Paper summary: Kling-Omni Technical Report
Kling-Omni is one end-to-end framework for video generation, editing and reasoning-based editing from mixed inputs (text, reference images, video context), built on a dedicated data system.
Problem
Video generation, video editing and “intelligent” reasoning-based tasks are usually handled by separate models or pipelines.
Method
Kling-Omni takes an end-to-end view. It accepts text instructions, reference images and video context, processes them into a unified multimodal representation, and generates or edits video. A comprehensive data system supports this, along with efficient large-scale pre-training and inference optimisations.
Key results
From the abstract: the paper reports exceptional capabilities in in-context generation, reasoning-based editing and multimodal instruction following, and positions the model as a step toward “multimodal world simulators”.
Limitations
There’s no dedicated limitations section in the extracted text. The report is from the product team and the abstract gives no specific benchmark numbers.
Sources
- Kling-Omni Technical Report (arXiv:2512.16776) — arXiv
- Hugging Face Daily Papers, 2025-12-19 — Hugging Face
- Kling-Omni Technical Report (arXiv HTML full text) — arXiv
This is a summary written from the linked public sources. Figures and numbers are as reported there.