{"ID":2839300,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.14993","arxiv_id":"2511.14993","title":"Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation","abstract":"This report introduces Kandinsky 5.0, a family of state-of-the-art foundation models for high-resolution image and 10-second video synthesis. The framework comprises three core line-up of models: Kandinsky 5.0 Image Lite - a line-up of 6B parameter image generation models, Kandinsky 5.0 Video Lite - a fast and lightweight 2B parameter text-to-video and image-to-video models, and Kandinsky 5.0 Video Pro - 19B parameter models that achieves superior video generation quality. We provide a comprehensive review of the data curation lifecycle - including collection, processing, filtering and clustering - for the multi-stage training pipeline that involves extensive pre-training and incorporates quality-enhancement techniques such as self-supervised fine-tuning (SFT) and reinforcement learning (RL)-based post-training. We also present novel architectural, training, and inference optimizations that enable Kandinsky 5.0 to achieve high generation speeds and state-of-the-art performance across various tasks, as demonstrated by human evaluation. As a large-scale, publicly available generative framework, Kandinsky 5.0 leverages the full potential of its pre-training and subsequent stages to be adapted for a wide range of generative applications. We hope that this report, together with the release of our open-source code and training checkpoints, will substantially advance the development and accessibility of high-quality generative models for the research community.","short_abstract":"This report introduces Kandinsky 5.0, a family of state-of-the-art foundation models for high-resolution image and 10-second video synthesis. The framework comprises three core line-up of models: Kandinsky 5.0 Image Lite - a line-up of 6B parameter image generation models, Kandinsky 5.0 Video Lite - a fast and lightwei...","url_abs":"https://arxiv.org/abs/2511.14993","url_pdf":"https://arxiv.org/pdf/2511.14993v3","authors":"[\"Vladimir Arkhipkin\",\"Vladimir Korviakov\",\"Nikolai Gerasimenko\",\"Denis Parkhomenko\",\"Viacheslav Vasilev\",\"Alexey Letunovskiy\",\"Nikolai Vaulin\",\"Maria Kovaleva\",\"Ivan Kirillov\",\"Lev Novitskiy\",\"Denis Koposov\",\"Nikita Kiselev\",\"Alexander Varlamov\",\"Dmitrii Mikhailov\",\"Vladimir Polovnikov\",\"Andrey Shutkin\",\"Julia Agafonova\",\"Ilya Vasiliev\",\"Anastasiia Kargapoltseva\",\"Anna Dmitrienko\",\"Anastasia Maltseva\",\"Anna Averchenkova\",\"Olga Kim\",\"Tatiana Nikulina\",\"Denis Dimitrov\"]","published":"2025-11-19T00:23:22Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.AI\",\"cs.LG\"]","methods":"[\"Reinforcement Learning\"]","has_code":false}