The compressed package contains 2 ComfyUI workflows for running: 1.Wan 2.1 T2V:	wan2-t2v-upscale-v1.json 2.Wan 2.1 I2V:	wan2-i2v-upscale-v1.json<h2 id="reference-output:-u1cokbdss">Reference output:</h2>On my RTX4060 8GB vRAM + 32G RAM i2v: Prompt executed in 2807.42 secondsOn my RTX5080 laptop 16G vRAM + 32G RAM i2v: Prompt executed in 1401.00 seconds<h2 id="requirements:-7u3113ipp">Requirements:</h2><h3 id="models:-n9k3jdtkh">Models:</h3>- wan2.1-t2v-14b-Q3_K_M.gguf (T2V) Put in: ComfyUI\models\unet <a target="_blank" rel="ugc" href="https://huggingface.co/city96/Wan2.1-T2V-14B-gguf/resolve/main/wan2.1-t2v-14b-Q3_K_M.gguf">https://huggingface.co/city96/Wan2.1-T2V-14B-gguf/resolve/main/wan2.1-t2v-14b-Q3_K_M.gguf</a>	- wan2.1-i2v-14b-480p-Q3_K_M.gguf (I2V) Put in: ComfyUI\models\unet <a target="_blank" rel="ugc" href="https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf/resolve/main/wan2.1-i2v-14b-480p-Q3_K_M.gguf">https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf/resolve/main/wan2.1-i2v-14b-480p-Q3_K_M.gguf</a>- wan2.1_t2v_1.3B_fp16.safetensors (t2v model, used in workflow "v2v") Put in: ComfyUI\models\diffusion_models <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_1.3B_fp16.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_1.3B_fp16.safetensors</a>- umt5-xxl-encoder-Q4_K_M.gguf (CLIP) Put in: ComfyUI\models\text_encoders <a target="_blank" rel="ugc" href="https://huggingface.co/city96/umt5-xxl-encoder-gguf/resolve/main/umt5-xxl-encoder-Q4_K_M.gguf">https://huggingface.co/city96/umt5-xxl-encoder-gguf/resolve/main/umt5-xxl-encoder-Q4_K_M.gguf</a>- umt5_xxl_fp8_e4m3fn_scaled.safetensors (CLIP, can use above if you modify workflow "v2v") Put in: ComfyUI\models\text_encoders <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors</a>- wan_2.1_vae.safetensors (VAE) Put in: ComfyUI\models\vae <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors</a>- clip_vision_h.safetensors (CLIP VISION) Put in: ComfyUI\models\clip_vision <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors</a>- RealESRGAN_x2plus.pth (Upscale Model) Put in: ComfyUI\models\upscale_models <a target="_blank" rel="ugc" href="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth">https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth</a><h3 id="comfyui-nodes:-fajzyllng">ComfyUI Nodes:</h3>- rgthree-comfy- ComfyUI-KJNodes- ComfyUI-VideoHelperSuite- ComfyUI-Frame-Interpolation- Comfyui-Memory_Cleanup (Not required if you modify the workflow)If you have higher performance hardware, you can choose higher quantization models.

Wan Video ComfyUI (T2V & I2V)

