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WAN 2.2 AIO Rapid — All-in-One T2V + I2V (4–12GB VRAM / GGUF)
WAN 2.2 AIO Rapid — All-in-One T2V + I2V (4–12GB VRAM / GGUF)
WAN 2.2 AIO Rapid — All-in-One T2V + I2V (4–12GB VRAM / GGUF)
Here check out my toturial on running this if youre stuck:📦 Download & Setup1. Main Model (Standard VRAM: 6–12GB)Download from:https://huggingface.co/Phr00t/WAN2.2-14B-Rapid-AllInOneFile:wan2.2-rapid-mega-aio-nsfw-v1…
视频
20 个节点 1,253 次使用 The_frizzy1 21 KB
需要的权重
这个工作流引用了 1 个权重文件，其中 0 个能在本站模型库里找到。
The_frizzy1_wan-2.2-aio-rapid_v1.0.1.json
模型库暂未收录
节点构成
CLIPTextEncode
× 2
LoadImage
× 2
Note
× 2
MarkdownNote
× 2
PrimitiveInt
× 1
KSampler
× 1
WanVaceToVideo
× 1
ModelSamplingSD3
× 1
CLIPLoader
× 1
WanVideoVACEStartToEndFrame
× 1
VAELoader
× 1
SaveVideo
× 1
Tiled KSampler
× 1
VAEDecode
× 1
CreateVideo
× 1
GGUFLoaderKJ
× 1
官方标注的模型
umt5_xxl_fp8_e4m3fn_scaled.safetensorswan2.2-rapid-mega-aio-v12-Q4_K.ggufwan_2.1_vae.safetensors
工作流 JSON
和上面「下载工作流 JSON」是同一份文件。
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822 "## How to use\n\n**What it does:** Wan 2.2 text-to-video and image-to-video from one \"rapid mega AIO\" GGUF file (experts and speed LoRA baked in). 4 steps, CFG 1.\n\n**Inputs**\n1. **Prompt** (top text box): describe the shot and the camera move. Positive wording only.\n2. **Negative Prompt**: leave it empty. At CFG 1 it has no effect.\n3. **Number of Frames**: 81 by default (about 5 s at 16 fps). Use 4n+1 values (49, 65, 81, 97 ...).\n4. **Start Frame / End Frame** (blue group, optional): images for I2V or first-frame-last-frame.\n\n**T2V or I2V**\n- **T2V (default):** keep the blue group and the *WanVideoVACEStartToEndFrame* node bypassed. The WanVaceToVideo node title says strength 0 for T2V (saved value is 1).\n- **I2V / FFLF:** un-bypass the two Load Image nodes and the StartToEndFrame node, load your images, set *strength* to 1. For first-frame-last-frame use 81 frames or more.\n- Only a start image: bypass the End Frame node.\n\n**Important settings**\n- **WanVaceToVideo**: width 1280, height 720 (multiples of 16).\n- **ModelSamplingSD3** shift 8.\n- **KSampler**: 4 steps, CFG 1, euler / simple, seed randomize.\n- **Create Video** 16 fps. Output lands in `ComfyUI/output/video/`.\n- **GGUF loader**: pick a smaller quant of the same mega AIO if you are short on VRAM.\n\n**Tips**\n- Out of VRAM: lower the size (e.g. 832x480) or the frame count first. The Tiled KSampler node (not wired, needs the tiled_ksampler pack) can stand in for the KSampler: connect the same model, positive, negative and latent.\n- Change the seed for a new take; keep it fixed while you tune the prompt.\n\n**Attention:** --use-sage-attention ran at the same speed as the default on the 24 GB bench and used less VRAM on Z-Image (not measured on Wan). --use-ck-attention changes the image for the same seed.\n\n**Tested on:** no recorded test run yet. Not run on ComfyUI 0.45.3 (the AIO GGUF is not on the bench server)."
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846 "## Downloads - put each file in the ComfyUI folder shown\n\nClick a file name to download it. Put it in the folder shown (inside `ComfyUI/models/`).\n\n| Folder | File (click = download) | Note |\n|---|---|---|\n| `diffusion_models/` | [wan2.2-rapid-mega-aio-v12-Q4_K.gguf](https://huggingface.co/befox/WAN2.2-14B-Rapid-AllInOne-GGUF/resolve/main/Mega-v12/wan2.2-rapid-mega-aio-v12-Q4_K.gguf) | single all-in-one file, 11.6 GB |\n| `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) | |\n| `vae/` | [wan_2.1_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors) | |\n\nNo separate high/low-noise or lightx2v files needed.\n\n**Custom node packs:** ComfyUI-KJNodes (GGUF loader), ComfyUI-WanVideoWrapper (StartToEndFrame, I2V only), tiled_ksampler (optional Tiled KSampler), ComfyUI-VideoHelperSuite.\n\nOne command from the repo root: `python scripts/frizzy.py doctor wan2.2/aio-rapid`"
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