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These workflows make it easier to install Wan Video more info here 👇
Runtime profile
Source excerpt
These workflows make it easier to install Wan Video more info here 👇
Estimated VRAM requirement
Estimate unavailable
9.72 GB across 1 of 4 model files. Model file total + 25% loading overhead + 2 GB execution buffer, rounded up.
Requirements
5 requirementsAI-generated commentary
AI-generated explanation based on source and configuration details. Suggestions are clearly labeled.
This workflow is for installing Wan Video and supports image-to-video generation: it takes an image and text and lists a WEBM video as its output.
The listed 17-node flow loads an image, encodes vision and text inputs, runs Wan image-to-video processing and sampling, decodes with a tiled VAE, and saves WEBM.
The meaningful inputs are an image and text; the listed output format is WEBM video.
The workflow is published by Tingtingin and uses Wan Video as its base model.
Required model files are `clip_vision_h.safetensors`, `umt5_xxl_fp8_e4m3fn_scaled.safetensors`, `wan_2.1_vae.safetensors`, and `wan2.1-i2v-14b-480p-Q4_K_S.gguf`.
The setup also lists a node pack named `comfyui-gguf`.
The listed model details use Wan 2.1 I2V 14B with GGUF, FP8, Q4, and Q4_K labels.
Before use, check that all four model files and `comfyui-gguf` are available under the listed names.
Suggestion · not verified
No license is specified for this workflow.
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Sources
1 sourceSource excerpts
1 excerptSource context: 1256 downloads · Type Workflows · Base model Wan Video
Vision model · Unknown
umt5_xxl_fp8_e4m3fn_scaled.safetensors
File unverifiedText encoder · SAFETENSORS · Unknown
VAE · Unknown
Checkpoint · 9.72 GB · GGUF · Unknown
comfyui-gguf
PossibleNode pack · Registry
