Text-to-video (T2V) is a generative AI technique that turns a written description — a prompt — into a moving video clip, complete with motion, lighting, and (on modern models) synchronized audio. You describe the scene; the model films it.
How it works
Under the hood, most text-to-video models are diffusion models trained on enormous libraries of video paired with captions. During generation, the model starts from pure noise and progressively "denoises" it into frames, guided at every step by your prompt. Because the model generates all frames within a shared temporal context, the output stays coherent: objects persist, motion flows, and the camera behaves like a camera rather than a slideshow.
What it's best at
Text-to-video shines when you're starting from nothing but an idea:
- Concept exploration — visualize a scene before committing to a shoot or a storyboard.
- Short-form content — hooks, B-roll, product teasers, and social clips in vertical or widescreen formats.
- Impossible shots — drone passes through a keyhole, a city made of glass, a fox in a spacesuit. If you can describe it, the model can attempt it.
What a good prompt includes
The strongest T2V prompts read like a director's shot note, not a wish. Cover four things: the subject (who or what), the action (what happens over time), the camera (framing and movement), and the atmosphere (lighting, palette, mood). For a deeper walkthrough, see our guide on how to write AI video prompts.
Text-to-video on Molyin
Molyin's generator runs Seedance 2.0 in text-to-video mode with clips of 5 or 10 seconds, resolution up to 1080p, six aspect ratios from 21:9 cinematic to 9:16 vertical, optional AI-generated audio, and seed control for reproducible results.
Related terms
- Image-to-Video — animate an existing image instead of starting from text alone.
- Reference-to-Video — guide generation with reference images for consistent subjects.
Try it yourself with the AI video generator.