I completely refactored the workflow.The compressed file contains 3 ComfyUI workflows for running: 1.wan2.2-i2v-gguf-v2.json 2.wan2.2-i2v-v2.json 2.wan2.2-t2v-gguf-v2.jsonReference output:RTX4060 8GB vRAM + 32G RAM i2v(GGUF Q5_K_M; 81*512*784): Prompt executed in 00:10:14RTX4070 16GB vRAM + 32G RAM i2v(Remix; 81*576*864): Prompt executed in 325.84 secondsRTX5080 laptop 16G vRAM + 64G RAM i2v(Remix; 81*576*960): Prompt executed in 377.07 secondsRequirements:Models:Main Process:- Wan 2.2 (GGUF), Put in: ComfyUI\models\unet; vRAM 16G can use Q8_0, vRAM 8G can use Q5_K_M. - Wan2.2-T2V. <a target="_blank" rel="ugc" href="https://huggingface.co/QuantStack/Wan2.2-T2V-A14B-GGUF/resolve/main/HighNoise/Wan2.2-T2V-A14B-HighNoise-Q5_K_M.gguf">https://huggingface.co/QuantStack/Wan2.2-T2V-A14B-GGUF/resolve/main/HighNoise/Wan2.2-T2V-A14B-HighNoise-Q5_K_M.gguf</a>	<a target="_blank" rel="ugc" href="https://huggingface.co/QuantStack/Wan2.2-T2V-A14B-GGUF/resolve/main/LowNoise/Wan2.2-T2V-A14B-LowNoise-Q5_K_M.gguf">https://huggingface.co/QuantStack/Wan2.2-T2V-A14B-GGUF/resolve/main/LowNoise/Wan2.2-T2V-A14B-LowNoise-Q5_K_M.gguf</a> - Wan2.2-I2V. <a target="_blank" rel="ugc" href="https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF/resolve/main/HighNoise/Wan2.2-I2V-A14B-HighNoise-Q5_K_M.gguf">https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF/resolve/main/HighNoise/Wan2.2-I2V-A14B-HighNoise-Q5_K_M.gguf</a> <a target="_blank" rel="ugc" href="https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF/resolve/main/LowNoise/Wan2.2-I2V-A14B-LowNoise-Q5_K_M.gguf">https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF/resolve/main/LowNoise/Wan2.2-I2V-A14B-LowNoise-Q5_K_M.gguf</a> Wan 2.2 (safetensors), Put in: ComfyUI\models\diffusion_models - Remix 2.0 NSFW Version, I2V. <a target="_blank" rel="ugc" href="https://huggingface.co/FX-FeiHou/wan2.2-Remix/resolve/main/NSFW/Wan2.2_Remix_NSFW_i2v_14b_high_lighting_v2.0.safetensors">https://huggingface.co/FX-FeiHou/wan2.2-Remix/resolve/main/NSFW/Wan2.2_Remix_NSFW_i2v_14b_high_lighting_v2.0.safetensors</a>	<a target="_blank" rel="ugc" href="https://huggingface.co/FX-FeiHou/wan2.2-Remix/resolve/main/NSFW/Wan2.2_Remix_NSFW_i2v_14b_low_lighting_v2.0.safetensors">https://huggingface.co/FX-FeiHou/wan2.2-Remix/resolve/main/NSFW/Wan2.2_Remix_NSFW_i2v_14b_low_lighting_v2.0.safetensors</a>- umt5-xxl-encoder-Q8_0.gguf; (CLIP) Put in: ComfyUI\models\text_encoders <a target="_blank" rel="ugc" href="https://huggingface.co/city96/umt5-xxl-encoder-gguf/resolve/main/umt5-xxl-encoder-Q8_0.gguf">https://huggingface.co/city96/umt5-xxl-encoder-gguf/resolve/main/umt5-xxl-encoder-Q8_0.gguf</a> NSFW-API/NSFW-Wan-UMT5-XXL <a target="_blank" rel="ugc" href="https://huggingface.co/NSFW-API/NSFW-Wan-UMT5-XXL/resolve/main/nsfw_wan_umt5-xxl_fp8_scaled.safetensors">https://huggingface.co/NSFW-API/NSFW-Wan-UMT5-XXL/resolve/main/nsfw_wan_umt5-xxl_fp8_scaled.safetensors</a>- wan_2.1_vae.safetensors (VAE) Put in: ComfyUI\models\vae <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors</a>- Optional Loras, speed-up; Put in: ComfyUI\models\loras\LightX2V Page Link: <a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/tree/main">https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/tree/main</a> <a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/resolve/main/wan2.2_i2v_A14b_high_noise_lora_rank64_lightx2v_4step_1022.safetensors">https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/resolve/main/wan2.2_i2v_A14b_high_noise_lora_rank64_lightx2v_4step_1022.safetensors</a> <a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/resolve/main/wan2.2_i2v_A14b_low_noise_lora_rank64_lightx2v_4step_1022.safetensors">https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/resolve/main/wan2.2_i2v_A14b_low_noise_lora_rank64_lightx2v_4step_1022.safetensors</a>ComfyUI Nodes:- rgthree-comfy- ComfyUI-KJNodes- ComfyUI-VideoHelperSuite- ComfyUI-Frame-Interpolation- Comfyui-Memory_Cleanup- ComfyUI-GGUF- comfyui-custom-scriptsIf you have higher performance hardware, you can choose higher quantization models.

Files with SHA256: 153cb08f18eb4de97e4690c750090f09929009009a129eda1600e3c3a87480f4