A newer version of the Gradio SDK is available:
5.34.2
Models Overview
WanGP supports multiple video generation models, each optimized for different use cases and hardware configurations.
Wan 2.1 Text2Video Models
Please note that that the term Text2Video refers to the underlying Wan architecture but as it has been greatly improved overtime many derived Text2Video models can now generate videos using images.
Wan 2.1 Text2Video 1.3B
- Size: 1.3 billion parameters
- VRAM: 6GB minimum
- Speed: Fast generation
- Quality: Good quality for the size
- Best for: Quick iterations, lower-end hardware
- Command:
python wgp.py --t2v-1-3B
Wan 2.1 Text2Video 14B
- Size: 14 billion parameters
- VRAM: 12GB+ recommended
- Speed: Slower but higher quality
- Quality: Excellent detail and coherence
- Best for: Final production videos
- Command:
python wgp.py --t2v-14B
Wan Vace 1.3B
- Type: ControlNet for advanced video control
- VRAM: 6GB minimum
- Features: Motion transfer, object injection, inpainting
- Best for: Advanced video manipulation
- Command:
python wgp.py --vace-1.3B
Wan Vace 14B
- Type: Large ControlNet model
- VRAM: 12GB+ recommended
- Features: All Vace features with higher quality
- Best for: Professional video editing workflows
MoviiGen (Experimental)
- Resolution: Claims 1080p capability
- VRAM: 20GB+ required
- Speed: Very slow generation
- Features: Should generate cinema like video, specialized for 2.1 / 1 ratios
- Status: Experimental, feedback welcome
Wan 2.1 Image-to-Video Models
Wan 2.1 Image2Video 14B
- Size: 14 billion parameters
- VRAM: 12GB+ recommended
- Speed: Slower but higher quality
- Quality: Excellent detail and coherence
- Best for: Most Loras available work with this model
- Command:
python wgp.py --i2v-14B
FLF2V
- Type: Start/end frame specialist
- Resolution: Optimized for 720p
- Official: Wan team supported
- Use case: Image-to-video with specific endpoints
Wan 2.1 Specialized Models
FantasySpeaking
- Type: Talking head animation
- Input: Voice track + image
- Works on: People and objects
- Use case: Lip-sync and voice-driven animation
Phantom
- Type: Person/object transfer
- Resolution: Works well at 720p
- Requirements: 30+ steps for good results
- Best for: Transferring subjects between videos
Recam Master
- Type: Viewpoint change
- Requirements: 81+ frame input videos, 15+ denoising steps
- Use case: View same scene from different angles
Sky Reels v2
- Type: Diffusion Forcing model
- Specialty: "Infinite length" videos
- Features: High quality continuous generation
Wan Fun InP Models
Wan Fun InP 1.3B
- Size: 1.3 billion parameters
- VRAM: 6GB minimum
- Quality: Good for the size, accessible to lower hardware
- Best for: Entry-level image animation
- Command:
python wgp.py --i2v-1-3B
Wan Fun InP 14B
- Size: 14 billion parameters
- VRAM: 12GB+ recommended
- Quality: Better end image support
- Limitation: Existing loras don't work as well
Wan Special Loras
Safe-Forcing lightx2v Lora
- Type: Distilled model (Lora implementation)
- Speed: 4-8 steps generation, 2x faster (no classifier free guidance)
- Compatible: Works with t2v and i2v Wan 14B models
- Setup: Requires Safe-Forcing lightx2v Lora (see LORAS.md)
Causvid Lora
- Type: Distilled model (Lora implementation)
- Speed: 4-12 steps generation, 2x faster (no classifier free guidance)
- Compatible: Works with Wan 14B models
- Setup: Requires CausVid Lora (see LORAS.md)
Hunyuan Video Models
Hunyuan Video Text2Video
- Quality: Among the best open source t2v models
- VRAM: 12GB+ recommended
- Speed: Slower generation but excellent results
- Features: Superior text adherence and video quality, up to 10s of video
- Best for: High-quality text-to-video generation
Hunyuan Video Custom
- Specialty: Identity preservation
- Use case: Injecting specific people into videos
- Quality: Excellent for character consistency
- Best for: Character-focused video generation
Hunyuan Video Avater
- Specialty: Generate up to 15s of high quality speech / song driven Video .
- Use case: Injecting specific people into videos
- Quality: Excellent for character consistency
- Best for: Character-focused video generation, Video synchronized with voice
LTX Video Models
LTX Video 13B
- Specialty: Long video generation
- Resolution: Fast 720p generation
- VRAM: Optimized by WanGP (4x reduction in requirements)
- Best for: Longer duration videos
LTX Video 13B Distilled
- Speed: Generate in less than one minute
- Quality: Very high quality despite speed
- Best for: Rapid prototyping and quick results
Model Selection Guide
By Hardware (VRAM)
6-8GB VRAM
- Wan 2.1 T2V 1.3B
- Wan Fun InP 1.3B
- Wan Vace 1.3B
10-12GB VRAM
- Wan 2.1 T2V 14B
- Wan Fun InP 14B
- Hunyuan Video (with optimizations)
- LTX Video 13B
16GB+ VRAM
- All models supported
- Longer videos possible
- Higher resolutions
- Multiple simultaneous Loras
20GB+ VRAM
- MoviiGen (experimental 1080p)
- Very long videos
- Maximum quality settings
By Use Case
Quick Prototyping
- LTX Video 13B Distilled - Fastest, high quality
- Wan 2.1 T2V 1.3B - Fast, good quality
- CausVid Lora - 4-12 steps, very fast
Best Quality
- Hunyuan Video - Overall best t2v quality
- Wan 2.1 T2V 14B - Excellent Wan quality
- Wan Vace 14B - Best for controlled generation
Advanced Control
- Wan Vace 14B/1.3B - Motion transfer, object injection
- Phantom - Person/object transfer
- FantasySpeaking - Voice-driven animation
Long Videos
- LTX Video 13B - Specialized for length
- Sky Reels v2 - Infinite length videos
- Wan Vace + Sliding Windows - Up to 1 minute
Lower Hardware
- Wan Fun InP 1.3B - Image-to-video
- Wan 2.1 T2V 1.3B - Text-to-video
- Wan Vace 1.3B - Advanced control
Performance Comparison
Speed (Relative)
- CausVid Lora (4-12 steps) - Fastest
- LTX Video Distilled - Very fast
- Wan 1.3B models - Fast
- Wan 14B models - Medium
- Hunyuan Video - Slower
- MoviiGen - Slowest
Quality (Subjective)
- Hunyuan Video - Highest overall
- Wan 14B models - Excellent
- LTX Video models - Very good
- Wan 1.3B models - Good
- CausVid - Good (varies with steps)
VRAM Efficiency
- Wan 1.3B models - Most efficient
- LTX Video (with WanGP optimizations)
- Wan 14B models
- Hunyuan Video
- MoviiGen - Least efficient
Model Switching
WanGP allows switching between models without restarting:
- Use the dropdown menu in the web interface
- Models are loaded on-demand
- Previous model is unloaded to save VRAM
- Settings are preserved when possible
Tips for Model Selection
First Time Users
Start with Wan 2.1 T2V 1.3B to learn the interface and test your hardware.
Production Work
Use Hunyuan Video or Wan 14B models for final output quality.
Experimentation
CausVid Lora or LTX Distilled for rapid iteration and testing.
Specialized Tasks
- VACE for advanced control
- FantasySpeaking for talking heads
- LTX Video for long sequences
Hardware Optimization
Always start with the largest model your VRAM can handle, then optimize settings for speed vs quality based on your needs.