Inputs
Pick quality vs. cost
Kling and Seedance produce the most cinematic motion; Wan is the cheapest option for fast iteration on a prompt.
Examples
Drafting an idea before committing to it
When you are still deciding whether a scene works at all, generate on Wan first. It is the cheapest per clip, so you can run several wordings of the same prompt and find out which one the model actually understands before paying for a cinematic render.
Producing a clip someone will watch
Once the wording is settled, regenerate the winning prompt on Kling or Seedance. The motion is markedly more stable across the whole clip, which is what separates something publishable from something that only looks right in the first second.
Failure modes and fixes
Where text-to-video still needs several attempts
Generating motion from words alone is the least predictable thing these models do, and the risk is spending credits on rewordings that were never going to work. Write one acceptance test before you start — the single beat the clip must land — then compare two or three cheap Wan drafts against it rather than judging each in isolation. Stop as soon as one passes and re-run that exact prompt on a higher-quality model; if none pass, choose a shorter or simpler action instead of adding more description. Long or multi-step actions drift, and legible on-screen text remains unreliable, so add titles afterwards.