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Kling Image 3.0 Omni

Released Apr 2026

Kling Image 3.0 Omni is a multimodal image generation model developed by KlingAI (Kuaishou), designed for professional digital art and cinematic storyboarding. As part of the Kling 3.0 series, the model integrates high-resolution output with logical reasoning capabilities to produce visual narratives rather than isolated frames. It is built to interpret complex creative intentions with high accuracy, adhering strictly to professional compositional rules and cinematic lighting requirements.

The model utilizes a Visual Chain-of-Thought (vCoT) reasoning framework, which allows it to process the relationships between objects and their environment before final rendering. This architecture enables the model to generate native 2K and 4K Ultra HD imagery directly, eliminating the need for external upscaling and preserving authentic textures and color transitions. Its multimodal reasoning is optimized for industrial-grade workflows, including film pre-visualization and brand asset creation.

Key Capabilities

  • Image Series Mode: This feature allows creators to generate logically coherent sequences of images from a single prompt or multiple references. It is designed to maintain character and environmental consistency across different shots, facilitating the creation of structured storyboards.
  • Multi-Reference Blending: Users can upload and blend up to three reference images to control specific elements such as character identity, style transfer, and background elements. This allows for precise Subject Locking, where facial features and outfits remain recognizable across various camera angles and scales.
  • Cinematic Shot Control: The model supports advanced control over camera logic, including specific executions for high angles, dutch tilts, and rack focuses. It deconstructs audiovisual elements to ensure that framing instructions and emotional cues are accurately translated into the final composition.
  • Local Re-editing: Kling Image 3.0 Omni includes granular tools for targeted modification, allowing users to adjust specific portions of a generated image without regenerating the entire frame.

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