工作流 /
视频 /
Wan2.1(GGUF) only 4GB-VRAM ComfyUI Workflow
Wan2.1(GGUF) only 4GB-VRAM ComfyUI Workflow
Wan2.1(GGUF) only 4GB-VRAM ComfyUI Workflow
Video Generation on a LaptopHello!This workflow utilizes a few custom nodes from Kijai and other sources to ensure smooth performance on an RTX 3050 Laptop Edition with just 4GB of VRAM. It's optimized to improve generat…
视频
30 个节点 29,955 次使用 The_frizzy1 36 KB
需要的权重
这个工作流引用了 2 个权重文件，其中 0 个能在本站模型库里找到。
The_frizzy1_wan-2.1-i2v_v2.0.1.json
模型库暂未收录
The_frizzy1_wan-2.1-t2v_v2.0.1.json
模型库暂未收录
节点构成
Note
× 2
CLIPTextEncode
× 2
MarkdownNote
× 2
Lora Loader Stack (rgthree)
× 1
TorchCompileModelWanVideoV2
× 1
PathchSageAttentionKJ
× 1
RIFE VFI
× 1
WanVideoNAG
× 1
ApplyRifleXRoPE_WanVideo
× 1
UpscaleModelLoader
× 1
ImageScale
× 1
ModelSamplingSD3
× 1
CFGZeroStarAndInit
× 1
VHS_VideoCombine
× 1
ImageUpscaleWithModel
× 1
CLIPVisionLoader
× 1
官方标注的模型
RealESRGAN_x4.pthclip_vision_h_fp8_e4m3fn.safetensorsrife49.ptht5xxl_um_fp8_e4m3fn_scaled.safetensorswan2.1-i2v-14b-480p-Q3_K_M.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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1313 "## How to use (Wan 2.1 I2V 14B 480p GGUF, v2.0.1)\n\n**What it does:** start image + prompt -> short video with Wan 2.1 I2V 14B 480p (GGUF). Then RealESRGAN x4 upscale, resize to 1080 x 1920 and save as MP4. Made for low VRAM (from 4 GB with a small quant).\n\n**Inputs**\n1. **Load Image** (group \"Input image workflow\"): the first frame. CLIP Vision reads it (center crop).\n2. **Positive prompt**: the motion and camera you want.\n3. **Negative prompt**: empty by default. It also feeds NAG.\n\n**Models (group \"Models and Loras\")**\n- Unet Loader (GGUF): wan2.1-i2v-14b-480p-Q3_K_M.gguf. Any Wan 2.1 I2V 14B 480p quant works.\n- CLIP Loader: t5xxl_um_fp8_e4m3fn_scaled, type wan.\n- VAE Loader: wan_2.1_vae.\n- CLIP Vision Loader: clip_vision_h_fp8_e4m3fn.\n- Lora Loader Stack: 4 slots, all None. Wan 2.1 I2V 14B LoRAs only.\n\n**Important settings**\n- Size and length (WanImageToVideo): 480 x 848, 29 frames. Match the shape of your image.\n- Sampler (Asymmetric Tiled KSampler): seed 8895 (fixed), steps 40, cfg 6, dpmpp_2m / sgm_uniform, denoise 1.\n- Shift (ModelSamplingSD3): 6.\n- TeaCache: threshold 0.276, start 0.6, end 0.9, coefficients i2v_480. Higher threshold = faster but softer.\n- Extras on the model line: Enhance-A-Video 1.0, CFG-Zero*, NAG scale 11, Skip Layer Guidance (block 10, 0.5 to 0.8), RifleXRoPE k 4.\n- VAE Decode (Tiled): tile 256.\n- Output: RealESRGAN x4, Image Scale 1080 x 1920 (lanczos, center crop), RIFE VFI multiplier 1 (set 2 for twice the frames), Export 24 fps h264 crf 19.\n\n**Tips**\n- Out of memory: pick a smaller GGUF quant (see the Quantization note), use fewer frames, or lower the VAE Decode (Tiled) tile size.\n- Torch Compile needs Triton. If it errors, select TorchCompileModelWanVideoV2 and bypass it (Ctrl+B).\n- The Patch Sage Attention KJ node needs the sageattention package. Without it, bypass that node.\n- **Faster attention:** start ComfyUI with --use-sage-attention (less VRAM). --use-ck-attention changes the image for the same seed.\n- The Export node has pingpong on: the clip plays forward, then backward. Turn it off for a plain clip.\n- Settings help: CFG and shift: https://www.reddit.com/r/StableDiffusion/comments/1j2q0xw/dont_overlook_the_values_of_shift_and_cfg_on_wan\n- Common errors: https://civitai.com/articles/17240\n\n**Tested on:** RTX 3050 Laptop 4 GB (author). Checked against ComfyUI 0.45.3: the core nodes and their inputs match; not run there (the test server has neither the tiled_ksampler and Frame-Interpolation packs nor these models).\n"
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1337 "## Downloads - put each file in the ComfyUI folder shown\n\nClick a file name to download it. Folders are inside `ComfyUI/models/`. Full list: downloads.md in this folder.\n\n| Folder | File (click = download) | Size |\n|---|---|---|\n| `diffusion_models/` | [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) (other quants in the same repo) | |\n| `text_encoders/` | [t5xxl_um_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/calcuis/wan-gguf/resolve/main/t5xxl_um_fp8_e4m3fn_scaled.safetensors) | 6.7 GB |\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| `clip_vision/` | [clip_vision_h_fp8_e4m3fn.safetensors](https://huggingface.co/calcuis/wan-gguf/resolve/main/clip_vision_h_fp8_e4m3fn.safetensors) | 0.6 GB |\n| `upscale_models/` | [RealESRGAN_x4.pth](https://huggingface.co/ai-forever/Real-ESRGAN/resolve/main/RealESRGAN_x4.pth) | 0.07 GB |\n\n`rife49.pth` is downloaded by ComfyUI-Frame-Interpolation on first run.\n\n**Custom node packs:** gguf (calcuis), tiled_ksampler, ComfyUI-KJNodes, ComfyUI-VideoHelperSuite, rgthree-comfy, ComfyUI-Frame-Interpolation.\n\nOne command from the repo root: `python scripts/frizzy.py doctor wan2.1/gguf-lowvram`\n"
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