jakechai
e9f17c7560
1. Create Subgraphs based on my Group Nodes and recreate all workflows using Subgraph. 2. Move all latest workflows using Group Node to subfolder named `ComfyUI_~frontend-1.23.4` or `Krita_~frontend-1.23.4_v1.19.20`. 3. Add LoRA Stack Model Only JK🐉, Apply LoRA Stack Model Only JK🐉. 4. Add Set LoRA | NAG | Set Radial Attention | FreeInit features to all WAN video gen workflows. 5. Add native VACE ff2v | VACE flf2v | VACE v2v | ATI ff2v | Fun control camera ff2v | Skyreel A2 ref2v | Phantom ref2v workflows. 6. Add native and wrapper Wan MAGREF workflows. 7. Update ref2v (subject2v) Wan workflows. 8. Add MultiTalk ff2v and v2v Wan Wrapper workflows. 9. Add Multitalk | Fantasy Talking v2v lip sync Wan Wrapper workflows. 10. Add Uni3C Camera Control to ff2v Wan Wrapper workflows. 11. Add MiniMax Remover v2v Wan Wrapper workflow. 12. Add Stand-In ref2v Wan wrapper workflows. 13. Add VACE | Phantom | Stand-In ref+v2v Face Swap workflows. 14. Add Create Loop Schedule List JK🐉 node. 15. Update SkyreelV2 DF long video Wan Wrapper workflow, using for loop. 16. Use the Torch Compile Model Wan Video v2 node for Native Wan Video workflows. 17. Set minimum resolution of Crop by Mask to 64. 18. Refine Common Group Node issue fixed. 19. Add Ksampler Adv Parameters Default JK🐉 node and 🐉 JK:::KSampler (High+Low) Group Node for Wan2.2. 20. Fix Switch(Any) node output datatype error in all workflows. 21. Update Refine Common Group Node for all workflows (ComfyUI frontend 1.23.4 or earlier).
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64 KiB
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This is usually slower, but saves even more VRAM compared to BlockSwap"],"color":"#432","bgcolor":"#653"},{"id":8,"type":"Note","pos":[2910,160],"size":[310,88],"flags":{},"order":5,"mode":0,"inputs":[],"outputs":[],"title":"Text Encode","properties":{},"widgets_values":["If you've already loaded the diffusion model to the offload device, you don't need to link model_to_offload, which will reduce some loading 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Very first steps should NEVER be skipped with this model or it kills the motion. When using the pre-calculated coefficients, the treshold value should be much higher than with the default coefficients. \n[Patch Model Patch Order](https://www.reddit.com/r/StableDiffusion/comments/1gjl982/lora_torchcompile_is_now_possible_thanks_to/) \nWith weight_patch_first, switching to a different LoRA is really fast, no need for full recompile. \n\n[Triton and SageAttention Installation](https://old.reddit.com/r/StableDiffusion/comments/1h7hunp/how_to_run_hunyuanvideo_on_a_single_24gb_vram_card/) \n[Triton:supported GPU](https://github.com/woct0rdho/triton-windows#1-gpu) \n[Triton:fp8 is not supported on RTX 30xx and older GPUs](https://github.com/woct0rdho/triton-windows#fp8-is-not-supported-on-rtx-30xx-and-older-gpus) \n\nEnhance: \n[Skip Layer Guidance](https://www.reddit.com/r/StableDiffusion/comments/1jac3wm/dramatically_enhance_the_quality_of_wan_21_using/) \n[CFG Zero Star](https://github.com/WeichenFan/CFG-Zero-star) \n[Enhance A Video](https://oahzxl.github.io/Enhance_A_Video/) \nEnhance-a-video can increase the fidelity of the results (also