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19 Dec 2025 · Paper summary

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.

#genai#video#multimodal

Sources

  1. Kling-Omni Technical Report (arXiv:2512.16776) — arXiv
  2. Hugging Face Daily Papers, 2025-12-19 — Hugging Face
  3. 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.