Skip to main content

Ring Corner Boxing Exchange

One square-ring exchange: a hook on a raised guard, sweat in the air, the camera orbiting without a cut.

Sports & actionText to video311 credits

Fills the prompt and every setting below into the Seedance 2.5 form. Nothing is submitted until you press generate.

The prompt

Two boxers trade in close: a short left hook lands on a raised guard, gloves and forearms colliding, sweat leaving the brow on the follow-through. The camera orbits them slowly at chest height, keeps both fighters in frame and never cuts. Warm tungsten from a single ring lamp overhead, dark hall behind, smoke hanging in the beam. Square framing, film grain, gritty broadcast texture. Audio: glove impact, hard breathing, shoe squeak on canvas.

Settings this prompt was written for

Settings this prompt was written for
FieldValue
ModeText to video
Duration8 seconds
Resolution720p
Aspect ratio1:1
AudioAudio on
Credits311

They are the real price of that exact configuration — computed with the same pricing engine the API charges with, at the resolution, duration and audio setting shown on the card. Change any of those in the generator and the price updates with it.

Why it works

Contact reads better as geometry than as force, so the prompt describes glove on guard, forearms colliding and sweat leaving on the follow-through, all of which a model can draw without depicting harm. Eight seconds is the shortest length that fits a throw, a block and the reaction after it, and the single slow orbit keeps both fighters readable at once. One overhead tungsten source is named so the ropes stay silhouetted instead of turning into a lit backdrop.

Mode

Most cases are text-to-video and need nothing but the prompt. The ones marked "needs one reference image" are image-to-video: you supply a photo and the prompt keeps that subject or product locked while the camera moves.

boxing video promptring slow motionsquare format sports videoboxing round prompt

Prompts stay in English on every language of this site: that is the language the model was trained on, and translating a prompt changes what it renders. The page around it is translated.