Update 08/08/2025 There was an error in the link I shared for the Lighting 2.2 I2V LoRA by Kijai. I’ve just fixed it so you can download it now. --------- Update 07/08/2025 What I’ll say next is my personal opinion — I could be wrong — but based on the few tests I’ve done, this is my conclusion. The more steps you use, the lower the strength you should assign to the lighting LoRAs. For example, I believe that for 6+6 or 7+7 steps, a strength of 1.0 is appropriate. I think different configurations not only affect generation speed but also the movement itself. Personally, using 6+6 or 7+7 steps with KSampler and LoRA strength at 1.0 gives more natural character movements, without losing image quality. The downside is that it's slower, whether you're using Lightning 2.2 or Lightx2 2.1 T2V. On the other hand, using 4+4 steps with a strength of around 1.50 for high and 1.20 for low results in simpler movements and only a slight reduction in quality, but it’s much faster. That setup might be useful for certain types of animations. LCM Sampler also seems to work. You can run your own tests with different sampler and lighting LoRA configurations. Lightx2v Actual Kijai Lora speed for 2.2: <a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Wan22-Lightning">https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Wan22-Lightning</a> ---------- I made a compact WF for WAN 2.2 GGUF Links: Lora Lightx2v (wan 2.1-But it might still be compatible.): <a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Lightx2v">https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Lightx2v</a> GGUF: <a target="_blank" rel="ugc" href="https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF/tree/main">https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF/tree/main</a> or <a target="_blank" rel="ugc" href="https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/tree/main">https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/tree/main</a> You need a High model and a Low model with the same quantization. The VAE is the same as WAN 2.1. Make sure to update your ComfyUI.

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