<h1 id="drag-and-drop-png-workflows-in-comfyui-just-like-json-a-set-of-comfyui-workflows-for-wan-video:">DRAG AND DROP PNG WORKFLOWS IN COMFYUI JUST LIKE JSON A set of ComfyUI workflows for WAN Video:</h1>I highly recommend using Torch Compile and Sage Attention (set as “SageAttention_Compiled” in the model loaders). The TorchCompile node and SageAttention are enabled by default. If you don’t have them installed, you can bypass the TorchCompile node and use SDPA instead of Sage Attention - it will be slower, but it will work.VACE WAN 2.2 Depth ControlWAN 2.1 I2VWAN 2.1 T2VWAN 2.2 FaceEnhanceWAN 2.2 I2V StartEnd FramesWAN 2.2 I2VWAN 2.2 LORA COMPAREWAN 2.2 S2VWAN 2.2 T2IWAN 2.2 T2VWAN ANIMATE 2.2WAN 2.2 FASTWAN 5B ControlNetDepthWAN 2.2 FASTWAN 5B I2VWAN 2.2 FASTWAN 5B T2VFlashVSR FaceEnhanceFlashVSR UPSCALEWAN 2.1 FantasyPortraitWAN 2.2 I2V FAST EFFICIENT BATCHWAN T2I 2.2 FAST EFFICIENT BATCHWAN T2V 2.2 FAST EFFICIENT BATCHWAN 2.2 UPSCALE + FACE ENHANCEWAN 2.2 UPSCALEWAN 2.2 FunCameraControl I2VWAN 2.2 FunControlWAN 2.2 MANUAL FunCameraControl I2V".png contains workflows, you can drag and drop them like .json in your ComfyUI interface"Some workflows uses Subgraphs, on your .bat launcher set:--front-end-version Comfy-Org/ComfyUI_frontend@latestMake sure to update your <a target="_blank" rel="ugc" href="https://github.com/kijai/ComfyUI-WanVideoWrapper">Kijai nodes</a> and <a target="_blank" rel="ugc" href="https://github.com/PGCRT/CRT-Nodes/tree/main">CRT-Nodes</a>You can find better <a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/tree/main">scaled versions here</a><a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/WanVideo_comfy/tree/main">Featured models</a><h3 id="this-is-my-runpod-referal-link-to-earn-5dollar-wich-is-about-6h-of-free-rtx-5090-usage-:-https:runpod.iorefu7b2habt">This is my RUNPOD referal link to earn 5$, wich is about 6h of free RTX 5090 usage : <a target="_blank" rel="ugc" href="https://runpod.io?ref=u7b2habt">https://runpod.io?ref=u7b2habt</a></h3>It also helps me to train new models, thanks.

WAN 2.2 Workflow T2V-I2V-T2I (Kijai Wrapper)

wan22WorkflowT2VI2VT2I_v153.zip

wan22WorkflowT2VI2VT2I_v164.zip

wan22WorkflowT2VI2VT2I_v179.zip

wan22WorkflowT2VI2VT2I_v160.zip

wan22WorkflowT2VI2VT2I_v167.zip

wan22WorkflowT2VI2VT2I_v182.zip

wan22WorkflowT2VI2V_v14.zip

wan22WorkflowT2VI2VT2I_v152.zip

wan22WorkflowT2VI2VT2I_v180.zip

wan22WorkflowT2VI2VT2I_v181.zip

wan22WorkflowT2VI2VT2I_v166.zip

wan22WorkflowT2VI2V_v13.zip

wan22WorkflowT2VI2VT2I_v165.zip

wan22WorkflowT2VI2VT2I_v177.zip

wan22WorkflowT2VI2VT2I_v163.zip

wan22WorkflowT2VI2VT2I_v183.zip

wan22WorkflowT2VI2VT2I_v162.zip

wan22WorkflowT2VI2VT2I_v154.zip

wan22WorkflowT2VI2VT2I_v175.zip

wan22WorkflowT2VI2VT2I_v176.zip

wan22WorkflowT2VI2VT2I_v157.zip

wan22WorkflowT2VI2VT2I_v155.zip

wan22WorkflowT2VI2VT2I_v158.zip

wan22WorkflowT2VI2VT2I_v178.zip

wan22WorkflowT2VI2VT2I_v184.zip

wan22WorkflowT2VI2VT2I_v185.zip

v1.8.5

Files with SHA256: c0e11d3ba34377e31c002c7832f9e2d3d972a592ee888cb290ba072ad39e4c57