Jimeng AI Video Guide: Text-to-Video, Image-to-Video and Prompt Writing

Where Jimeng fits in the pipeline

By the end of this article you'll be able to take one image to a usable clip in Jimeng on your own, and you'll know how to set the parameters and write the prompt. Jimeng is a ByteDance product, available on the web at jimeng.jianying.com; it shares its lineage with CapCut, so assets move between them easily. As of 2026-11 it supports text-to-video, image-to-video, and video extension, up to 1080P and roughly 60 seconds per clip.

Set the parameters before talking about creativity

• Aspect ratio: 9:16 for vertical short video, 16:9 for landscape. Choose correctly up front and you won't have to crop later.
• Duration: 3-8 seconds per shot is the sweet spot. The per-clip limit is about 60 seconds, but longer generations are harder to control.
• Resolution: test at low resolution first, then render at 1080P once it looks right. Saves both time and credits.

Once the parameters are set, only the prompt is left. Many people agonize over the wording first, then discover the aspect ratio was wrong and start over.

Text-to-video: split one sentence into four parts

Write only "a girl walking on the beach" and you'll most likely get mediocre footage. An effective prompt usually contains four parts: subject + action + environment and lighting + camera movement.

For example: A young woman in a beige trench coat walks slowly forward and turns her head to look into the distance, seaside at dusk, side backlight, hair moving in the wind, low-angle camera slowly following. With all four parts present, the model knows what moves, where the light comes from, and where the camera sits.

Then add a negative prompt to suppress common problems: no text, no watermark, no extra fingers, no facial distortion, no rapid flicker.

Image-to-video: start with a reference portrait

When a character appears across multiple shots, don't force it with text-to-video. Generate a clean character image in Jimeng's drawing tools first, then animate that image. Character, clothing, and setting stay consistent from shot to shot. This is the most effective way to avoid a different face in every clip.

The focus of the prompt shifts: instead of what the subject looks like, describe how it moves, the rhythm of the walk, how far the head turns, how the hem and hair drift, whether the camera pushes in or orbits.

First frame + last frame: let the model handle the transition

Jimeng lets you specify both a first and a last frame. Give it a starting image and an ending image, and the model fills in the middle. This works well for transitions like day to night, interior to exterior, or close-up to wide shot. Keep the composition of the two frames reasonably close; large differences tend to dissolve into mush.

Where Jimeng shines, and where it doesn't

For traditional Chinese aesthetics, landscapes, and food, Jimeng's detail is dependable and its Chinese comprehension is strong. Describe "blue-green shanshui" or "steam rising from a wok" and it understands. Complex character motion, multi-person interaction, and precise lip sync remain weak spots; those shots are easier to hand to Kling.

Working with CapCut

Generated assets can go straight into CapCut, skipping the download-and-import detour. Once there, work in the order stitch → voiceover → subtitles → music, then export at 1080P. Create the project at 9:16 from the start; don't force a vertical crop inside a landscape project.

Common problems

• The face changes between shots: switch to image-to-video and keep the same base image.
• Motion looks stiff: shorten each shot and describe only one main action.
• The image looks blurry: remove conflicting descriptions from the prompt, reduce complexity first, then add detail back.
• Not enough credits: test at low resolution, go high-def only after confirming; credits and pricing follow the official source.

To compare generation tools side by side, see the tool library; for the full chain from topic selection to publishing, see the learning path.