time), too high values lead to noisy results. \n[Unet Temporal Attention Multiply](https://www.runcomfy.com/comfyui-nodes/ComfyUI/UNetTemporalAttentionMultiply) \nuseful for tasks that require temporal coherence and consistency, such as video frame interpolation, temporal segmentation, and other time-series related applications. \n[RIFLEx](https://github.com/thu-ml/RIFLEx) \nExtent video."],"color":"#432","bgcolor":"#653"},{"id":46,"type":"Note","pos":[2410,620],"size":[470,88],"flags":{},"order":18,"mode":0,"inputs":[],"outputs":[],"title":"fp8_fast and fp16_fast precision","properties":{},"widgets_values":["fp8_fast seems to cause huge quality degradation\n\nfp_16_fast enables \"Full FP16 Accmumulation in FP16 GEMMs\" feature available in the very latest pytorch nightly, this is around 20% speed boost. 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Without this feature, even when slightly modifying the parameters of a workflow and rerunning it, there will be a cost of reloading into VRAM.\n This feature can be disabled using the --disable-smart-memory option.\nWhen --disable-smart-memory is applied, all data in VRAM is unloaded to RAM upon the completion of the workflow (based on the --normalvram setting).\n Choose --normalvram when --lowvram isn't enough VRAM.\n\n--cpu\n To use the CPU for everything 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name for S&R":"WanVideoTextEncode"},"widgets_values":["a monkey robot is smiling","色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",true,false,"gpu"],"color":"#332922","bgcolor":"#593930"},{"id":17,"type":"LoadWanVideoT5TextEncoder","pos":[2280,880],"size":[460,130],"flags":{},"order":45,"mode":0,"inputs":[{"localized_name":"model_name","name":"model_name","type":"COMBO","widget":{"name":"model_name"},"link":null},{"localized_name":"precision","name":"precision","type":"COMBO","widget":{"name":"precision"},"link":null},{"localized_name":"load_device","name":"load_device","shape":7,"type":"COMBO","widget":{"name":"load_device"},"link":null},{"localized_name":"quantization","name":"quantization","shape":7,"type":"COMBO","widget":{"name":"quantization"},"link":null}],"outputs":[{"localized_name":"wan_t5_model","name":"wan_t5_model","type":"WANTEXTENCODER","slot_index":0,"links":[9,16]}],"properties":{"cnr_id":"ComfyUI-WanVideoWrapper","ver":"d9b1f4d1a5aea91d101ae97a54714a5861af3f50","Node name for S&R":"LoadWanVideoT5TextEncoder"},"widgets_values":["WanVideo\\Kijai\\umt5-xxl-enc-fp8_e4m3fn.safetensors","bf16","offload_device","disabled"]},{"id":38,"type":"CLIPLoader","pos":[2280,1450],"size":[320,106],"flags":{},"order":46,"mode":0,"inputs":[{"localized_name":"clip_name","name":"clip_name","type":"COMBO","widget":{"name":"clip_name"},"link":null},{"localized_name":"type","name":"type","type":"COMBO","widget":{"name":"type"},"link":null},{"localized_name":"device","name":"device","shape":7,"type":"COMBO","widget":{"name":"device"},"link":null}],"outputs":[{"localized_name":"CLIP","name":"CLIP","type":"CLIP","slot_index":0,"links":[1,5,18]}],"properties":{"cnr_id":"comfy-core","ver":"0.3.29","Node name for