2.safetensors · individual shard
- transformer/3.safetensors · individual shard
- transformer/4.safetensors · individual shard
- transformer/5.safetensors · individual shard
- transformer/6.safetensors · individual shard
- transformer/7.safetensors · individual shard
- transformer/8.safetensors · individual shard
- transformer/9.safetensors · individual shard
- transformer/10.safetensors · individual shard
- transformer/11.safetensors · individual shard
- transformer/12.safetensors · individual shard
- transformer/13.safetensors · individual shard
transformer_2 · 14 weight files
All files listed in the provider index are present.
- transformer_2/model.safetensors.index.json · provider index
- transformer_2/0.safetensors · individual shard
- transformer_2/1.safetensors · individual shard
- transformer_2/2.safetensors · individual shard
- transformer_2/3.safetensors · individual shard
- transformer_2/4.safetensors · individual shard
- transformer_2/5.safetensors · individual shard
- transformer_2/6.safetensors · individual shard
- transformer_2/7.safetensors · individual shard
- transformer_2/8.safetensors · individual shard
- transformer_2/9.safetensors · individual shard
- transformer_2/10.safetensors · individual shard
- transformer_2/11.safetensors · individual shard
- transformer_2/12.safetensors · individual shard
- transformer_2/13.safetensors · individual shard
vae · 1 weight files
All files listed in the provider index are present.
- vae/model.safetensors.index.json · provider index
- vae/0.safetensors · individual shard
Repository files
File inventory only; completeness is unverified.
Artefacts du modèle
32 artefacts
Artefacts du modèle
32 artefactstext_encoder/model-00001-of-00003.safetensors
safetensors · 4,60 GB · SHA-256 a8e861969c74…8f58 · Hugging Face
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safetensors · 4,64 GB · SHA-256 d57d948ece48…02d7 · Hugging Face
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safetensors · 1,34 GB · SHA-256 0da9ee284e21…7c5f · Hugging Face
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safetensors · 1,99 GB · SHA-256 f9ee806421df…7e92 · Hugging Face
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safetensors · 1,96 GB · SHA-256 eb55633aaeb2…f158 · Hugging Face
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safetensors · 1,96 GB · SHA-256 94b781cf8b59…c5ab · Hugging Face
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safetensors · 1,96 GB · SHA-256 f437bf829039…7013 · Hugging Face
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safetensors · 1,96 GB · SHA-256 8fe482282a1d…306a · Hugging Face
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safetensors · 1,07 GB · SHA-256 1b45445e9600…5700 · Hugging Face
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safetensors · 1,96 GB · SHA-256 e11c8e7cadae…0bcb · Hugging Face
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safetensors · 1,96 GB · SHA-256 1abc8a6e026c…e807 · Hugging Face
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safetensors · 1,96 GB · SHA-256 d5a43ede6ddb…b5c0 · Hugging Face
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safetensors · 1,96 GB · SHA-256 e658e5e45271…7617 · Hugging Face
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safetensors · 1,96 GB · SHA-256 93cebfd35a90…054a · Hugging Face
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safetensors · 1,96 GB · SHA-256 3d73d1cbb1ac…73c7 · Hugging Face
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safetensors · 1,96 GB · SHA-256 3b1b5339b411…0db2 · Hugging Face
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safetensors · 1,96 GB · SHA-256 f8a23cc15756…28f6 · Hugging Face
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safetensors · MIXED (unverified) · 1,99 GB · SHA-256 077956a53e07…3fea · Hugging Face
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safetensors · BF16 (unverified) · 1,96 GB · SHA-256 03d004b2dae0…2ae6 · Hugging Face
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safetensors · 1,96 GB · SHA-256 9357ebc9ab1a…6b52 · Hugging Face
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safetensors · 1,96 GB · SHA-256 1323c2e22d6f…f8b3 · Hugging Face
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safetensors · 1,96 GB · SHA-256 07c337852a24…5bd8 · Hugging Face
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safetensors · 1,07 GB · SHA-256 72b0a3b4542e…9772 · Hugging Face
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safetensors · 1,96 GB · SHA-256 c3560d3937a7…e5ba · Hugging Face
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safetensors · 1,96 GB · SHA-256 10e2f5e5243f…32c6 · Hugging Face
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safetensors · 1,96 GB · SHA-256 d0517b2b5bdc…a5ae · Hugging Face
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safetensors · 1,96 GB · SHA-256 4abb152a6668…9de3 · Hugging Face
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safetensors · 1,96 GB · SHA-256 b36b0e4c7067…a717 · Hugging Face
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safetensors · 1,96 GB · SHA-256 730b11f1d1cf…b9b4 · Hugging Face
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safetensors · 1,96 GB · SHA-256 4d3ddbe5a34b…3158 · Hugging Face
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safetensors · 1,96 GB · SHA-256 a9b6614e8094…13ec · Hugging Face
Download fileExtraits de sources
2 extraits
Extraits de sources
2 extraits--- 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 - bf16 - wan - wan2.2 - video-generation - text-to-video - wan-a14b --- # wan2.2-t2v-a14b-diffusers-bf16 This repository contains 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. 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 prepared derivative follows the Apache 2.0 license of the source model. ## Precision This package stores the Wan A14B T2V transformer and VAE weights for MLX-Gen BF16 runtime use. The UMT5 text encoder, scheduler metadata, tokenizer files, and model index are included in the prepared folder. ## 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 | |---|---:|---:|---:|---:|---:|---| | This 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 | | 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 | 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-bf16 mlxgen generate \ --model AbstractFramework/wan2.2-t2v-a14b-diffusers-bf16 \ --task text-to-video \ --prompt "...
Source context: 0 downloads · 0 likes · Pipeline text-to-video · Library mlx-gen · Repo AbstractFramework/wan2.2-t2v-a14b-diffusers-bf16
