1. Abstract
HunyuanVideo 1.5 is an open-source text/image generation video model from Tencent's Hunyuan team, based on the DiT architecture, with parameters of about 8.3B. Its main feature is that it is memory-friendly, can run on a consumer-grade GPU with about 14GB of video memory, natively supports 5–10 seconds of 480p/720p video generation, and supports a super-resolution module upgraded to 1080p, suitable for content creation, product display and model research and other scenarios.
2. Core features
- Lightweight DiT architecture: 8.3B parameter volume, easier to deploy locally than similar large models.
- HD output capability: Support 480p/720p native video and obtain 1080p image quality through super-resolution.
- T2V and I2V in one: Support both text generation video and image generation video workflows.
- Efficient reasoning optimization: Combine spatio-temporal compression with efficient attention algorithms to take into account both quality and speed.
- Chinese and English prompts are friendly: Design coding and prompt enhancement strategies for Chinese and English prompts.
3. Installation
- Preparation environment: Linux, Python 3.10+, PyTorch with CUDA support, and NVIDIA GPU with more than 14GB of video memory.
2. Clone warehouse: git clone https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5.git && cd HunyuanVideo-1.5.
3. Install dependencies: Use pip install -r requirements.txt to install basic dependencies, and you can choose to install acceleration components such as FlashAttention according to the documentation.
- Download weights: Follow the official instructions to obtain the weights of the main model and the super-resolved model from Hugging Face or the script provided.
4. Typical use cases
- Copywriting generation short video: Convert product selling points and plot scripts into 5-10 second preview videos for solution review and delivery testing.
- Image generation dynamic poster: based on the brand's main visual or illustration, expand into a short video with lens movement and light and shadow changes with one click.
- AIGC tool integration: Access to web pages, desktops or workflow tools, providing users with one-click Wensheng video capabilities.
- Research baseline model: used to verify the effect of new attention mechanism, distillation and acceleration algorithm in video generation tasks.
5. Ecology and Competing Products
- Ecological aspect: Provide the official website Project Page, GitHub repository, Hugging Face model cards, technical reports and prompt guides, and the community has integrated visual workflows such as ComfyUI.
- Comparison of competing products: Compared with large open source video models such as Wan and OpenSora, HunyuanVideo 1.5 emphasizes the balance of "small parameter scale + low memory threshold", which is suitable for local experiments by small and medium-sized teams and individual creators.
6. Limitations and precautions
- Long duration and complex sports scenes may still have missing details or incoherent movements, which require manual screening.
- 14GB video memory is the ideal configuration, and the actual speed will be affected by the disk, bandwidth and acceleration library installation.
- Prompt word engineering is very important, and it is recommended to use clear scene descriptions, style specifications, and lens instructions.
- The model adopts a custom open source license, and the license and terms of use must be read carefully before commercial or secondary distribution.
7. Project address
https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5
8. FAQ
Q: What is the memory requirement of HunyuanVideo 1.5, and can it be used with a consumer graphics card?
A: After enabling the corresponding optimized configuration, the reference memory requirement is about 14GB, and common 16GB consumer graphics cards can generally run through basic reasoning, but the resolution and duration need to be adjusted according to the video memory.
Q: How long and what resolution does HunyuanVideo 1.5 support? Can you generate 1080p?
A: The model is primarily geared towards 480p/720p video generation from 5–10 seconds, which can be further enlarged to 1080p with the official super-resolution module.
Q: What tasks does HunyuanVideo 1.5 support? What is the difference between text-to-video and image-to-video?
A: Currently, text-to-video (T2V) and image-to-video (I2V) are supported, the former generates video directly from text, and the latter expands a continuous frame with a given image as the first frame, and the two are slightly different in terms of calling interfaces and parameters.
Q: What are the key advantages of HunyuanVideo 1.5 compared to other open-source video generation models?
A: Its core advantages are that the number of parameters is relatively small, the threshold for video memory is low, and it maintains strong competitiveness in image quality and motion coherence, making it suitable for rapid iteration and implementation in the local environment.