S&R":"CLIPLoader","models":[{"name":"umt5_xxl_fp8_e4m3fn_scaled.safetensors","url":"https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true","directory":"text_encoders"}]},"widgets_values":["WanVideo\\ComfyOrg\\umt5_xxl_fp8_e4m3fn_scaled.safetensors","wan","default"]},{"id":15,"type":"WanVideoTextEmbedBridge","pos":[2970,1450],"size":[250,46],"flags":{},"order":58,"mode":0,"inputs":[{"localized_name":"positive","name":"positive","type":"CONDITIONING","link":6},{"localized_name":"negative","name":"negative","shape":7,"type":"CONDITIONING","link":7}],"outputs":[{"localized_name":"text_embeds","name":"text_embeds","type":"WANVIDEOTEXTEMBEDS","links":null}],"properties":{"cnr_id":"ComfyUI-WanVideoWrapper","ver":"18aa47cc74534241835d2682bc5b51293082529c","Node name for S&R":"WanVideoTextEmbedBridge"},"widgets_values":[]},{"id":14,"type":"CLIPTextEncode","pos":[2650,1450],"size":[285.6000061035156,100],"flags":{},"order":55,"mode":0,"inputs":[{"localized_name":"clip","name":"clip","type":"CLIP","link":5},{"localized_name":"text","name":"text","type":"STRING","widget":{"name":"text"},"link":null}],"outputs":[{"localized_name":"CONDITIONING","name":"CONDITIONING","type":"CONDITIONING","slot_index":0,"links":[6]}],"title":"CLIP Text Encode (Positive Prompt)","properties":{"cnr_id":"comfy-core","ver":"0.3.29","Node name for S&R":"CLIPTextEncode"},"widgets_values":["a monkey robot is smiling"],"color":"#232","bgcolor":"#353"},{"id":45,"type":"LoadWanVideoClipTextEncoder","pos":[1840,1240],"size":[400,106],"flags":{},"order":47,"mode":0,"inputs":[{"localized_name":"model_name","name":"model_name","type":"COMBO","widget":{"name":"model_name"},"link":null},{"localized_name":"precision","name":"precision","type":"COMBO","widget":{"name":"precision"},"link":null},{"localized_name":"load_device","name":"load_device","shape":7,"type":"COMBO","widget":{"name":"load_device"},"link":null}],"outputs":[{"localized_name":"wan_clip_vision","name":"wan_clip_vision","type":"CLIP_VISION","slot_index":0,"links":[]}],"properties":{"cnr_id":"ComfyUI-WanVideoWrapper","ver":"d9b1f4d1a5aea91d101ae97a54714a5861af3f50","Node name for S&R":"LoadWanVideoClipTextEncoder"},"widgets_values":["WanVideo\\Kijai\\open-clip-xlm-roberta-large-vit-huge-14_visual_fp16.safetensors","bf16","offload_device"]},{"id":37,"type":"WanVideoTextEncode","pos":[2770,880],"size":[450,234],"flags":{},"order":52,"mode":0,"inputs":[{"localized_name":"t5","name":"t5","shape":7,"type":"WANTEXTENCODER","link":9},{"localized_name":"model_to_offload","name":"model_to_offload","shape":7,"type":"WANVIDEOMODEL","link":null},{"localized_name":"positive_prompt","name":"positive_prompt","type":"STRING","widget":{"name":"positive_prompt"},"link":null},{"localized_name":"negative_prompt","name":"negative_prompt","type":"STRING","widget":{"name":"negative_prompt"},"link":null},{"localized_name":"force_offload","name":"force_offload","shape":7,"type":"BOOLEAN","widget":{"name":"force_offload"},"link":null},{"localized_name":"use_disk_cache","name":"use_disk_cache","shape":7,"type":"BOOLEAN","widget":{"name":"use_disk_cache"},"link":null},{"localized_name":"device","name":"device","shape":7,"type":"COMBO","widget":{"name":"device"},"link":null}],"outputs":[{"localized_name":"text_embeds","name":"text_embeds","type":"WANVIDEOTEXTEMBEDS","slot_index":0,"links":[17]}],"properties":{"cnr_id":"ComfyUI-WanVideoWrapper","ver":"d9b1f4d1a5aea91d101ae97a54714a5861af3f50","Node