VACE_Skyreels_V3_R2V_Merge-GGUF

BlackStone-Yu/VACE_Skyreels_V3_R2V_Merge-GGUF

VACE_Skyreels_V3_R2V_Merge-GGUF is a machine learning model from BlackStone-Yu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for gguf.

GGUF quantized versions of Inner-Reflections/VACESkyreelsV3R2VMerge for use with ComfyUI-GGUF.

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Repo size

33.3 GB

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Hugging Face

Repo makeup

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.gguf33.3 GB · 100%

At a glance

Library: gguf
Access: Public
Created: Jul 7, 2026
Updated: Jul 7, 2026
SHA: 8a387a90

Base models

Inner-Reflections/VACE_Skyreels_V3_R2V_Merge

Model card

From the Hugging Face model README

VACE Skyreels V3 R2V Merge — GGUF

GGUF quantized versions of Inner-Reflections/VACE_Skyreels_V3_R2V_Merge for use with ComfyUI-GGUF.

This is a merge of Wan 2.1 VACE with SkyReels V3 R2V by Inner-Reflections, enabling VACE-controlled reference-to-video generation. See the original model card for full details on capabilities and workflows.

Quantizations Available

Filename	Quant Type	Description
`wan-14B_vace_skyreels_v3_R2V_e4m3fn_v1-Q4_K_M.gguf`	Q4_K_M	Smallest, good balance of quality and size
`wan-14B_vace_skyreels_v3_R2V_e4m3fn_v1-Q5_K_M.gguf`	Q5_K_M	Recommended, better quality with moderate size

Usage

Install ComfyUI-GGUF custom nodes
Place the .gguf file in ComfyUI/models/unet/
Use the Unet Loader (GGUF) node in your workflow
For workflows, see the original VACE Skyreels repo and the VACE Phantom repo (same workflows apply)

Conversion Notes

Quantized from the fp8 (e4m3fn) source weights
This is a VACE variant with two 5D tensors (patch_embedding.weight and vace_patch_embedding.weight), which required a modified convert.py to handle correctly
Conversion done using city96/ComfyUI-GGUF tools with a patched handle_nd_tensor method for multi-5D-tensor support

Credits

Original model merge by Inner-Reflections
SkyReels V3 by Skywork
Wan 2.1 VACE by Wan-AI
GGUF conversion tools by city96

Library: gguf
Created: Jul 7, 2026
Updated: Jul 7, 2026