Abiray/Wan2.2-LightX2V-260412-4STEP-GGUF
62.6k
๐ฌ Wan2.2 14B I2V Distill LightX2V 4-Step (GGUF)
This repository contains GGUF-quantized versions of the LightX2V Distilled Wan2.2 14B Image-to-Video Model.
By quantizing the ultra-fast 4-step distilled models into the GGUF format, this repository allows for drastically reduced VRAM/RAM requirements while maintaining near real-time, high-performance video generation.
๐ What's Special About This Version?
- โก Ultra-Fast 4-Step Generation: Distillation-accelerated version of Wan2.2 requires only 4 steps instead of the traditional 50+ steps.
- ๐พ VRAM & Memory Efficient: Utilizing GGUF quantizations (from
Q3up toQ8), you can run full 14B parameter models on consumer-grade hardware.
๐ฆ Available GGUF Models
We provide quantizations ranging from heavily compressed (Q3) to near-lossless (Q8) to fit your specific memory and quality requirements. Both High Noise and Low Noise versions are available.
