license: apache-2.0
pipeline_tag: image-text-to-video
base_model: ByteDance/Bernini-R
Quantized GGUF version of Bernini-R for ComfyUI.
Original model link: https://huggingface.co/ByteDance/Bernini-R
Watch us on Youtube: @VantageWithAI
Latent Semantic Planning for Video Diffusion
Chenchen Liu*, Junyi Chen*, Lei Li*, Lu Chi*,§, Mingzhen Sun*, Zhuoying Li*, Yi Fu, Ruoyu Guo, Yiheng Wu, Ge Bai, Zehuan Yuan✉
* Equal contribution ✉ Corresponding author § Project lead
🎉 News
- [2026-06-01] We open-sourced the inference code and model weights of the Bernini Renderer (Bernini-R).
- [2026-05-22] We released our paper Bernini: Latent Semantic Planning for Video Diffusion.
✨ Highlights
Bernini is a unified framework for video generation and editing that combines an MLLM-based semantic planner with a DiT-based renderer.
On video editing, Bernini reaches the first tier among leading closed-source commercial models. The leaderboard below comes from our self-built arena platform, where human annotators blindly vote on paired edits and the votes are aggregated into a Bradley-Terry score and a pairwise win-rate matrix.
📑 Citation
If you use Bernini in your research, please cite:
@article{bernini,
title = {Bernini: Latent Semantic Planning for Video Diffusion},
author = {Chenchen Liu and Junyi Chen and Lei Li and Lu Chi and Mingzhen Sun and Zhuoying Li and Yi Fu and Ruoyu Guo and Yiheng Wu and Ge Bai and Zehuan Yuan},
journal = {arXiv preprint arXiv:2605.22344},
year = {2026}
}
🙏 Acknowledgements
Bernini builds on several outstanding open-source projects:
We thank the authors and communities of these projects for their contributions.
📄 License
Apache License 2.0. See LICENSE.