How do I install the Workflow Wan 2 2 I2v 14b Gguf skill?

Run npx skillmds@latest add steliosot/workflow-wan-2-2-i2v-14b-gguf in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Workflow Wan 2 2 I2v 14b Gguf skill do?

Workflow wrapper imported from `Wan 2.2 I2V 14B GGUF.json`. It is listed under Productivity on SkillMD.

Is Workflow Wan 2 2 I2v 14b Gguf safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Workflow Wan 2 2 I2v 14b Gguf?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Workflow Wan 2 2 I2v 14b Gguf free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Workflow Wan 2 2 I2v 14b Gguf?

steliosot (@steliosot) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Workflow Wan 2 2 I2v 14b Gguf by steliosot

Name: Workflow Wan 2 2 I2v 14b Gguf
Author: steliosot

File contents

workflow_wan_2_2_i2v_14b_gguf

Imported workflow skill generated from Wan 2.2 I2V 14B 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: wan2.2_i2v_high_noise_14B_Q4_K_M.gguf -> models/diffusion_models
diffusion_model: wan2.2_i2v_low_noise_14B_Q4_K_M.gguf -> models/diffusion_models

Custom Node Requirements

ComfyUI-GGUF
comfyui-videohelpersuite

Routing Metadata

Family: video_t2v_i2v_avatar
Input modalities: image, text_prompt
Output modalities: video/mp4
Model families: sd3, wan
Node count: 18
Complexity score: 9
Resource profile: very_high
Estimated runtime: heavy (can exceed 6 min; best on high-VRAM GPU)
Max latent resolution hint: NonexNone
Max sampler steps hint: None

Detected Models

clip: umt5_xxl_fp8_e4m3fn_scaled.safetensors -> models/clip
vae: wan_2.1_vae.safetensors -> models/vae
diffusion_model: wan2.2_i2v_high_noise_14B_Q4_K_M.gguf -> models/diffusion_models
diffusion_model: wan2.2_i2v_low_noise_14B_Q4_K_M.gguf -> models/diffusion_models

Detected Custom Nodes

ComfyUI-GGUF
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.

---name: workflow-wan-2-2-i2v-14b-ggufdescription: Workflow wrapper imported from `Wan 2.2 I2V 14B GGUF.json`.---# workflow_wan_2_2_i2v_14b_ggufImported workflow skill generated from `Wan 2.2 I2V 14B 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`: `wan2.2_i2v_high_noise_14B_Q4_K_M.gguf` -> `models/diffusion_models`- `diffusion_model`: `wan2.2_i2v_low_noise_14B_Q4_K_M.gguf` -> `models/diffusion_models`## Custom Node Requirements- `ComfyUI-GGUF`- `comfyui-videohelpersuite`## Links- https://discord.com/invite/gggpkVgBf3- https://docs.comfy.org/tutorials/video/wan/wan2_2- 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/Wan-AI/Wan2.2-I2V-A14B- https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/resolve/main/wan2.2_i2v_high_noise_14B_Q4_K_M.gguf?download=true- https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/resolve/main/wan2.2_i2v_low_noise_14B_Q4_K_M.gguf?download=true- https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-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: `sd3, wan`- Node count: `18`- Complexity score: `9`- Resource profile: `very_high`- Estimated runtime: `heavy (can exceed 6 min; best on high-VRAM GPU)`- Max latent resolution hint: `None`x`None`- Max sampler steps hint: `None`## Detected Models- `clip`: `umt5_xxl_fp8_e4m3fn_scaled.safetensors` -> `models/clip`- `vae`: `wan_2.1_vae.safetensors` -> `models/vae`- `diffusion_model`: `wan2.2_i2v_high_noise_14B_Q4_K_M.gguf` -> `models/diffusion_models`- `diffusion_model`: `wan2.2_i2v_low_noise_14B_Q4_K_M.gguf` -> `models/diffusion_models`## Detected Custom Nodes- `ComfyUI-GGUF`- `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.

Frequently asked questions

Workflow Wan 2 2 I2v 14b Gguf