Comparison of Open-Source Video Generation Models (CogVideoX vs Mochi vs LTX Video vs HunyuanVideo)
- Video Generation Overview
- Video Generation Key Comparison Points
- Example Demonstrations
- Introduction to Open-Source Video Models
- Usage in ComfyUI
- Online Run
Video Generation Overview
With the rapid development of generative AI technology, the field of video generation has seen the emergence of several open-source models that provide developers and researchers with powerful tools for high-quality content creation. Currently, representative open-source video generation models include CogVideoX, Mochi, and LTX Video, as well as the newly released HunyuanVideo. These models each have unique features in terms of quality, generation speed, and ecosystem support. This article primarily compares the first three models, as HunyuanVideo is newly released and lacks comprehensive testing and ecosystem integration, thus not included in the full evaluation.
Video GenerationKey Comparison Points
Best Image-to-Video Quality: CogVideoX
Best Text-to-Video Quality: Mochi
Best Generation Speed: LTX Video
Best Ecosystem Completeness: CogVideoX supports Lora
Largest Parameter Scale: HunyuanVideo with 13 billion, surpassing Mochi's 10 billion
Example Demonstrations
CogVideoX Image to Video
CogVideoX-Fun Video to Video
CogVideoX 1.5 Image to Video
LTX Text to Video
LTX Video to Video
LTX Image to Video
LTX Video to Video (ref Image)
Mochi Text to Video
Mochi Edit
DimensionX + CogVideoX Image to Video
Introduction to Open-Source Video Models
CogVideoX
CogVideoX is an open-source text-to-video generation model developed by the Zhipu team at Tsinghua University, combining 3D VAE and expert Transformer technology. It supports generating high-quality short videos from text or image input, optimizing memory usage and precision. With the LoRA module, CogVideoX can extend functionalities according to user needs, offering high adaptability.
homepage: https://github.com/THUDM/CogVideo
Mochi
Mochi is a high-performance text-to-video generation model launched by Genmo, featuring a scale of 10 billion parameters. It uses an asymmetric diffusion Transformer (AsymmDiT) architecture, excelling in text consistency. Mochi supports generating 480p videos (with plans for HD support in the future) and provides impressive generation effects through efficient compression and decoding technology. Mochi 1 represents a significant advancement in the open-source video generation field, being the largest video generation model ever publicly released.
homepage: https://www.genmo.ai/blog
LTX Video
LTX Video is an open-source model launched by Lightricks, focusing on efficient video generation. Its optimized architecture allows for extremely fast generation speeds, running smoothly even on consumer-grade hardware like the RTX 4090. The model integrates ComfyUI nodes, enhancing user development and deployment experience. LTX-Video capable of generating high-quality videos in real-time.
homepage: https://github.com/Lightricks/LTX-Video
HunyuanVideo
HunyuanVideo is a new text-to-video generation model developed by Tencent, part of the Hunyuan large model, adopting MoE architecture and cross-frame text guidance modules. It has significant temporal consistency and long-sequence generation capabilities, suitable for complex cross-modal applications. HunyuanVideo, with over 13 billion parameters, is the largest among all open-source models.
homepage: https://aivideo.hunyuan.tencent.com