WAN 2.2 IMAGE to VIDEO with Caption and Postprocessing

Details

Model description

Workflow: Image -> Autocaption (Prompt) -> WAN I2V with Upscale and Frame Interpolation and Video Extension

  • Creates Video Clips with 480p or 720p resolution.

There is a Florence Caption Version and a LTX Prompt Enhancer (LTXPE) version. LTXPE is more heavy on VRAM


Oct.25: New LightX Lora (MoE) is out , try with strength > 1.5, 7 steps, SD3 shift =5.0. replace High Noise Lora:

https://huggingface.co/Kijai/WanVideo_comfy/tree/main/LoRAs/Wan22_Lightx2v

Oct 22nd 25: another LightX Lora has just been released (named 1022):

https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/tree/main


MultiClip LTXPE PLUS: Wan 2.2. 14B I2V Version based on below MultiClip workflow with improved LTX Prompt Enhancer (LTXPE) features (see notes in workflow).

Workflow enhances the LTXPE features to give more control over the prompt generation, it uses an uncensored language model, the video generation part is identical to below version. More Info: /model/1823416?modelVersionId=2303138&dialog=commentThread&commentId=972440


MultiClip: Wan 2.2. 14B I2V Version supporting LightX2V Wan 2.2. Loras to create clips with 4-6 steps and extend up to 3 times, see examples posted with 15-20sec of length.

There is a normal version which allows to use own prompts and a version using LTXPE for autoprompting. Normal version works well for specific or NSFW clips with Loras and the LTXPE is made to just drop an image, set width/height and hit run. The clips are combined to one full video at the end.

  • supporting new Wan 2.2. LightX2v Loras for low steps

  • in addition you are able to inject the "old" LightX2v Wan 2.1 Lora. This can help to avoid slow motion clips and can introduce more dynamic motion.

  • supporting Wan 2.2. Loras per sequence

  • Single Clip Versions included, which correspond to below V1.0 Workflow with additional Lora loader for "old" Wan 2.1. LightX2v Lora.

Since Wan 2.2 uses 2 models, the workflow gets complex. Still recommend to check the Wan 2.1 MultiClip Version, which is much leaner and has a rich selection of Loras. It can be found here: /model/1309065?modelVersionId=1998473


V1.0 WAN 2.2. 14B Image to Video workflow with LightX2v I2V Wan 2.2 Lora support for low steps (4-8 steps)

  • Wan 2.2. uses 2 models to process a clip. A High Noise and a Low Noise model, processed in sequence.

  • compatible with LightX2v Loras to process clips fast with low steps.

  • compatible to some of the "old" Wan2.1 Loras and "new" Wan 2.2. Loras

  • See notes in workflow and Tips below.

Models can be donwloaded here:

Models (Low & High Noise required, pick the ones matching your Vram): https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/tree/main

LightX2v Loras for Wan 2.2. (I2v, Hi and Lo): https://huggingface.co/Kijai/WanVideo_comfy/tree/main/LoRAs/Wan22-Lightning/old

LightX2v Lora (old Wan 2.1): https://huggingface.co/lightx2v/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v/tree/main/loras

Vae (same as Wan 2.1): https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/vae

Textencoder (same as Wan 2.1): https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files/text_encoders


WAN 2.2. I2V 5B Model (GGUF) workflow with Florence or LTXPE auto caption

  • lower quality than 14B model

  • 720p @ 24 frames

  • with FastWan Lora use CFG of 1 and 4-5 Steps, place a LoraLoader node after Unet Loader to inject Lora

FastWan Lora: https://huggingface.co/Kijai/WanVideo_comfy/tree/main/FastWan

Model (GGUF, pick model matching your Vram): https://huggingface.co/QuantStack/Wan2.2-TI2V-5B-GGUF/tree/main

VAE : https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files/vae

Textencoder (same as Wan 2.1) :https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files/text_encoders


location to save those files within your Comfyui folder:

Wan GGUF Model -> models/unet

Textencoder -> models/clip

Vae -> models/vae


Tips (for 14b Model):

Images made by this model

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