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Wan2.1 T2V 14B LightX2V StepCfgDistill VACE GGUF

Developed by QuantStack
The GGUF format converted version of the Wan 2.1 text-to-video model, supporting text-to-video, image-to-video, and video-to-video conversions. It has been quantized to improve operational efficiency.
Downloads 3,634
Release Time : 6/16/2025

Model Overview

This project is a GGUF format converted version based on Wan2.1-T2V-14B-StepDistill-CfgDistill and the Wan2.1-VACE-14B range expansion plugin, which can be used for multimodal video conversion tasks.

Model Features

Multimodal conversion
Supports text-to-video, image-to-video, and video-to-video conversions
Quantization processing
Quantized based on the FP16 model to improve operational efficiency
Strong compatibility
Compatible with ComfyUI and ComfyUI-GGUF custom nodes

Model Capabilities

Text-to-video conversion
Image-to-video conversion
Video-to-video conversion

Use Cases

Video creation
Generate video from text description
Automatically generate corresponding video content based on text description
Generate video clips that match the text description
Convert image to video
Convert static images to dynamic videos
Generate dynamic videos based on the input images
Video style conversion
Convert the input video to a video of a different style
Generate a video with a converted style
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