Pick by use case

Best AI video model for consistent characters

Two different problems hide under "consistent characters," and they have different winners. For the same character across multiple cuts of a scene, Runway Gen-4 Scenes mode is the only model documented to hold identity that far — others visibly drift after a few cuts. For locking one character to a reference image inside a single clip, Vidu's Reference-to-Video pipeline leads. Decide which kind of consistency your shot needs before picking.

Deciding attribute: identity holding — the same face/character across cuts or a reference

Short answer

For consistency across multiple cuts, Runway Gen-4 (Scenes mode) is the best — it is the only model documented to hold one character across several cuts. For locking a character to a reference image in a single clip, Vidu (Reference-to-Video) leads.

Models ranked for consistent characters across shots

1. Runway Gen-4

Best pick

Scenes mode is purpose-built to carry one character across multiple cuts using a shared identity embedding, and it is the only covered model documented to do this — others drift after a few cuts. Its documented weak points are hands on close-ups and dropped instructions on dense prompts, not identity. This is the pick for multi-shot narrative with a recurring character.

Most relevant documented failure: Identity Coherence Failure

2. Vidu

Situational

Vidu's Reference-to-Video pipeline locks a character to a still image, which outperforms text-only conditioning for single-clip identity. It has no multi-cut equivalent of Scenes, so it can't carry the character across a scene — and motion plausibility is its most-documented weakness.

Most relevant documented failure: Face Distortion

3. Luma Dream Machine Ray-2

Runner-up

Luma holds a face well within a single well-lit take, so it is a strong consistency pick inside one shot. But identity-coherence drift is documented past roughly three cuts, so it is the wrong tool the moment your character needs to survive a scene change.

Most relevant documented failure: Identity Coherence Failure

4. Kling 1.6

Avoid here

Kling is strong on single-subject motion but documents face-coherence drift past roughly four seconds and has no multi-cut identity feature. Avoid it when the same character has to hold across cuts; use it for motion-led single shots instead.

Most relevant documented failure: Identity Coherence Failure

What to check before you commit credits

  • Across-cuts vs in-one-clip — Runway Scenes wins multi-cut; Vidu Reference-to-Video wins single-clip locking. They solve different problems.
  • Do you have a reference image? If yes, reference-to-video locking beats text-only identity conditioning.
  • Cut count — most models drift after ~3 cuts; only Scenes mode is documented to hold further.
  • Hands and close-ups — even when identity holds, hand-anatomy failure is documented across every model on close-ups.

FAQ

Which AI video model keeps a character consistent across shots?

Runway Gen-4 with Scenes mode — it is the only covered model documented to hold one character across multiple cuts. Other models drift visibly after about three cuts. For locking a character to a reference image inside a single clip, Vidu Reference-to-Video leads instead.

How do I keep the same face across AI video cuts?

Use Runway Gen-4 Scenes mode, which carries identity across cuts with a shared embedding. If you only need one clip, lock to a reference image with Vidu. Expect drift past a few cuts on every other model, so plan cuts around the tool, not the reverse.

Why does my character look different in each AI video clip?

Most models condition identity from text alone and re-sample each generation, so the face drifts between clips. This identity-coherence failure is documented across models past roughly three cuts. Use Runway Scenes for multi-cut continuity or a reference-image pipeline like Vidu for single-clip locking.

Is Runway or Vidu better for character consistency?

It depends on the shot. Runway Gen-4 Scenes is better for carrying a character across multiple cuts. Vidu Reference-to-Video is better for locking a character to a reference image inside one clip. Vidu cannot carry identity across cuts; Runway has no reference-image locking.

Go deeper

Score before you generate

AVA scores your prompt against each model's documented failure profile

The free Chrome extension flags which documented failure your prompt is most likely to hit on each model — before you spend the credits. Pick by track record, not by demo reel.

Last updated: 2026-06-12. Grounded in AVA's documented per-model failure catalogue.