Text to Video AI Generator
Describe a shot and get it rendered. Nothing is being cut together from a stock library — every frame is generated for your prompt.
18+ only · fictional characters only · no public gallery
How it works
Three steps, about five minutes end to end.
Describe the shot, not just the subject
"A woman in a red coat" is a subject. "Medium shot, a woman in a red coat walking toward camera, shallow depth of field, overcast light, slow handheld" is a shot. The second one gets a usable clip.
Pick a model
Models differ in what they are good at — camera movement, stylised art, or holding a face steady. The same prompt on two models is the fastest way to learn the difference.
Generate, judge, adjust one thing
Change a single element between runs. Changing the whole prompt at once tells you nothing about which part was responsible.
What makes it different
No source material needed
Nothing to shoot, nothing to license, nothing to find. That is the whole point of text to video and it is why it is used most for shots that would otherwise need a location.
Prompt structure that actually helps
Shot type, subject, action, lighting, camera movement, style. Six slots, in that order. It is not a magic formula but it stops you from leaving the camera unspecified.
Fast iteration
Because there is no input to prepare, the loop is short. Ten prompt variants are a reasonable afternoon and normally beat one carefully engineered prompt.
Same queue as image to video
Generate a still, decide you like the frame, then animate it instead. The two paths are one workflow, not two products.
Prompt anatomy
| Slot | Example | What happens if you omit it |
|---|---|---|
| Shot type | medium shot, close-up, wide | The model picks at random |
| Subject | a woman in a red coat | Nothing usable |
| Action | walking toward camera | Near-static output |
| Lighting | overcast, golden hour, low key | Flat, default lighting |
| Camera | slow dolly in, static, handheld | Unpredictable movement |
| Style | cinematic, anime, 35mm film | Generic look |
Why text to video is harder than text to image
A still image has to be coherent once. A video has to be coherent in every frame and consistent between all of them. Every problem in image generation — hands, faces, text, physics — is still there, and now it also has to hold together over time. That is why generated clips are short, why they cost more per second than images, and why the best results come from tight, well-specified prompts rather than long poetic ones.
It also explains the drift you will see on longer runs. The model has no persistent memory of your subject; it maintains consistency through the momentum of preceding frames, and that momentum decays. Keeping clips short is not a limitation to work around so much as the way the technology behaves.
Prompts that work and prompts that do not
What works: concrete nouns, one clear action, an explicit camera instruction, and a named lighting condition. What does not work: emotional abstractions the model cannot see ("a sense of longing"), multiple simultaneous actions, more than two subjects, and stacked style words that pull in opposite directions.
Negatives are worth a word of caution. Telling a model what to avoid works far less reliably in video than in image generation, and writing "no blur" frequently produces blur. Say what you want present instead.
When to switch to image to video instead
If you have run six prompts and the subject still is not right, stop prompting for video. Generate a still until the frame is exactly what you want, then animate that still. You will spend fewer credits and get a better clip, because you have separated "is the frame right" from "is the motion right" — two questions that are impossible to debug when they are tangled together.
This is the workflow most experienced users converge on, and it is the reason image to video and text to video sit in the same tool rather than in two.
Frequently asked questions
How long can a text-to-video clip be?
Seconds, not minutes. Longer sequences are made by generating several clips and joining them.
Can I control the camera?
Yes, by naming the movement in the prompt — static, slow dolly in, orbit, handheld. Naming it is far more reliable than leaving it out.
Why do my results look different every run?
Video generation is stochastic. Two runs of the same prompt are two samples, not a repeat. Change one element at a time so you can tell what caused a difference.
Is text to video better than image to video?
Different jobs. Text to video is better when you have no source material; image to video is better whenever you already have a frame you like.
Can I generate video with speech or sound?
The output is silent video. Audio is added afterwards in any editor.
Does prompt length help?
Only up to a point. Specific and structured beats long. Past roughly a paragraph, extra words mostly dilute the instruction.
Try it on your own image
New accounts get starter credits. No card needed to run a first generation.
Write a prompt