This GGUF file is a direct conversion of Wan-AI/Wan2.2-T2V-A14B Since this is a quantized model, all original licensing terms and usage restrictions remain in effect. Usage The model can be used with the ComfyUI custom node ComfyUI-GGUF by city96 Place model files in ComfyUI/models/unet see the GitHub readme for further installation instructions.
Open-weight model · Text to video
Wan2.1_14B_VACE-GGUF
by QuantStack QuantStack/Wan2.1_14B_VACE-GGUF
Example workflow - based on the Comfyui example workflow This is a direct GGUF conversion of Wan-AI/Wan2.1-VACE-14B All quants are created from the FP32 base file, though I only uploaded the Q80 and less, if you want the F16 or BF16 one I would upload it per…
Parameters—
Context—
Weights205.2 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads27.7k
Model Card
By QuantStack, published under apache-2.0, revision 18432c8dcafd.
Example workflow - based on the Comfyui example workflow This is a direct GGUF conversion of Wan-AI/Wan2.1-VACE-14B All quants are created from the FP32 base file, though I only uploaded the Q80 and less, if you want the F16 or BF16 one I would upload it per request. The model files can be used with the ComfyUI-GGUF custom node. Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions. The VAE can be downloaded from here Please refer to this chart for a basic overview of quantization types. For conversion I used the conversion scripts from city96
Read QuantStack's full model card
Example workflow - based on the Comfyui example workflow
This is a direct GGUF conversion of Wan-AI/Wan2.1-VACE-14B
All quants are created from the FP32 base file, though I only uploaded the Q8_0 and less, if you want the F16 or BF16 one I would upload it per request.
The model files can be used with the ComfyUI-GGUF custom node.
Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions.
The VAE can be downloaded from here
Please refer to this chart for a basic overview of quantization types.
For conversion I used the conversion scripts from city96
Identity and Version
- Repository
- QuantStack/Wan2.1_14B_VACE-GGUF
- Publisher
- QuantStack
- Task
- Text to video
- Modality
- Video
- Library
- gguf
- Parameters
- Not stated by the source
- Languages
- Not stated by the source
- Revision
- 18432c8dcafd3170bc92ba933510b3bad440f3fe
- First published
- 2025-05-16
- Last updated
- 2025-06-11
Files and Weights
16 files, 205.2 GB in total. The weights are 13 files totalling 205.2 GB in gguf.
Weights13 files · 205.2 GB
Configuration1 file · 36.4 KB
Documentation1 file · 1.3 KB
Repository1 file · 3.1 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| Wan2.1_14B_VACE-BF16.gguf | Weights | 34.7 GB | a3ac1560db8f |
| Wan2.1_14B_VACE-F16.gguf | Weights | 34.7 GB | 7121c7704b96 |
| Wan2.1_14B_VACE-Q3_K_S.gguf | Weights | 7.8 GB | 94498ff3fc96 |
| Wan2.1_14B_VACE-Q4_0.gguf | Weights | 10.3 GB | 6760c57d558a |
| Wan2.1_14B_VACE-Q4_1.gguf | Weights | 11.2 GB | 311c277f5e8f |
| Wan2.1_14B_VACE-Q4_K_M.gguf | Weights | 11.6 GB | d03b2280e996 |
| Wan2.1_14B_VACE-Q4_K_S.gguf | Weights | 10.6 GB | 4ffac58131d2 |
| Wan2.1_14B_VACE-Q5_0.gguf | Weights | 12.5 GB | fc18b8a15cc3 |
| Wan2.1_14B_VACE-Q5_1.gguf | Weights | 13.3 GB | 076947ac74c3 |
| Wan2.1_14B_VACE-Q5_K_M.gguf | Weights | 13.0 GB | 40dc6bf86a8b |
| Wan2.1_14B_VACE-Q5_K_S.gguf | Weights | 12.3 GB | 66dde54e0e74 |
| Wan2.1_14B_VACE-Q6_K.gguf | Weights | 14.5 GB | 2d7b6937bfeb |
| Wan2.1_14B_VACE-Q8_0.gguf | Weights | 18.7 GB | 3c5e7ff7718e |
| vace_v2v_example_workflow.json | Configuration | 36.4 KB | — |
| README.md | Documentation | 1.3 KB | — |
| .gitattributes | Repository | 3.1 KB | — |
License and Download
- License
- apache-2.0
- Access
- Open weights, no gate
- Download size
- 205.2 GB
Download from QuantStack
Released by QuantStack through its official repository on Hugging Face. Read the license.
Built From
- Derived from Wan-AI/Wan2.1-VACE-14B
- Quantized from Wan-AI/Wan2.1-VACE-14B
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 205.2 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About Wan2.1_14B_VACE-GGUF
Can I use Wan2.1_14B_VACE-GGUF commercially?
Yes. Wan2.1_14B_VACE-GGUF is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
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