To keep a face consistent in Kling image-to-video:
- Start from one sharp, front-facing reference photo.
- Paste the same written description of the person into every prompt.
- Ask for small motions and slow camera moves.
- Use first-and-last-frame mode when a clip must begin and end on a known face.
No setting guarantees an identical face, so review every clip and regenerate the weak ones.
As of Oct 12, 2026. Official sources: Kling AI blog: Introducing Kling 4.0 and Kling 4.0 vs 3.0.
Is Kling 4.0 available for image to video yet?
As of Oct 12, 2026:
- Kling AI's official blog (Sep 30, 2026) says the full Kling 4.0 "will officially launch in October."
- Kling 4.0 Flash "became available to a limited group of users for early access on September 28." The announcement says Flash is for Ultra Yearly subscribers.
- Kling 4.0 is not in this site's current generation catalog, which uses Kling 3.0 and other connected models.
The techniques below work with any Kling image-to-video model. We'll update this section when the full Kling 4.0 release is public.
What is face drift?
Face drift is when a person's features change within a clip or between clips: a different jawline, eye shape, hairline or apparent age. It tends to get worse with:
- Fast motion
- Big head turns
- Hands or hair covering the face
- Vague prompts
Which image-to-video mode should I use?
| Mode | What it fixes | Best for |
|---|---|---|
| Image reference | How the subject looks | Single shots, gentle motion |
| First & last frame | The start and end frames | Shots that must match the next clip |
| Text only (no image) | Nothing visual | Not recommended when identity matters |
The Image to Video tool accepts JPEG, PNG or WebP images. For keyframe planning, see the Kling 4.0 keyframes guide.
How do I keep the same face step by step?
- Choose the reference photo. Front-facing or at a slight angle, with even light, sharp focus, no heavy filters, and nothing covering the eyes or mouth.
- Write a fixed description. Example:
A woman in her early 30s with shoulder-length straight black hair, light freckles, small silver hoop earrings, wearing a navy turtleneck.
- Add one action and one camera move.
[description]. She looks up from a book and smiles softly. Slow push-in, soft window light, realistic. More patterns are in Kling prompts.
- Fix the start and end when needed. Upload two photos of the same person from the same shoot in first-and-last-frame mode.
- Generate several versions and compare. Check frame by frame around blinks, head turns and hand movements.
- Reuse everything for the next shot. Keep the same photo, description and lighting words. Change only the action and the camera move.
Why does the face still change, and how do I fix it?
| Symptom | Likely cause | Fix |
|---|---|---|
| Face shifts mid-clip | Big head turn or fast motion | Smaller motion, slower camera |
| Different person in shot 2 | New photo or reworded description | Reuse the same photo and text |
| Distortion behind hands or hair | Something covering the face | Remove the covering action |
| Looks older or younger | Lighting or style words changed | Keep that wording fixed |
Checklist
- ☐ One master photo per character
- ☐ Same description pasted into every prompt
- ☐ One action and one camera move per clip
- ☐ First & last frame used for shots that must match
- ☐ Every clip reviewed at full size
- ☐ Permission to use the person's likeness
FAQ
Is image to video better than text to video for faces? Yes, when identity matters. Text-to-video has no picture to anchor the face.
Will Kling 4.0 fix face drift? Kling's official posts describe stronger reference consistency in Kling 4.0. We haven't tested it, and the full model isn't public as of Oct 12, 2026.
How many attempts should I plan for? Plan several for close-up shots. Wide shots usually need fewer.
Next step
Upload your reference photo in Image to Video and start with a slow push-in.