name for S&R":"WanVideoTextEncode"},"widgets_values":["a monkey robot is smiling","色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",true,false,"gpu"]},{"id":58,"type":"WanVideoTextEncodeSingle","pos":[2770,1180],"size":[450,180],"flags":{},"order":53,"mode":0,"inputs":[{"localized_name":"t5","name":"t5","shape":7,"type":"WANTEXTENCODER","link":16},{"localized_name":"model_to_offload","name":"model_to_offload","shape":7,"type":"WANVIDEOMODEL","link":null},{"localized_name":"prompt","name":"prompt","type":"STRING","widget":{"name":"prompt"},"link":null},{"localized_name":"force_offload","name":"force_offload","shape":7,"type":"BOOLEAN","widget":{"name":"force_offload"},"link":null},{"localized_name":"use_disk_cache","name":"use_disk_cache","shape":7,"type":"BOOLEAN","widget":{"name":"use_disk_cache"},"link":null},{"localized_name":"device","name":"device","shape":7,"type":"COMBO","widget":{"name":"device"},"link":null}],"outputs":[{"localized_name":"text_embeds","name":"text_embeds","type":"WANVIDEOTEXTEMBEDS","links":[15]}],"properties":{"cnr_id":"ComfyUI-WanVideoWrapper","ver":"907d1b0b0f649bd569bbf23430e107ab37832d73","Node name for S&R":"WanVideoTextEncodeSingle"},"widgets_values":["色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",true,false,"gpu"]},{"id":61,"type":"Note","pos":[3280,1060],"size":[300,240],"flags":{},"order":48,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["nag_scale: The scale for attention feature extrapolation. Higher values result in stronger negative guidance.\nnag_tau: The normalisation threshold. Higher values result in stronger negative guidance.\nnag_alpha: Blending factor between original and extrapolated attention. Higher values result in stronger negative guidance.\n\nFor image-reference tasks (e.g., Image2Video), use lower nag_tau and nag_alpha to preserve the reference content more faithfully.\nFor models that require more sampling steps and higher CFG, also prefer lower nag_tau and nag_alpha.\nFor few-step models, you can use higher nag_tau and nag_alpha to have stronger negative guidance."],"color":"#432","bgcolor":"#653"},{"id":57,"type":"WanVideoApplyNAG","pos":[3280,880],"size":[300,126],"flags":{},"order":57,"mode":0,"inputs":[{"localized_name":"original_text_embeds","name":"original_text_embeds","type":"WANVIDEOTEXTEMBEDS","link":17},{"localized_name":"nag_text_embeds","name":"nag_text_embeds","type":"WANVIDEOTEXTEMBEDS","link":15},{"localized_name":"nag_scale","name":"nag_scale","type":"FLOAT","widget":{"name":"nag_scale"},"link":null},{"localized_name":"nag_tau","name":"nag_tau","type":"FLOAT","widget":{"name":"nag_tau"},"link":null},{"localized_name":"nag_alpha","name":"nag_alpha","type":"FLOAT","widget":{"name":"nag_alpha"},"link":null}],"outputs":[{"localized_name":"text_embeds","name":"text_embeds","type":"WANVIDEOTEXTEMBEDS","links":null}],"properties":{"cnr_id":"ComfyUI-WanVideoWrapper","ver":"907d1b0b0f649bd569bbf23430e107ab37832d73","Node name for