✨One-click Pod available on:✨

🟣 Runpod ComfyUI 0.19.0 CUDA 12.8 for 5090

🟣 Runpod ComfyUI 0.19.0 CUDA 12.4 for 4090

🟡 VastAI ComfyUI 0.19.0 CUDA 13.0 for 5090

🟡 VastAI ComfyUI 0.19.0 CUDA 13.0 for 4090

Just click on the link, choose a Video Card and the Template will install all you need + all my workflows.

Wan 2.2 Models are not included, you can install it using Civicomfy or ComfyUI-HuggingFace directly inside ComfyUI

OneClick-I2V-Story on Runpod Basic Tutorial

https://limewire.com/d/2TAty#No5eoN7WhU

☕️ buymeacoffee

IMPORTANT:

If you install RES4LYF node it will broke the MoEKSampler, to use it you have to use the KSampler included in that node.

🔥 02/28/26 UPDATE 🔥

✨ NEW NODES ✨

EASY MODEL DOWNLOAD FROM HUGGINGFACE

cd ComfyUI/custom_nodes
git clone https://github.com/huchukato/ComfyUI-HuggingFace.git

RIFE INTERPOLATION WITH TENSORRT

with Auto Install (CUDA 12/CUDA 13) and Auto Model Download

cd ComfyUI/custom_nodes
git clone https://github.com/huchukato/ComfyUI-RIFE-TensorRT-Auto.git

UPSCALER WITH TENSORRT

with Auto Install (CUDA 12/CUDA 13) and Auto Model Download

cd ComfyUI/custom_nodes
git clone https://github.com/huchukato/ComfyUI-Upscaler-TensorRT-Auto.git

✨MY QWEN3-VL NODE IS FINALLY IN THE MANAGER✨

Just search for "QwenVL-Mod" to install it

or dowload it from GitHub: QwenVL-Mod: Enhanced Vision-Language

ComfyUI-QwenVL-Mod - Enhanced Vision-Language with WAN 2.2

Version 2.2.4 (2026/03/13) - 🎬 Critical I2V Timeline Fixes & NSFW Presets Optimization

🌟 What is ComfyUI-QwenVL-Mod?

A powerful enhanced vision-language node for ComfyUI that combines Qwen3-VL models with professional WAN 2.2 video generation workflows. Features multilingual support, visual style detection, and NSFW capabilities for professional AI content creation.

Think: "Your all-in-one solution for intelligent prompt enhancement and video generation with cutting-edge AI models!"

🎬 Key Features

🚀 WAN 2.2 Video Generation

• Text-to-Video (T2V): Professional 5-second video generation

• Image-to-Video (I2V): Advanced image animation with style detection

• Story Generation: 20-second continuous videos with 4 narrative segments

• Storyboard Workflows: Seamless storyboard-to-storyboard generation

• Cinematic Video: Professional cinematography specifications

🌐 Enhanced Capabilities

• Multilingual Support: Process prompts from any language (Italian, English, etc.)

• Visual Style Detection: 12+ artistic styles (anime, 3D, pixel art, puppet animation, etc.)

• Smart Prompt Caching: Performance optimization with Fixed Seed Mode

• GGUF Backend: Efficient local model inference with quantization support

• NSFW Support: Comprehensive content generation without restrictions

🧠 Intelligent Features

• Auto-Prompt Enhancement: Automatically enhance user prompts for optimal generation

• Professional Cinematography: Built-in specifications for lighting, camera angles, shot types

• Timeline Structure: Precise 5-second timeline with frame-by-frame descriptions

• Keep Last Prompt: Generate once, preserve results while changing inputs

🎯 What's New in v2.2.4 - CRITICAL I2V TIMELINE FIXES

🚨 Major I2V Timeline (20s) Fixes

• ✅ Style Coherence: Fixed AI changing anime→realism mid-sequence

• ✅ Character Stability: Fixed characters disappearing/appearing incorrectly

• ✅ Natural Lighting: Fixed AI adding artificial lights not in image

• ✅ Timeline Structure: Fixed continuous numbering (6,7,8...) instead of 0-5 restart

