FramePack is an AI model that compresses temporal information across video frames to achieve smoother, more coherent, and efficient video generation.

FramePack is an innovative AI framework designed to improve video generation efficiency by compressing temporal information into compact, trainable frame representations. Developed by Lvmin Zhang (lllyasviel) and Maneesh Agrawala, it introduces a new paradigm for large video models with reduced memory footprint and superior temporal coherence.
FramePack efficiently encodes video frames into compact latent representations, allowing large-scale video generation models to operate faster and with less memory.
Maintains smooth transitions and continuity across frames, significantly reducing flickering and motion inconsistency in generated videos.
Easily integrates into existing diffusion and transformer-based video generation models without requiring major architectural changes.
Optimized for generating longer video sequences by minimizing temporal redundancy and maximizing information retention.
Validated in experiments showing superior efficiency and quality over baseline frame-by-frame methods in AI video synthesis tasks.
Follow these steps to generate smooth, high-quality videos using the FramePack model directly on Story321.
Write a detailed text prompt describing the scene, motion, and tone you want to generate.
Choose video length, frame rate, and style preferences for your generation task.
Click 'Generate Video' to start the FramePack process and preview the output directly on the page.
Tweak your prompt or parameters for improvements, then export your video for further use.
FramePack runs directly within Story321’s generation interface, optimized for seamless user experience.
FramePack enables new possibilities in AI-assisted video generation, animation, and visual storytelling.
Produce cinematic, coherent videos from text or image prompts with minimal temporal artifacts.
Enhance 2D or 3D animation pipelines by ensuring frame-level continuity and consistent motion flow.
Serve as a foundation for exploring efficient video diffusion models and frame compression techniques.
Generate storyboards or dynamic scene previews with stable visual continuity for creative projects.
Learn more about the FramePack model and its integration into Story321’s AI video generation suite.
FramePack is an AI model architecture that efficiently compresses temporal information across frames, enabling smoother and faster video generation.
FramePack was developed by Lvmin Zhang (lllyasviel) and Maneesh Agrawala from Stanford University.
Unlike frame-by-frame generation, FramePack uses compact frame representations to maintain coherence and reduce computational load.
Yes. FramePack can integrate with existing diffusion-based or transformer-based models for video synthesis, serving as an enhancement layer.
Yes. The official implementation of FramePack is available on GitHub under lllyasviel’s repository.
Absolutely. You can experiment with FramePack directly on its Story321 model page to create coherent AI-generated videos.
Experience next-generation video generation with FramePack. Create fluid, coherent, and cinematic videos powered by state-of-the-art AI compression technology.
FramePack is available directly within Story321’s model library for creative and research purposes.