
WAN 2.x inference with ComfyUI

A streamlined and automated environment for running ComfyUI with WAN 2.x video models, optimized for use on RunPod.io
🔧 Features
- Automatic model and LoRA downloads via environment variables.
- Supports advanced workflows for video generation and enhancement using pre-installed custom nodes.
- Compatible with high-performance NVIDIA GPUs.
🔧 Built-in authentication
- ComfyUI
- Code Server
- Hugging Face API
- CivitAI API
📦 Template Deployment
👉 One-click Deploy on RunPod WAN 2.2 t2v (lightx2v)
👉 One-click Deploy on RunPod WAN 2.2 i2v (lightx2v)
👉 One-click Deploy on RunPod WAN 2.2 animate (lightx2v)
👉 One-click Deploy on RunPod WAN 2.2 lightx2v Dyno
👉 One-click Deploy on RunPod WAN 2.2 v2v Lucy Edit
Workflows
💻 Hardware Requirements
T2V-A14B/I2V-A14B (high/low)
- precision fp16
- video settings 1024x768 122 frames
| Recommended GPU |
VRAM |
RAM |
| L40S, RTX 6000 Ada |
40 GB |
90GB |
Animate
- precision fp16
- video settings 1024x768 77 chunks/Sampler
| Recommended GPU |
VRAM |
RAM |
| L40S, RTX 6000 Ada |
40 GB |
105GB |
Storage
| Component |
Minimum |
| Volume Storage |
90GB (/workspace) |
| Pod Storage |
15GB |
⚙️ Environment Variables
ComfyUI Configuration
| Variable |
Description |
COMFYUI_EXTRA_ARGUMENTS |
Additional arguments for ComfyUI CLI |
Authentication Tokens
| Token Source |
Variable |
| Code Server |
PASSWORD |
| Hugging Face |
HF_TOKEN |
| CivitAI |
CIVITAI_TOKEN |
Hugging Face Model Configuration
| Model Type |
Model |
Safetensors/GGUF |
| Diffusion Model |
HF_MODEL_DIFFUSION_MODELS[1-10] |
HF_MODEL_DIFFUSION_MODELS_FILENAME[1-10] |
| Checkpoints |
HF_MODEL_CHECKPOINTS[1-10] |
HF_MODEL_CHECKPOINTS_FILENAME[1-10] |
| Text Encoders |
HF_MODEL_TEXT_ENCODERS[1-10] |
HF_MODEL_TEXT_ENCODERS_FILENAME[1-10] |
| Clip Vision |
HF_MODEL_CLIP_VISION[1-10] |
HF_MODEL_CLIP_VISION_FILENAME[1-10] |
| Audio Encoders |
HF_MODEL_AUDIO_ENCODERS[1-10] |
HF_MODEL_AUDIO_ENCODERS_FILENAME[1-10] |
| Model patches |
HF_MODEL_PATCHES[1-10] |
HF_MODEL_PATCHES_FILENAME[1-10] |
| VAE |
HF_MODEL_VAE[1-10] |
HF_MODEL_VAE_FILENAME[1-10] |
| Upscalers |
HF_MODEL_UPSCALER[1-10] |
HF_MODEL_UPSCALER_PTH[1-10] |
| Loras |
HF_MODEL_LORA[1-10] |
HF_MODEL_LORA_FILENAME[1-10] |
| VLM/mmproj |
HF_MODEL_VL[1-10] |
HF_MODEL_VL_FILENAME[1-10] |
| SAM segmentation |
HF_MODEL_SAMS[1-10] |
HF_MODEL_SAMS_FILENAME[1-10] |
CivitAI LORAs
| Variable |
Description |
CIVITAI_MODEL_LORA_URL[1-10] |
Direct download link for LoRAs |
Workflows
| Variable |
Description |
WORKFLOW[1-50] |
download link (compressed or plain) |
🌐 Network Services
| Service |
Port |
Access Type |
| ComfyUI |
8188 |
Web |
| Code Server |
9000 |
Web |
| SSH/SCP |
22 |
Terminal |
📚 Tutorials & Resources
🧩 Pre-Installed Custom Nodes
Interface
Video/Upscale
Controlnet
Flow
Segmentation
Wan
Animate
Sampling
📦 Model Sources
⚙️ Setup
| Component |
Version |
| OS |
Ubuntu 22.04 x86_64 |
| Python |
3.11.x |
| PyTorch |
2.8.0 |
| CUDA |
12.9 |
| Triton |
3.4.0 |
| onnxruntime-gpu |
1.22.x |
| ComfyUI |
0.3.68 |
| CodeServer |
Latest |
⚙️ Installed Attentions
Wheels
| Package |
Version |
| flash_attn |
2.8.3 |
| sageattention |
2.2.0 |
Build for
| Processor |
Compute Capability |
SM |
| A40 |
8.6 |
sm_86 |
| L40S |
8.9 |
sm_89 |