• ✅ Format Consistency: Fixed missing parentheses and unwanted labels

• ✅ Output Format: Each prompt starts directly with timeline markers

🔧 NSFW Presets Optimization

• ✅ Complete Specifications: All 8 NSFW presets now include full NSFW descriptions

• ✅ Emoji Display: Restored proper emoji rendering (🍿🎥🎬📖)

• ✅ Clear Instructions: Removed confusing recommendations from presets

• ✅ User Guide: Token settings guide created for workflow optimization

📋 Technical Improvements

• ✅ Timeline Markers: Correct (At X seconds: ...) format for all 4 prompts

• ✅ Character Continuity: Natural progression without forced artificial presence

• ✅ Lighting Rules: Logical progression instead of absolute prohibitions

• ✅ Style Detection: Consistent style application across all timeline segments

🎯 Model Recommendations

• Qwen3-VL-8B: Recommended for I2V Timeline (20s) complex sequences

• Qwen3-VL-4B: Sufficient for I2V Scene (5s) single prompts

• Token Settings: 2048+ for 20s timeline, 1024+ for 5s prompts

🎯 What's New in v2.2.3

• CUDA 13 Compatibility: Fixed crashes caused by conflicting unload operations

• Parameter Cleanup: Removed redundant unload_after_run from all nodes

• Bug Fixes: Resolved "missing required positional argument" errors

• Memory Management: Streamlined VRAM cleanup with VRAM Cleanup node

• Documentation: Updated all README files with new memory features

• Credits: Added community credits for feedback and testing

🎯 What's New in v2.2.2

🚀 Critical T2V/I2V Workflow Fixes

• Batch Processing: Fixed critical T2V → GGUF issue with batch images

• Frame Detection: Added automatic batch detection and individual frame processing

• Video Support: Enhanced video frame processing with proper shape handling

• Debug Enhanced: Comprehensive logging for batch processing troubleshooting

🔄 Same Model Reuse Fix

• Conflict Resolution: Fixed crash when using same model between T2V and I2V nodes

• Memory Management: Enhanced cleanup with CUDA synchronization and timing

• Signature Mismatch: Resolved different signature patterns between nodes

• Aggressive Cleanup: Forced complete VRAM cleanup before model reload

🔧 keep_model_loaded Enhancement

• Missing Parameter: Added keep_model_loaded to PromptEnhancer node

• Consistent Behavior: Both GGUF and PromptEnhancer now have identical memory management

• Conditional Cleanup: Proper cleanup based on keep_model_loaded setting

• User Control: Full control over memory usage vs performance

🚨 CRITICAL BUG FIXES - v2.2.4

🎬 I2V Timeline (20s) - COMPLETELY FIXED

Before v2.2.4:

• ❌ Anime style changed to realism mid-sequence

• ❌ Characters disappeared/appeared randomly

• ❌ AI added artificial lights not in image

• ❌ Timeline numbering: 6,7,8... instead of 0-5 restart

• ❌ Missing parentheses and unwanted "Prompt 1:" labels

After v2.2.4:

• ✅ Perfect Style Coherence: Anime stays anime, realism stays realism

• ✅ Character Stability: Same characters throughout all 4 prompts

• ✅ Natural Lighting: Only lights visible in image, logical progression

• ✅ Correct Timeline: Each prompt uses 0-5 seconds format

• ✅ Clean Output: Proper (At X seconds: ...) format, no labels

🔥 NSFW Presets - ENHANCED & FIXED

• ✅ Complete Specifications: All 8 presets with full explicit descriptions

• ✅ Emoji Display: Proper 🍿🎥🎬📖 icons (no more unicode codes)

• ✅ User-Friendly: Removed confusing technical recommendations

• ✅ Token Guide: Workflow note for optimal settings

🎯 Result: Perfect I2V Timeline generation every time!

