Pick by use case · 4 guides
Which model for your shot.
Most “best AI video model” rankings sort by demo polish. That is useless when your job has one attribute it lives or dies on. These guides rank models by the documented failure mode that decides each specific use case — talking-head, character consistency, product demos, on-screen text.
Best model for
talking-head & dialogue videos
Decided by: native audio + lip sync that holds across a spoken line
Best model for
consistent characters across shots
Decided by: identity holding — the same face/character across cuts or a reference
Best model for
product-demo & e-commerce videos
Decided by: color stability, camera control, and on-screen text — the three things a product shot lives or dies on
Best model for
on-screen text, captions & logos
Decided by: readable on-screen text — which no covered model produces reliably
Cross-references for picking the right tool before you commit credits.
Consistency ranking
Which model is most consistent
9 models ranked by documented failure profile.
Head-to-head
Model-vs-model comparisons
Dimension-by-dimension, organized by failure profile.
Failure reference
Documented failure modes
Catalogued across every covered model.
Prompt scoring
Score a prompt before you generate
Flags the failure your prompt is most likely to hit per model.
Methodology
Why pick by use case.
Every AI video model fails differently, and most jobs hinge on a single attribute — synced audio for a talking head, identity coherence for a recurring character, color and camera stability for a product reveal, and (for everyone) the fact that no model renders readable on-screen text.
These guides rank models by the documented failure mode that decides each use case, with deep links into the per-model failure catalogue and the consistency ranking. Pick by track record on the attribute your shot depends on — not by which model is generating the most demos this quarter.