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Open-weight model · Image to video

WorldCrafter-Fast

by ARC Lab, Tencent TencentARC/WorldCrafter-Fast

WorldCrafter-Fast is an open-weight model for image to video from ARC Lab, Tencent. Its published files total 147.2 GB.

Self-contained weights for WorldCrafter Fast image-to-video, text-to-video, and the interactive image-to-video demo. Use the WorldCrafter inference code and its pinned uv environment. The two transformer branches have independent DMD LoRA and camera adapters.

Parameters—
Context—
Weights147.2 GB
License—
AccessOpen weights
Monthly Downloads—

Model Card

Self-contained weights for WorldCrafter Fast image-to-video, text-to-video, and the interactive image-to-video demo. Use the WorldCrafter inference code and its pinned uv environment. The two transformer branches have independent DMD LoRA and camera adapters. The RepEncoder, text encoder, tokenizer, VAE, and scheduler are included here. No WorldCrafter-Base files are needed for Fast inference. Image-to-video uses five high-noise steps and one low-noise step per chunk. Text-to-video uses four high-noise and eight low-noise steps for the first chunk, then two high-noise and four low-noise steps. Compilation is optional with --enable-compile. inferenceconfig.json resolves shared components…

Excerpt from the card by ARC Lab, Tencent.

Identity and Version

Repository
TencentARC/WorldCrafter-Fast
Publisher
ARC Lab, Tencent
Task
Image to video
Modality
Other
Library
diffusers
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
51320c3eb58a6313ccd6021a1da6d723d53e1a58
First published
2026-09-21
Last updated
2026-09-22

Files and Weights

46 files, 147.2 GB in total. The weights are 23 files totalling 147.2 GB in pth, safetensors.

Weights23 files · 147.2 GB
Configuration17 files · 493.0 KB
Tokenizer3 files · 21.4 MB
Documentation1 file · 1.5 KB
Other1 file · 5.0 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
adapter_high_noise/pytorch_lora_weights.safetensorsWeights2.5 GB e46e41944879
adapter_high_noise/transformer_partial.pthWeights1.1 GB 9785e4e131a5
adapter_low_noise/pytorch_lora_weights.safetensorsWeights2.5 GB a0f2884a8e87
adapter_low_noise/transformer_partial.pthWeights1.1 GB 72e4a61fe7c6
repencoder/model.safetensorsWeights2.5 GB 5e86abf6f1ec
text_encoder/model-00001-of-00005.safetensorsWeights5.0 GB c0ef3a140898
text_encoder/model-00002-of-00005.safetensorsWeights4.9 GB 481c7b2b3977
text_encoder/model-00003-of-00005.safetensorsWeights5.0 GB f93148bcc040
text_encoder/model-00004-of-00005.safetensorsWeights5.0 GB a451792c739c
text_encoder/model-00005-of-00005.safetensorsWeights2.9 GB 7e76e18d2245
transformer_high_noise/diffusion_pytorch_model-00001-of-00006.safetensorsWeights10.0 GB 14ed769fec0e
transformer_high_noise/diffusion_pytorch_model-00002-of-00006.safetensorsWeights9.9 GB ebf49848c399
transformer_high_noise/diffusion_pytorch_model-00003-of-00006.safetensorsWeights9.9 GB df3a5b2638a0
transformer_high_noise/diffusion_pytorch_model-00004-of-00006.safetensorsWeights9.8 GB e7a1ceb71b84
transformer_high_noise/diffusion_pytorch_model-00005-of-00006.safetensorsWeights9.8 GB 0dace3ef6cdf
transformer_high_noise/diffusion_pytorch_model-00006-of-00006.safetensorsWeights7.6 GB 5c232e391954
transformer_low_noise/diffusion_pytorch_model-00001-of-00006.safetensorsWeights10.0 GB 29f1170e1805
transformer_low_noise/diffusion_pytorch_model-00002-of-00006.safetensorsWeights9.9 GB 4dcbc0e907e0
transformer_low_noise/diffusion_pytorch_model-00003-of-00006.safetensorsWeights9.9 GB 2b1babf24fd4
transformer_low_noise/diffusion_pytorch_model-00004-of-00006.safetensorsWeights9.8 GB a45ccb075a03
transformer_low_noise/diffusion_pytorch_model-00005-of-00006.safetensorsWeights9.8 GB af637c31b37a
transformer_low_noise/diffusion_pytorch_model-00006-of-00006.safetensorsWeights7.6 GB be48d3043a9e
vae/diffusion_pytorch_model.safetensorsWeights507.6 MB d6e524b3fffe
adapter_high_noise/dmd_timestep_contract.jsonConfiguration123.8 KB —
adapter_high_noise/repencoder_frozen.jsonConfiguration841 B —
adapter_low_noise/dmd_timestep_contract.jsonConfiguration123.8 KB —
adapter_low_noise/repencoder_frozen.jsonConfiguration841 B —
inference_config.jsonConfiguration419 B —
manifest.jsonConfiguration13.0 KB —
repencoder/config.jsonConfiguration628 B —
repencoder/manifest.jsonConfiguration440 B —
scheduler/scheduler_config.jsonConfiguration546 B —
text_encoder/config.jsonConfiguration853 B —
text_encoder/model.safetensors.index.jsonConfiguration22.5 KB —
tokenizer/special_tokens_map.jsonConfiguration7.1 KB —
transformer_high_noise/config.jsonConfiguration961 B —
transformer_high_noise/diffusion_pytorch_model.safetensors.index.jsonConfiguration97.8 KB —
transformer_low_noise/config.jsonConfiguration961 B —
transformer_low_noise/diffusion_pytorch_model.safetensors.index.jsonConfiguration97.8 KB —
vae/config.jsonConfiguration724 B —
README.mdDocumentation1.5 KB —
SHA256SUMSOther5.0 KB —
.gitattributesRepository1.6 KB —
tokenizer/spiece.modelTokenizer4.5 MB e3909a67b780
tokenizer/tokenizer.jsonTokenizer16.8 MB 20a46ac25674
tokenizer/tokenizer_config.jsonTokenizer61.8 KB —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
147.2 GB
Download from ARC Lab, Tencent

Released by ARC Lab, Tencent through its official repository on Hugging Face.

Built From

  • Described by arXiv:2609.24984

Memory Requirements

PrecisionWeights in memory
As published147.2 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

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