Wan2.1/docs/MODELS.md

Models Overview

WanGP supports multiple video generation models, each optimized for different use cases and hardware configurations.

Text-to-Video Models

Wan 2.1 Models

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

Wan Vace 14B

• Type: Large ControlNet model
• VRAM: 12GB+ recommended
• Features: All Vace features with higher quality
• Best for: Professional video editing workflows

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
• 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

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

Other Models

Sky Reels v2

• Type: Diffusion Forcing model
• Specialty: "Infinite length" videos
• Features: High quality continuous generation
• Note: Uses causal attention (SDPA only)

MoviiGen (Experimental)

• Resolution: Claims 1080p capability
• VRAM: 20GB+ required
• Speed: Very slow generation
• Status: Experimental, feedback welcome

CausVid (Via Lora)

• Type: Distilled model (Lora implementation)
• Speed: 4-12 steps generation, 2x faster
• Compatible: Works with Wan 14B models
• Setup: Requires CausVid Lora (see LORAS.md)

Image-to-Video Models

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
• Command: python wgp.py --i2v-14B

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

FLF2V

• Type: Start/end frame specialist
• Resolution: Optimized for 720p
• Official: Wan team supported
• Use case: Image-to-video with specific endpoints

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

1. LTX Video 13B Distilled - Fastest, high quality
2. Wan 2.1 T2V 1.3B - Fast, good quality
3. CausVid Lora - 4-12 steps, very fast

Best Quality

1. Hunyuan Video - Overall best t2v quality
2. Wan 2.1 T2V 14B - Excellent Wan quality
3. Wan Vace 14B - Best for controlled generation

Advanced Control

1. Wan Vace 14B/1.3B - Motion transfer, object injection
2. Phantom - Person/object transfer
3. FantasySpeaking - Voice-driven animation

Long Videos

1. LTX Video 13B - Specialized for length
2. Sky Reels v2 - Infinite length videos
3. Wan Vace + Sliding Windows - Up to 1 minute

Lower Hardware

1. Wan Fun InP 1.3B - Image-to-video
2. Wan 2.1 T2V 1.3B - Text-to-video
3. Wan Vace 1.3B - Advanced control

Performance Comparison

Speed (Relative)

1. CausVid Lora (4-12 steps) - Fastest
2. LTX Video Distilled - Very fast
3. Wan 1.3B models - Fast
4. Wan 14B models - Medium
5. Hunyuan Video - Slower
6. MoviiGen - Slowest

Quality (Subjective)

1. Hunyuan Video - Highest overall
2. Wan 14B models - Excellent
3. LTX Video models - Very good
4. Wan 1.3B models - Good
5. CausVid - Good (varies with steps)

VRAM Efficiency

1. Wan 1.3B models - Most efficient
2. LTX Video (with WanGP optimizations)
3. Wan 14B models
4. Hunyuan Video
5. MoviiGen - Least efficient

Model Switching

WanGP allows switching between models without restarting:

1. Use the dropdown menu in the web interface
2. Models are loaded on-demand
3. Previous model is unloaded to save VRAM
4. 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.