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Image Generation Model

Kling Image O1

Kling Omni Image O1 is Kuaishou's multi-reference image generation model that maintains stunning visual consistency across characters, styles, and scenes using up to 10 reference images at once.

Publisher Kling
Type Image
Context Window 10,000 tokens
Training Data December 2025
Price Free/image
Provider WaveSpeed
Source Image

Multi-reference image generation with visual consistency

Kling Image O1, formally known as Kling Omni Image O1, is an image generation model developed by Kuaishou Technology, the company behind the Kling AI ecosystem. It is built on a Multimodal Visual Language (MVL) framework that combines natural language understanding with multi-reference image processing, allowing it to accept between 1 and 10 reference images simultaneously and extract consistent visual features across all outputs. The model was trained through December 2025 and supports a context window of 10,000 tokens.

The model is designed to address a common challenge in AI image generation: maintaining consistent character identity, style, and visual detail across multiple generated images. It is particularly suited for workflows such as IP character design, comic and manga creation, brand merchandise imagery, and serialized visual content where cross-image consistency is a requirement. Inputs include image URL arrays alongside select and toggle controls, giving users structured options for guiding generation behavior.

What Kling Image O1 supports

Multi-Reference Input

Accepts between 1 and 10 reference images simultaneously via image URL arrays, extracting outlines, color tones, and lighting from each to inform generation.

Character Consistency

Preserves subject identity across multiple generated images, maintaining recognizable features of characters or objects from one output to the next.

Style Control

Sustains a coherent visual aesthetic and tone across an entire project, suitable for brand systems, comic series, and marketing campaigns.

Precision Element Editing

Allows specific elements to be added, removed, or modified through natural language instructions without disrupting the surrounding style or texture.

Configurable Generation Options

Exposes select and toggle group inputs so users can control generation parameters such as aspect ratio or output mode directly at the API level.

MVL Framework Processing

Uses a Multimodal Visual Language framework to interpret complex creative text prompts alongside visual references within a 10,000-token context window.

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Common questions about Kling Image O1

How many reference images can I provide at once?

The model supports between 1 and 10 reference images simultaneously, supplied as an array of image URLs.

What is the context window for Kling Image O1?

The model has a context window of 10,000 tokens, which covers both the text prompt and associated image reference metadata.

What was the training data cutoff for this model?

According to the model metadata, the training date is listed as December 2025.

What input types does the model accept?

The model accepts image URL arrays, select inputs, and toggle group inputs, allowing structured control over generation behavior alongside visual references.

Who developed Kling Image O1?

Kling Image O1 was developed by Kuaishou Technology, the company behind the broader Kling AI ecosystem.

Parameters & options

Reference Images Image URL Array

Provide up to 10 references images of the scene, subject, objects, or anything else in the image.

Aspect Ratio Select
Default: 16:9
16:99:161:14:33:43:22:321:9
Resolution Toggle Group
Default: 2k

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