🎬 WAN 2.2 Story Workflow - Revolutionary AI Storytelling

📖 AI Story Generation

• 4-Segment Videos: Automatic 20-second videos (4 × 5-second segments)

• Narrative Continuity: Perfect story flow between segments

• NSFW Support: Enhanced adult content generation

• Timeline-Free: Natural storytelling without time markers

🔄 Smart Auto-Split

• Story Split Node: Intelligent prompt separation technology

• Auto-Detection: Handles any separator format automatically

• 4-Output Guarantee: Always produces exactly 4 prompts

• Debug Mode: Built-in troubleshooting information

📦 Installation

Requirements

• ComfyUI: v0.13.0+

• GPU: 8GB+ VRAM (16GB+ recommended)

• System: Windows/Linux/Mac

• Python: 3.10+ (or use provided Docker environment)

Docker/Cloud Ready

• RunPod: Pre-configured templates available

• VastAI: Optimized instances ready

• Local: Docker support included

Quick Install

1. Download: ComfyUI-QwenVL-Mod (latest version)

2. Extract to ComfyUI/custom_nodes/ComfyUI-QwenVL-Mod

3. Restart ComfyUI

4. Load included workflows

🎮 Usage Examples

Basic Image-to-Video

1. Load WAN2.2-I2V-AutoPrompt.json

2. Upload your image

3. Select model (HF or GGUF)

4. Generate enhanced video

Basic Text-to-Video

1. Load WAN2.2-T2V-AutoPrompt.json

2. Input your text prompt

3. Select model (HF or GGUF)

4. Generate enhanced video

Image-to-Video with Style

1. Load WAN2.2-I2V-AutoPrompt.json

2. Upload your image

3. Enable style detection

4. Generate animated video

AI Story Generation

1. Load WAN2.2-I2V-AutoPrompt-Story.json

2. Input your story idea

3. Auto-split into 4 segments

4. Generate 20-second story video

🔧 Technical Specifications

⚡ Performance

• Context: 65,536 tokens (8B models)

• Memory: Optimized VRAM usage

• Stability: Crash-free operation

• Speed: Fast generation times

🎨 Model Support

• Qwen3-VL 4B: 7 GGUF variants (2.38GB-4.28GB)

• Qwen3-VL 8B: 7 GGUF variants (4.8GB-8.71GB)

• HF Models: Josiefed and official variants

• Quantization: Q4_K_S, Q5_K_S for VRAM efficiency

🌐 Multilingual Capabilities

• Input Languages: Any language supported

• Auto-Translation: Automatic translation to optimized English

• Style Detection: Works with multilingual prompts

• Cultural Adaptation: Context-aware prompt enhancement

🎯 Included Workflows

🍿 WAN 2.2 Presets

• 🍿 Wan 2.2 I2V Timeline: Image-to-video with timeline structure

• 🎥 Wan 2.2 I2V Scene: Image-to-video with professional specs

• 🍿 Wan 2.2 T2V Timeline: Text-to-video with timeline structure

• 🎥 Wan 2.2 T2V Scene: Text-to-video with professional specs

• 🎬 Wan 2.2 I2V Timeline: 20-second multi-segment continuity

• 📖 Wan 2.2 I2V Scene: 20-second single scene with cinematography

🔥 Advanced Features

• NSFW Enhancement: Uncensored content generation

• Professional Lighting: 8 light types + 9 qualities

• Camera Control: 6 shot types + 5 compositions

• Color Grading: 4 tone options

🎨 Visual Style Detection

Automatically detects and enhances:

• Photorealistic style - Realistic lighting, natural textures, lifelike details

• Anime style - Japanese animation aesthetics with vibrant colors

• Cartoon style - Bold outlines, flat colors, exaggerated expressions

• 3D animation style - Computer-generated 3D rendering characteristics

• Fantasy style - Magical elements, ethereal lighting, imaginative atmosphere

• Artistic portrait style - Painterly qualities, artistic brushwork, stylized composition

🔥 NSFW Content Support

Enhanced Generation

• Explicit Content: Uncensored adult descriptions

• Detailed Scenes: 8-12 sentences per segment

• Natural Progression: Smooth story flow

• Style Adaptation: Automatic visual style matching

• Quality: Consistent characters & scenes

Professional Applications

• Adult Content: Industry-standard generation

• Artistic Nudity: Classical art styles

• Educational: Anatomy and artistic study

• Creative: Artistic expression

🚀 Why Choose ComfyUI-QwenVL-Mod?