S&R":"WanVideoApplyNAG"},"widgets_values":[11,2.5,0.25]},{"id":62,"type":"WanVideoTextEmbedBridge","pos":[2970,1800],"size":[250,46],"flags":{},"order":59,"mode":0,"inputs":[{"localized_name":"positive","name":"positive","type":"CONDITIONING","link":20},{"localized_name":"negative","name":"negative","shape":7,"type":"CONDITIONING","link":null}],"outputs":[{"localized_name":"text_embeds","name":"text_embeds","type":"WANVIDEOTEXTEMBEDS","links":null}],"properties":{"cnr_id":"ComfyUI-WanVideoWrapper","ver":"18aa47cc74534241835d2682bc5b51293082529c","Node name for S&R":"WanVideoTextEmbedBridge"},"widgets_values":[]},{"id":59,"type":"CLIPTextEncode","pos":[2650,1800],"size":[303.6000061035156,130],"flags":{},"order":56,"mode":0,"inputs":[{"localized_name":"clip","name":"clip","type":"CLIP","link":18},{"localized_name":"text","name":"text","type":"STRING","widget":{"name":"text"},"link":null}],"outputs":[{"localized_name":"CONDITIONING","name":"CONDITIONING","type":"CONDITIONING","slot_index":0,"links":[20]}],"title":"CLIP Text Encode (NAG Negative Prompt)","properties":{"cnr_id":"comfy-core","ver":"0.3.29","Node name for S&R":"CLIPTextEncode"},"widgets_values":["色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"],"color":"#322","bgcolor":"#533"},{"id":48,"type":"MarkdownNote","pos":[-100,1690],"size":[210,320],"flags":{},"order":49,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["Recommend native workflow: \n1. Native Video Inpaint \n2. Native VACE Video Repaint\n3. Depth | Tile Lora (error occur when wrapper loading model)\n4. Not using features below:\n- [VACE](https://ali-vilab.github.io/VACE-Page/) other than Repaint\n- Skyreel [A2](https://github.com/SkyworkAI/SkyReels-A2) [V2](https://github.com/SkyworkAI/SkyReels-V2)\n- [ATI](https://github.com/bytedance/ATI)\n- [ReCamMaster](https://github.com/KwaiVGI/ReCamMaster)\n- [MiniMax Remover](https://github.com/zibojia/MiniMax-Remover)\n- [Fantasy Talking](https://github.com/Fantasy-AMAP/fantasy-talking)\n- [Multi Talking](https://github.com/MeiGen-AI/MultiTalk)\n- [Unianimate](https://github.com/ali-vilab/UniAnimate)\n- [Uni3C](https://github.com/ewrfcas/Uni3C)\n- [Flow Edit](https://github.com/fallenshock/FlowEdit)\n- [Dilated ControlNet](https://github.com/TheDenk/wan2.1-dilated-controlnet)\n- [Radial Attention](https://github.com/mit-han-lab/radial-attention)\n- [Enhanced A Video](https://oahzxl.github.io/Enhance_A_Video/)\n- [FreeInit](https://tianxingwu.github.io/pages/FreeInit/)\n- [Loop](https://github.com/YisuiTT/Mobius/)\n- [Context Window](https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved) "],"color":"#432","bgcolor":"#653"},{"id":56,"type":"MarkdownNote","pos":[1330,1550],"size":[560,1600],"flags":{},"order":50,"mode":0,"inputs":[],"outputs":[],"title":"WAN eco","properties":{},"widgets_values":["| Features | Function | Usage |\n|----------|----------|-------|\n| ComfyOrg [2.2](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged) [2.1](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main) | | |\n| Kijai [WAN](https://huggingface.co/Kijai/WanVideo_comfy/tree/main) [WAN fp8 scaled](https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled) | | |\n| *Common Feature* | | |\n| [Triton (Torch Compile)](https://github.com/woct0rdho/triton-windows) | speed up | ~ |\n| [Radial Attention](https://github.com/mit-han-lab/radial-attention) | speed up | ~ |\n| [Sage