Jimeng AI Image Guide: Usable Results from Chinese Prompts

This guide shows how to get usable images out of Jimeng AI with prompts written in plain Chinese, and how to finish them on the smart canvas instead of rerolling again and again.

Why start with a Chinese-first tool

Jimeng AI is ByteDance's image product. The web entry point is jimeng.jianying.com, there is a mobile app of the same name, and the international version is called Dreamina. Its main difference is that it is native to Chinese: you can type a Chinese prompt directly, with no mental translation step.

That matters more in practice than it sounds. Vague Chinese descriptors such as a sense of atmosphere, negative space, national style or everyday warmth are understood reasonably well. Models trained mainly on English tend to collapse those words into a generic high-saturation, high-contrast look. Local aesthetic preferences in the training data also raise the hit rate for portraits, seasonal themes and everyday scenes.

The platform covers text-to-image, image-to-image, a smart canvas, style transfer and style extraction from reference images. It also has video tools, which are covered in a separate guide.

Your first generation

Open image generation, type one sentence, pick a ratio, and generate. Each run returns four images in roughly eight to twelve seconds per image.

The first run is for learning the model's defaults, not for producing a final asset. Leave style strength and model tier alone and run two or three rounds with default settings. Watch how it fills gaps: realistic or illustrative, centred or generous with empty space. Knowing the baseline is what makes later adjustments meaningful.

A four-part prompt formula

You do not need an elaborate structure. Four parts cover most briefs: subject, action, environment, light and style.

For example: a woman in a beige knit sweater sitting by the window turning a page, afternoon side light, shallow depth of field, Japanese film texture, quiet. Subject, action, setting and light are all present, with nothing wasted.

• Put the most important words first. Early tokens carry more weight.
• One idea per image. Asking for a person, a product, a landscape and a headline at once usually yields four unclear things.
• Give vague words somewhere to land. After "a sense of atmosphere", add warm tone, low contrast, slight grain, so the model knows which direction to take.

Finish with a short exclusion line: no text, no watermark, no extra fingers. It works better than repeating please do not in the body of the prompt.

Choosing one image out of four

Do not pick the prettiest frame. Judge in this order:

1. Is the subject intact? Check faces, hands, edges and product geometry.
2. Is there room for type? A cover needs a clean area for the headline.
3. Does the style match your account? Consistency beats novelty.
4. Does it hold up when enlarged? A good thumbnail is not proof; inspect at full size.

Choose the repairable frame, not the most attractive one. If composition and subject are right, broken hands, clutter and proportion problems can be fixed on the canvas. A bad composition cannot. Once you pick, copy the prompt and change one variable at a time, so you learn which word did what.

The smart canvas in four moves

The canvas is Jimeng's real advantage: generation and retouching happen in one place, with no export to another editor.

• Local redraw: broken hands, wrong expression, an extra or misplaced object. Mask the area and describe the fix, for example a relaxed right hand hanging naturally. Only that region is regenerated.
• Outpainting: the ratio is wrong, you need empty space for a title, or a vertical image must become horizontal. Extend the frame and let the model complete the edges.
• Erase: passers-by, cables, clutter on the table, leftover text fragments. Mask and remove; the background is filled in.
• Cutout: the subject needs a different background, must become a cover element, or goes into a slide. Isolate it with a transparent background.

Add layers and you can separate person, props and type, then change one without disturbing the rest. Work in this order: fix composition with outpainting, repair the subject with redraw and erase, cut out last. Reversing it wastes work; cut out first and outpainting will regenerate your edges.

Building a series with reference images

The biggest risk for a content account is style drift. Upload one image you are happy with as a style reference, then change only the subject. Keep ratio, keyword order and style strength fixed.

Before batch running, write the prompts for six to eight images at once and check that their style sections are identical. Improvising each prompt guarantees a scattered set. The first image is the master: its value is not the frame itself but the definition it gives every frame after it.

Making the free tier work

The free allowance is a daily login credit that refreshes each day, with one credit roughly equal to one standard image. Observed daily grants vary, commonly in the range of sixty to one hundred credits, and the number changes often, so treat the official page as the source of truth.

A run of four images costs about four credits, which is enough for light daily use. The sensible strategy is to test composition cheaply, then spend on quality once a direction is chosen. Do not burn credits rerolling four images after changing a single adjective.

Be clear about limits: free exports are restricted in resolution and watermarking, and higher-tier models or 4K export usually require a membership. Commercial terms follow the membership agreement, so do not assume the free tier is licensed for client work.

From image to video cover

Jimeng is connected to Jianying and the wider Douyin ecosystem, so images can move straight into Jianying for covers and short-video assets, skipping an export step. For covers, keep three things in mind: place the subject to one side and leave a text zone, keep contrast high, and check legibility at phone size. In a feed the cover is thumbnail-sized; fine detail is invisible.

Three mistakes worth repeating: cramming too many elements into one frame, assuming the free tier is commercially usable, and accepting the first round as final. The last one costs the most time, because rework usually surfaces at the layout stage, when changes are most expensive.

For the wider tool landscape, read the AI image tools introduction. For the full path from brief to delivery, see the AI image workflow guide. For what happens after the image reaches the editor, see AI editing in Jianying.