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🎬 KLING AI ⏱ 4 min read 🎨 Omni Image

Omni Image — Technical Guide

Combine faces, outfits, objects, and scenes from multiple photos into one image — reference anything by label and the AI assembles the composition you describe

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Omni Image

Combine faces, outfits, objects, and scenes from multiple photos into one image — reference anything by label and the AI assembles the composition you describe
Omni Image lets you mix and match elements from different photos in a single generation. Upload a face photo, an outfit photo, and a background — then write a prompt telling the AI exactly what to take from each one.

The magic is in the labeling system. Every image you upload gets a label — image_1, image_2, and so on. Pre-trained elements from your library get labels like object_1, object_2. In your prompt, you reference these labels with triple brackets: Generate a photo of <<<image_1>>> wearing the dress from <<<image_2>>> in the setting of <<<object_1>>>. The AI understands which part of each reference to use based on your instructions.

This is the tool you reach for when standard image generation is not enough — when you need to put a specific person in a specific outfit in a specific place, all sourced from different images. Face swaps, outfit transfers, style mixing, multi-character scenes, and product placement in custom environments all become a single prompt.

The v3 Omni model adds Series mode, generating 2 to 9 linked images that stay visually consistent — perfect for storyboards, photo series, or marketing sets where every shot needs to feel like part of the same shoot.
✦ Best Results Tips
🏷️ Label Everything Clearly
Each uploaded image gets a label — image_1, image_2, etc. Each element gets object_1, object_2. Use these exact labels in your prompt so the AI knows which reference to pull from.
🎭 Be Specific About Roles
Tell the AI what each reference contributes. Say the face from image_1, the outfit from image_2, the background from image_3 — not just use all my images together.
📸 High-Quality Reference Photos
Each reference image should be clear and well-lit. The AI can only extract what it can see — blurry or dark references produce blurry or dark results.
🔁 Create Elements for Repeat Characters
If you use the same character often, train them as an Element first. Elements give more consistent identity preservation than uploading photos each time.
🔟 Stay Within 10 References
You can use up to 10 references total — images and elements combined. More references means more instructions for the AI to follow, so keep it focused on what matters.
🔗 Use Series for Linked Sets
Series mode on v3 Omni generates 2 to 9 images that share the same visual style — ideal for creating content sets, storyboards, or carousel posts that feel cohesive.

Omni Image — Available Models

v3 Omni
Latest Default
kling-v3-omni
Latest — 4K resolution, series generation, intelligent aspect ratio.
Res: 1K, 2K, 4K Max refs: 10 9 aspect ratios
Omni Image (O1)
kling-image-o1
Advanced reasoning image model. Supports image references.
Res: 1K, 2K Max refs: 10 9 aspect ratios
📥 You Give
📝Template Prompt 🖼️Image References 🧩Element References
AI Magic
klingai
🖼️ You Get
🖼️ Image
Resolutions
1K
2K
4K
Aspect ratios
auto
1:1
16:9
9:16
4:3
3:4
3:2
2:3
Result types
Single
Series (2-9 images)
📸
10 references
Max images per request

💰 Omni Image — Pricing

Estimated cost
Failed jobs are automatically refunded

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