Attention](https://github.com/thu-ml/SageAttention) | speed up | ~ |\n| [Flash Attention](https://github.com/Dao-AILab/flash-attention) | speed up | ~ |\n| [SDP Attention](https://uxlfoundation.github.io/oneDNN/dev_guide_graph_sdpa.html) | speed up | ~ |\n| [EasyCache](https://github.com/H-EmbodVis/EasyCache) | speed up | ~ |\n| [MagCache](https://github.com/Zehong-Ma/MagCache) | speed up | ~ |\n| [TeaCache](https://github.com/ali-vilab/TeaCache) | speed up | ~ |\n| [Enhanced A Video](https://oahzxl.github.io/Enhance_A_Video/) | enhancement | ~ |\n| [SLG](https://www.reddit.com/r/StableDiffusion/comments/1jac3wm/dramatically_enhance_the_quality_of_wan_21_using/) | enhancement | ~ |\n| [CFG Zero Star](https://github.com/WeichenFan/CFG-Zero-star) | enhancement | ~ |\n| [FreSca](https://github.com/WikiChao/FreSca) | enhancement | ~ |\n| [FreeInit](https://tianxingwu.github.io/pages/FreeInit/) | enhancement | ~ |\n| [NAG](https://chendaryen.github.io/NAG.github.io/) | enhancement | ~ |\n| [TCFG](https://huggingface.co/papers/2503.18137) | enhancement | ~ |\n| [RAAG](https://arxiv.org/abs/2508.03442) | enhancement | ~ |\n| [Loop](https://github.com/YisuiTT/Mobius/) | loop video | ~ |\n| [RIFLEx](https://github.com/thu-ml/RIFLEx) | long video | ~ |\n| [Context Window](https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved) | long & loop video | ~ |\n| [Flow Edit](https://github.com/fallenshock/FlowEdit) | in content edit | v2v |\n| *Main Model* | | |\n| WAN Video [2.2](https://github.com/Wan-Video/Wan2.2) [2.1](https://github.com/Wan-Video/Wan2.1) | main model | t2v ff2v flf2v v2v |\n| WAN Video GGUF [2.2](https://huggingface.co/collections/QuantStack/wan22-ggufs-6887ec891bdea453a35b95f3) [2.1](https://huggingface.co/city96) | main model | t2v ff2v flf2v v2v |\n| VACE [2.2 Test](https://huggingface.co/lym00/Wan2.2_T2V_A14B_VACE-test) [2.2 Fake](https://huggingface.co/CCP6/FakeVace2.2) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| VACE GGUF [2.1](https://huggingface.co/QuantStack/Wan2.1_14B_VACE-GGUF) [2.1](https://github.com/ali-vilab/VACE) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| VACE LightX2V [2.1](https://huggingface.co/lym00/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| VACE LightX2V GGUF [2.1](https://huggingface.co/QuantStack/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| VACE FusionX [2.1](https://huggingface.co/QuantStack/Wan2.1_T2V_14B_FusionX_VACE) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| VACE FusionX GGUF [2.1](https://huggingface.co/collections/QuantStack/wan21-fusionx-ggufs-68498e41b3597737512c0636) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| VACE Phantom [2.1](https://huggingface.co/Inner-Reflections/Wan2.1_VACE_Phantom) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| VACE SF (GGUF) [2.1](https://huggingface.co/lym00) | main model | t2v ff2v flf2v ref2v v2v ref+v2v |\n| *Low-Step model* | | |\n| lightX2V [2.2](https://huggingface.co/lightx2v/Wan2.2-Lightning) [2.1](https://huggingface.co/lightx2v) | main model & lora | t2v ff2v v2v lcm simple steps 4 cfg 1.0 |\n| FusionX [2.1](https://huggingface.co/vrgamedevgirl84/Wan14BT2VFusioniX) | main model & lora | t2v ff2v v2v uni_pc simple steps 8 cfg 1.0|\n| FusionX GGUF [2.1](https://huggingface.co/collections/QuantStack/wan21-fusionx-ggufs-68498e41b3597737512c0636) | main model | t2v ff2v v2v uni_pc simple steps 8 cfg 1.0|\n| CausVid [2.1](https://github.com/tianweiy/CausVid) | main model & lora | t2v ff2v v2v uni_pc(flowmatch_causvid) simple steps 8 cfg 1.0 |\n| AccVid [2.1](https://github.com/aejion/AccVideo) | main model & lora | t2v ff2v v2v uni_pc simple steps 8 cfg 1.0 |\n| Fast Wan [2.1](https://huggingface.co/FastVideo) | main model & lora | t2v v2v uni_pc simple steps 8 cfg 1.0 |\n| Pusa* [2.1](https://github.com/Yaofang-Liu/Pusa-VidGen) | lora | t2v ff2v flf2v v2v uni_pc(flowmatch_pusa) simple steps 5 cfg 5.0 |\n| *Functional Model* | | |\n| FUN Control [2.2](https://huggingface.co/collections/alibaba-pai/wan22-fun-68958eabec343b948f1225c5) [2.1](https://huggingface.co/collections/alibaba-pai/wan21-fun-v11-680f514c89fe7b4df9d44f17) | main model & lora | t2v ff2v |\n| FUN Inpaint [2.2](https://huggingface.co/collections/alibaba-pai/wan22-fun-68958eabec343b948f1225c5) [2.1](https://huggingface.co/collections/alibaba-pai/wan21-fun-v11-680f514c89fe7b4df9d44f17) | main model & lora | ff2v flf2v |\n| FUN Camera [2.1](https://huggingface.co/collections/alibaba-pai/wan21-fun-v11-680f514c89fe7b4df9d44f17) | main model | ff2v |\n| Phantom [2.1](https://github.com/Phantom-video/Phantom) | main model & lora | ref2v ref+v2v |\n| Stand-In [2.1](https://www.stand-in.tech/) | lora | ref2v ref+v2v |\n| MAGREF [2.1](https://github.com/MAGREF-Video/MAGREF) | main model | ref2v |\n| Skyreel A2 [2.1](https://github.com/SkyworkAI/SkyReels-A2) | main model | ref2v |\n| Skyreel V2 [2.1](https://github.com/SkyworkAI/SkyReels-V2) | main & lora | t2v ff2v v2v |\n| Skyreel V2 DF [2.1](https://github.com/SkyworkAI/SkyReels-V2) | main DF model | t2v ff2v v2v |\n| MoviiGen [2.1](https://huggingface.co/ZuluVision/MoviiGen1.1) | main model & lora | t2v v2v |\n| Echo Shot [2.1](https://github.com/JoHnneyWang/EchoShot) | main model & lora | t2v |\n| ATI [2.1](https://github.com/bytedance/ATI) | main model | ff2v |\n| AniSora [2.1](https://github.com/bilibili/Index-anisora) | main model | ff2v |\n| ReCamMaster [2.1](https://github.com/KwaiVGI/ReCamMaster) | main model | v2v |\n| MiniMax Remover [2.1](https://github.com/zibojia/MiniMax-Remover) | main model | v2v |\n| Fantasy Talking [2.1](https://github.com/Fantasy-AMAP/fantasy-talking) | module model | ff2v v2v |\n| Multi Talk [2.1](https://github.com/MeiGen-AI/MultiTalk) | module model | ff2v v2v |\n| *control* | | |\n| Unianimate [2.1](https://github.com/ali-vilab/UniAnimate) | control lora | ff2v |\n| Depth lora [2.1](https://huggingface.co/spacepxl/Wan2.1-control-loras/tree/main/1.3b/depth) | control lora | t2v |\n| Tile lora [2.1](https://huggingface.co/spacepxl/Wan2.1-control-loras/tree/main/1.3b/tile) | control lora | v2v |\n| Dilated ControlNet [2.2](https://huggingface.co/collections/TheDenk/wan22-controlnets-688b754ca3ee3bc7b34253bf) [2.1](https://github.com/TheDenk/wan2.1-dilated-controlnet) | controlnet | t2v v2v |\n| Uni3C* [2.1](https://github.com/ewrfcas/Uni3C) | 3D controlnet | t2v ff2v v2v |\n| RealisDance* [2.1](https://github.com/damo-cv/RealisDance) | 3D controlnet | t2v ff2v v2v 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