CRITICALFailure Reference

Kling AI Face Distortion — Pre-Generation Risk Reference

Technical Classification

Identity Coherence Failure

Identity Coherence Failure occurs when Kling's model fails to maintain a stable face across the clip. The subject's identity drifts — eye spacing changes, jaw shape morphs, the person at frame 60 looks like a different person from frame 1. The failure compounds with clip length, fast cuts, and prompts involving multiple subjects. Output is unusable for any character-driven content, branded talent, or commercial work requiring identity consistency.

How to identify this failure

✕Eye spacing widening or narrowing across the clip
✕Jaw shape morphing between frames
✕One half of the face melting or stretching
✕Subject identity visibly changing mid-clip
✕Facial features asymmetric with no anatomical cause

Real generation examples

Prompt used

"Woman in red dress smiling at the camera, professional portrait"

Failure observed @ 0:02

Eye spacing widened from 0:02 to 0:05; jawline morphed; identity drifted noticeably

Prompt used

"Two friends laughing at a café, candid shot"

Failure observed @ 0:03

Left subject's face morphed at 0:03; right subject's features melted on right side

Documentation strength

If you need to escalate

HIGH — Kling support refunds identity coherence failures on documented portrait or commercial work. Submit Generation ID with paired screenshots at clip start and end.

AVA is a pre-purchase prevention tool, not a post-purchase recovery tool. Platforms generally do not guarantee credit refunds for output-quality failures; goodwill credits are at each platform's discretion. The strength rating reflects how well-formed your support ticket can be, not a promised outcome.

Prevention + documentation steps

01
Score your prompt before you generate
Run your prompt through AVA's pre-flight scoring against the Identity Coherence Failure pattern. Green light = generate. Yellow/red = rewrite using the suggested fix before you commit credits.
02
Capture Generation ID + timestamp if it failed anyway
Find the Generation ID in the URL or share link. Note the exact time when the Identity Coherence Failure first appears (e.g. "failure first visible at 1.2s"). Timestamped evidence is significantly stronger than a general complaint.
03
Use the correct technical term in your support ticket
Describe this failure as "Identity Coherence Failure". This term maps to a recognised internal workflow in the support system and routes the ticket to the right team.
04
Submit via the correct support channel
Runway has no direct email intake. Pro+ plan: open the in-app AI Assistant (help widget bottom-right of app.runwayml.com), describe the failure with the technical term, attach evidence. Free/Standard plan: human support isn't available — your channel is Discord #community-help with @On Call - Moderators.

Frequently asked questions

Does Kling refund credits for face distortion?

Yes. Submit the Generation ID with two screenshots — clip start and end — showing the same subject with visibly different facial structure. Kling support refunds identity drift on documented commercial work.

Why does Kling fail at face coherence?

Kling's identity-conditioning signal is learned statistically rather than enforced. The model maintains face structure across frames via temporal consistency loss, but the loss is not strong enough to prevent slow drift on longer clips or fast-motion sequences.

How do I avoid face distortion on Kling?

Keep clips ≤4 seconds when faces are the subject. Avoid rapid motion or multiple subjects in frame. Use simple lighting. AVA flags face-coherence risk prompts before submission.

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