AI video generation model for long, high-framerate videos
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# Framepack AI: The Revolutionary AI Video Generation Model
Framepack AI is a breakthrough neural network structure for AI video generation. It employs innovative "next frame prediction" technology combined with a unique fixed-length context compression mechanism, enabling users to generate high-quality, high-framerate (30fps) videos up to 120 seconds long with very low hardware barriers (requiring only consumer-grade NVIDIA GPUs with 6GB of VRAM).
## What Makes Framepack AI Unique?
The core innovation of Framepack AI lies in its fixed-length context compression technology. In traditional video generation models, context length grows linearly with video duration, leading to a sharp increase in VRAM and computational resource demand. Framepack AI effectively solves this challenge by intelligently evaluating the importance of input frames and compressing this information into fixed-length context 'notes'. This significantly reduces the demand for VRAM and computational resources, making it possible to generate long videos on consumer hardware.
## Key Features
* Fixed-Length Context Compression:
Intelligently compresses all input frames into fixed-length context information, preventing memory usage from scaling with video length and dramatically reducing VRAM requirements.
* Minimal Hardware Requirements:
Requires an NVIDIA RTX 30XX, 40XX, or 50XX series GPU with at least 6GB of VRAM. Compatible with both Windows and Linux operating systems, supporting FP16 and BF16 data formats.
* Efficient Generation:
Generates frames at approximately 2.5 seconds per frame on RTX 4090 desktop GPUs, with optimization (like teacache) reducing this to 1.5 seconds per frame.
* Strong Anti-Drift Capabilities:
Progressive compression and differential handling of frames by importance mitigates the 'drift' phenomenon common in long video generation, ensuring consistent quality throughout.
* Multiple Attention Mechanisms:
Support for PyTorch attention, xformers, flash-attn, and sage-attention provides flexible optimization options for different hardware setups.
* Open-Source and Free:
Developed by ControlNet creator Lvmin Zhang and Stanford University professor Maneesh Agrawala. Framepack AI is a fully open-source project with its code and models publicly available on GitHub, backed by an active community and rich ecosystem.
## Getting Started with Framepack AI
You can download Framepack AI from its official GitHub repository. It can be used as a standalone application or integrated with platforms like ComfyUI. The community, such as RunningHub, has also created a Framepack plugin for zero-threshold usage.
Framepack AI is dedicated to advancing AI video generation technology. Join us in exploring the future of video creation!
Download the open-source code and models from the official GitHub repository.
Install on a Windows or Linux system with an NVIDIA RTX 30XX/40XX/50XX GPU (6GB+ VRAM).
Provide input frames or text prompts to start generating a video.
Adjust settings for desired video length (up to 120 seconds) and frame rate (30fps).
Optionally enable teacache optimization to speed up frame generation.
Fixed-length context compression prevents VRAM usage from scaling with video length.
Generates videos up to 60–120 seconds long at 30fps on GPUs with just 6GB of VRAM.
Efficient frame generation: ~2.5s/frame (RTX 4090), down to 1.5s/frame with teacache.
Progressive compression and differential frame handling reduces visual drift in long videos.
Supports PyTorch attention, xformers, flash-attn, and sage-attention for hardware flexibility.
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Common questions to help you decide if Framepack AI is right for you.