🎬 For Content Creators

• Storytelling: Create compelling narratives

• Efficiency: One prompt → complete video

• Quality: Professional video output

• Flexibility: Any genre, any style

🔥 For NSFW Content

• Explicit: Uncensored generation

• Detailed: Rich scene descriptions

• Continuous: Smooth story flow

• Natural: Realistic progression

⚡ For Power Users

• Customizable: Easy to modify

• Extendable: Add more segments

• Integrable: Works with existing setups

• Optimized: Maximum performance

🌟 What Makes This Special?

• First: Complete AI story system with vision enhancement

• Smart: Intelligent prompt splitting and enhancement

• Complete: End-to-end solution from text to video

• Optimized: Performance-tuned for professional use

• Ready: Works out-of-the-box with included workflows

🎬 Create Amazing AI Videos Today!

Transform your ideas into stunning videos with the power of Qwen3-VL vision enhancement and WAN 2.2 video generation.

Perfect for creators, artists, and professionals looking for the ultimate AI video enhancement tool! 🌟

Built with ❤️ for the ComfyUI community

🔶 All the images used to create the videos in the gallery are generated with PimpMyPony 🔶

The new version is out today, with a brand new anime style ✨

WORKFLOWS TESTED ON:

• ComfyUI 0.17.1

• Python 3.12.12

• Pytorch 2.9.1 + CUDA 13.0

🟣 Credits

This workflows are intended to be used with the models by taek75799 as they follow the structure of Dynamic Prompts you can find under these models:

WAN 2.2 Enhanced NSFW | SVI | camera prompt adherence (Lightning Edition) I2V and T2V fp8 GGUF

🟣 Other tested models:

• Smooth Mix Wan 2.2 14B (I2V/T2V) by DigitalPastel | GGUF versions by Santodan

• Wan2.2-Remix (T2V&I2V) by FX_FeiHou | GGUF versions by Santodan

Thanks to all the users who are commenting and helping me improve the workflows ❤️

🔖 T2V-I2V AUTOPROMPT

🛑 Experimental WF 🛑

Start with a T2V prompt and extend the generated video with I2V

This workflow requires both T2V and I2V Wan 2.2 Models

🔖 SVI I2V AUTOPROMPT

Thanks to taek75799 for his models ❤️

• NSFW SVI CF FP8 High

• NSFW SVI CF FP8 Low

SVI LORAS:

• SVI High

• SVI Low

LIGHTX2V LoRaS are not included in the model

🔖 FULL I2V AUTOPROMPT

Complete workflow that includes:

• Long Video Generation [from 5 to 20 seconds]

• Auto Prompting [Qwen3-VL]

• Upscale [2xLexicaRRDBNet and Tensorrt]

• Frame Interpolation [30fps and 60fps for img2vid | 24fps and 50fps for MMAudio]

• MMAudio [NSFW Unlocked]

📝 AUTO PROMPT

• Prompt Description Box [Multilanguage]: Just write your idea and the LLM will do the rest, formatting the prompt in the dynamic prompt format used in the Wan 2.2 models

• Final Prompt Preview: Shows up the final prompt

🔶 QWEN3-VL NODE FOR GGUF MODELS 🔶

🔖 To use the Qwen3-VL GGUF Quantized models you have to install llama-cpp-python

If you are not comfortable in manual install the llama, just go with the normal version inside Full-I2V-LongVideo

1. 🛑 STOP COMFYUI

1. 📂 Activate the ComfyUI Virtual Enviroment

In your ComfyUI root installation folder type:

on Windows:

Command Prompt:

\venv\Scripts\activate.bat

or Power Shell:

\venv\Scripts\Activate.ps1

on Linux:

. /venv/bin/activate

If you use ComfyUI Desktop:

Click on Console and then on Terminal

1. ⬇️ Install llama-cpp-python

pip install --upgrade --force-reinstall --no-cache-dir "llama-cpp-python @ git+https://github.com/JamePeng/llama-cpp-python.git"

1. 🔄 Restart ComfyUI and enjoy

📝 SWITCH CLIP

By default the WF uses the GGUF node to load quantized Clip, if you wanna switch to the NSFW Clip model, you have to bypass the GGUF node and connect the other Clip loader to the "Set_CLIP"

ACCELERATION:

Triton is disabled by default, you can enable it by opening the first Subgraph

Inside the workflow you will find all the links to download the models you will need

That's all, hope you enjoy ^^