Workflow Wan 2 1 Image To Video 14b 480p Gguf

workflow_wan_2_1_image_to_video_14b_480p_gguf

Imported workflow skill generated from Wan 2.1 Image to Video 14B 480p GGUF.json.

Family

• video_t2v_i2v_avatar

Inputs

• Optional runtime overrides supported by run(...):
  • prompt
  • negative_prompt
  • width, height
  • seed, steps, cfg
  • sampler_name, scheduler, denoise
  • server, headers, api_prefix

Outputs

• Returns JSON with:
  • status
  • prompt_id
  • output_images

Model Requirements

• clip: umt5_xxl_fp8_e4m3fn_scaled.safetensors -> models/clip
• vae: wan_2.1_vae.safetensors -> models/vae
• diffusion_model: wan2.1-i2v-14b-480p-Q4_0.gguf -> models/diffusion_models

Custom Node Requirements

• comfyui-videohelpersuite

Links

• https://discord.com/invite/gggpkVgBf3
• https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors?download=true
• https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true
• https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true
• https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf/resolve/main/wan2.1-i2v-14b-480p-Q4_0.gguf?download=true
• https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf/tree/main
• https://www.youtube.com/@pixaroma

Routing Metadata

• Family: video_t2v_i2v_avatar
• Input modalities: image, text_prompt
• Output modalities: video/mp4
• Model families: wan
• Node count: 14
• Complexity score: 8
• Resource profile: high
• Estimated runtime: slow (often 2-6 min depending on model/server load)
• Max latent resolution hint: NonexNone
• Max sampler steps hint: 30

Detected Models

• clip: umt5_xxl_fp8_e4m3fn_scaled.safetensors -> models/clip
• vae: wan_2.1_vae.safetensors -> models/vae
• diffusion_model: wan2.1-i2v-14b-480p-Q4_0.gguf -> models/diffusion_models

Detected Custom Nodes

• comfyui-videohelpersuite

Runtime Warnings

• Large model(s) detected; ensure enough VRAM and disk space.
• Uses custom nodes; missing nodes can cause validation/runtime failures.
• Video workflow: usually slower and VRAM-intensive than still-image workflows.