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Kling 3.0 Image
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Kling 3.0 Image

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Kling 3.0 Image

Kling 3.0 Image is an advanced AI image generation. It represents a significant evolution in AI-driven visual creation, building on previous iterations like Kling O1 and 2.6 to deliver a unified multimodal framework known as Multi-modal Visual Language (MVL). This architecture integrates text, image, video, and audio inputs seamlessly, allowing the image model to serve as a foundational tool for broader creative workflows, including transitions to video generation.

Key Features and Capabilities

Kling 3.0 Image excels in generating photorealistic and cinematic visuals, emphasizing realism over stylized effects.

It supports two primary modes:

· Text-to-Image (T2I): Converts descriptive prompts into high-quality images, interpreting cinematic intent such as shot composition, lighting, and narrative elements rather than just object lists.

· Image-to-Image (I2I): Transforms existing images while preserving key details like identity, layout, text, textures, and materials, making it ideal for refinements or style transfers.

The model prioritizes:

· Enhanced Realism: It produces images with accurate lighting (including prompted color temperatures), volumetric effects, hyper-detailed textures (e.g., skin, fabric, hair), and precise material rendering, reducing common AI artifacts like plastic-looking surfaces or soft macro details.

· Style and Element Consistency: Supports batch generation of image series with consistent lighting, colors, and subjects, ensuring cohesion across multiple outputs for storytelling or branding.

· Improved Text Rendering: Better handles legible, perspective-correct text on signs, interfaces, or objects, which is particularly useful for advertising and commercial applications.

· Multimodal Integration: As part of the Kling 3.0 ecosystem, images generated can directly feed into video models for consistent subject tracking, motion addition, or full narrative development.

Prompting Tips

For optimal results include structuring descriptions like director's notes—specifying shots, motions (if transitioning to video), and details—rather than vague lists. For example, prompts work best when they describe scenes with narrative flow, such as "A wide-angle shot of a coastal town at golden hour, with volumetric lighting and hyper-realistic watercolor textures."

Resolutions and Output Quality

· Standard outputs include 1K and 2K resolutions, with Image 3.0 Omni extending to native 4K for ultra-high-definition results.

· Generation is native at the pixel level, avoiding upscaling artifacts for sharper details, better grain structures, and professional presentation quality.

· Outputs are optimized for cinematic use, with options for series generation and batch style control.

Use Cases

Designed for creators and professionals, Kling 3.0 Image is suited for:

· Storyboards and concept art in film, advertising, and game development.

· Cinematic stills and pre-visualization for virtual scenes.

· High-fidelity production assets, such as branded visuals or photorealistic mockups.

· Integrated workflows where images evolve into videos, like multi-shot storyboarding or audio-synced narratives.

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公告
2026-02-06
发布模型
2026-03-30
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模型详情
类型
Checkpoint
发布时间
2026-02-06
基础模型
Kling Image
模型参数
clip_skip:1
训练参数
Epochs:1
Steps:0
许可范围
创作许可范围
在线生图
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