# HunyuanVideo — Open-Source Text-to-Video Generation by Tencent

> A systematic video generation framework using a dual-stream diffusion transformer to produce high-quality videos from text prompts with motion consistency.

## Install

Save as a script file and run:

# HunyuanVideo — Open-Source Text-to-Video Generation by Tencent

## Quick Use
```bash
git clone https://github.com/Tencent-Hunyuan/HunyuanVideo.git
cd HunyuanVideo
pip install -r requirements.txt
python sample_video.py --prompt "A cat walking in a garden" 
  --video-size 720 1280 --video-length 77
```

## Introduction
HunyuanVideo is an open-source video generation framework from Tencent that converts text descriptions into coherent, high-quality video clips. It uses a unified image-video diffusion transformer architecture trained on large-scale datasets to achieve strong temporal consistency and visual fidelity.

## What HunyuanVideo Does
- Generates video clips from natural language text prompts
- Produces temporally consistent motion across frames
- Supports configurable video resolution and duration
- Handles both realistic and stylized visual content
- Provides image-to-video generation capabilities

## Architecture Overview
HunyuanVideo employs a Dual-Stream to Single-Stream diffusion transformer (Hunyuan DiT) that processes spatial and temporal dimensions jointly. The model uses a 3D VAE for video encoding and decoding, a CLIP-based text encoder for prompt understanding, and a flow matching training objective for stable, high-quality generation.

## Self-Hosting & Configuration
- Clone the repository and install Python dependencies
- Download pretrained model weights from the Hugging Face model hub
- Requires a GPU with at least 60 GB VRAM for full-resolution generation (lower with quantization)
- Configure resolution, frame count, and inference steps via command-line arguments
- Supports FP16 and BF16 precision modes for memory optimization

## Key Features
- Unified image-and-video generation in a single model architecture
- Strong temporal coherence across long video sequences
- Open model weights for research and commercial use
- Configurable output resolution up to 1280x720
- Active development with v1.5 adding lightweight and faster variants

## Comparison with Similar Tools
- **Open-Sora** — community-driven Sora replication; HunyuanVideo offers a production-trained model with higher visual quality
- **Stable Video Diffusion** — image-to-video only; HunyuanVideo supports text-to-video generation directly
- **CogVideo** — earlier text-to-video model; HunyuanVideo improves on motion consistency and resolution
- **Wan2.1** — similar open-source video gen; HunyuanVideo uses a dual-stream DiT for richer temporal modeling

## FAQ
**Q: What GPU hardware is needed?**
A: Full-resolution inference requires around 60 GB VRAM (A100 or similar). Quantized modes can run on smaller GPUs with reduced quality.

**Q: Can it generate videos longer than a few seconds?**
A: The default configuration produces clips of a few seconds. Longer videos can be created by adjusting the frame count parameter.

**Q: Is the model free for commercial use?**
A: Yes, the model weights are released under the Tencent Hunyuan Community License which permits commercial applications.

**Q: Does it support image-to-video generation?**
A: Yes, you can provide a reference image along with a text prompt to generate a video that starts from that image.

## Sources
- https://github.com/Tencent-Hunyuan/HunyuanVideo
- https://aivideo.hunyuan.tencent.com/

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Author: Script Depot