The still-image negative prompt is a second text stream that pushes the model away from named things: watermarks, extra fingers, a plastic sheen. On video that stream has to cover failures that only exist in time. A shirt that changes colour, a logo that crawls, a face that morphs at second four, a camera that floats when you asked for lock-off, a hand that gains a finger on the swing. Temporal consistency is the quality name for some of that. The negative prompt is the instruction, where the model even exposes one.
Copying a hundred-word image negative into a video field is how you shrink the space the model can move in without telling it what is going wrong. Name the artefact you keep seeing. 'Camera drift, morphing face, extra limbs, on-screen text, watermark' is a list. 'Bad, ugly, worst quality, jpeg' is a superstition, and it is worse on video because the model also has to spend capacity on motion. If a term is already in the positive prompt, the two cancel.
Not every video model has the field. Where it is missing, the equivalent is a tighter positive prompt, a lower motion level, a locked camera, a shorter duration, a seed-lock on a take that was already clean, or a region-edit on the one object that failed. Negations inside the positive prompt still plant the concept: 'no flicker' often flickers. Put the noun in the negative field, or do not mention it.
In practice
- List concrete time-based failures you have actually seen on this model, not a forum's image dump.
- Keep the negative list shorter than the prompt. If it is longer, you are fighting the brief.
- If the row has no negative field, spend the effort on camera lock, duration, and motion level instead.
The mistake to avoid
Pasting an image-generation negative prompt into a video job and expecting flicker to stop. Still-image nouns do not name the failure you are looking at.
Where you will run into it
- AI Video Generator — Text-to-video, image-to-video, and story chaining in one studio.
Related terms
Negative prompt
Negative prompt meaning: a list of what you do not want in the output, steering generation away from those terms.
Prompt
Prompt meaning: the written instruction a generative model reads to decide what to make. The one input almost every model needs.
Temporal consistency
Temporal consistency is how well a generated clip keeps things the same from one frame to the next, with no flicker, shimmer or drifting detail.
Camera control
Camera control is the set of inputs that decide how the virtual camera behaves during a generated clip — whether it pushes in, orbits, pans, or stays locked off.
Seed
Seed meaning: the number that sets the random starting noise so the same seed and settings can reproduce the same output.
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