Keeping a character consistent across AI images comes down to giving the generator the same anchors every time: a fixed written description, one or more reference images, and a stable style. Image models do not "remember" a character between prompts, so consistency has to be built into your process rather than hoped for. The techniques below work, in varying degrees, across most modern image tools.
Why characters drift
A text-to-image model starts each image from random noise and steers it towards your prompt. If your prompt says "a woman with short red hair in a green coat", there are countless images that fit, and the model will pick a different one each time. Change the scene, lighting or camera angle and the drift gets worse, because the model has to reinterpret the character in a new context.
Common signs of drift:
- Face shape, age or ethnicity changes between shots.
- Hair length, parting or colour shifts.
- Clothing gains or loses details: a zip becomes buttons, a logo appears.
- Proportions change, particularly in wide shots.
- The art style itself wanders, from painterly to glossy 3D.
Viewers notice all of these, especially the face and the outfit. In a story video, a character who looks different in every scene breaks the illusion faster than almost anything else.
Step 1: Write a fixed character description
Before generating anything, write a short, specific description and treat it as a locked block of text you paste into every prompt unchanged. Be concrete about the features that identify the character:
MAYA: woman in her early thirties, round face, warm brown skin,
dark brown eyes, black curly hair in a high puff, small gold hoop
earrings, mustard-yellow knitted jumper, dark green corduroy trousers,
white trainers with a red stripe.
Guidelines for the description:
- Name distinctive features, not vague qualities. "Round face, small gold hoops" helps; "beautiful, friendly" does not.
- Keep the outfit simple. Solid colours and one or two distinctive details are much easier to repeat than complex patterns.
- Give each character a colour signature. A mustard jumper is easy to spot and helps viewers track the character even when the face is small in frame.
- Do not reword it. Changing "curly" to "coily" in one prompt is enough to change the result.
Then build each prompt as: style block + character block + scene description + camera. Only the scene and camera parts change from shot to shot.
Step 2: Make a character sheet
A character sheet is a single image showing the character from several angles, usually front, three-quarter and side, often with a couple of expressions. It serves two purposes: it forces you to settle on one version of the character, and it becomes the reference image for everything that follows.
Generate plenty of candidates and pick one you are happy with. Look closely at the details you will need to repeat: the hairline, the ears, the shoes. If something is odd in the sheet, it will be odd in every scene. Fix it now, with inpainting or a regeneration, rather than later.
Save the chosen sheet somewhere permanent in your project, alongside the text description, so the whole team works from the same source. A clear project folder structure helps here.
Step 3: Use reference images, not just text
Text alone rarely gives reliable consistency. Most current tools offer some way to feed in an image as a reference, and this is the single most effective technique. Depending on your tool, it may be called image-to-image, image prompt, character reference, style reference, or "ingredients".
The approaches differ in what they preserve:
| Technique | What it holds | Trade-off |
|---|---|---|
| Image-to-image | Overall composition and colours of the source | Changing the pose or scene is harder |
| Character or subject reference | Identity (face, hair, outfit) | Quality varies between tools |
| Style reference | Rendering style, palette, texture | Does not hold identity on its own |
| Adapter models (e.g. IP-Adapter in open-source pipelines) | Identity or style from an image | Needs a local setup such as ComfyUI |
| Trained LoRA | A learned character that can be posed freely | Needs 15–30 good training images and time to train |
In practice, combine them: character reference from your sheet, style reference from a finished scene you like, and the fixed text description on top.
When to train a LoRA
If a character will appear in dozens of videos, training a small LoRA (a lightweight add-on to an open model) can be worth the effort. You generate or draw a varied set of images of the character, caption them, train, and from then on the model can produce the character from a trigger word. It is more work up front, and it only applies to tools that let you load your own models, but it gives the most control for long-running series.
Step 4: Control the variables you are not changing
Every variable you leave open is another chance for drift.
- Seed. In tools that expose a seed, keeping it fixed while you adjust the scene can reduce variation. It is not a guarantee of consistency on its own, because any change to the prompt changes the result.
- Style block. Keep the style wording identical across the project: medium, lighting approach, colour palette, lens.
- Aspect ratio and resolution. Changing shape changes composition, and characters often shift with it.
- Model version. Tools update their models. Note which version you used, and avoid switching mid-project.
- Pose control. Open-source pipelines can use ControlNet with an openpose or depth map to fix a pose while the reference handles identity.
Step 5: Fix, do not regenerate everything
Even with good references, some images will be slightly off. Rather than regenerating a whole scene that is otherwise right, use targeted fixes:
- Inpainting to repaint just the face, the hands or a wrong detail, using the character sheet as reference.
- Face-focused passes in tools that support them.
- Manual touch-ups in an image editor for small colour or logo fixes.
Keep a simple review step: put the character sheet next to each new image and compare face, hair, outfit and colour signature. If you are generating many variations per scene, a batch tool such as the Image Replicator can help keep numbered files per scene organised, and our guide to batch renaming image sequences covers naming.
Planning shots that are easier to keep consistent
Some shots are much harder than others. You can make life easier at the planning stage (see storyboarding AI video):
- Medium shots are the most reliable. Faces are large enough to hold identity, and the outfit is visible.
- Extreme close-ups are fine for faces but can lose the outfit cues.
- Wide shots make faces tiny, so rely on the colour signature and silhouette.
- Two characters in one image is the hardest case; features often blend. Consider generating them separately and compositing, or use regional prompting where the tool supports it.
- Back and over-the-shoulder shots are forgiving, and useful for cutaways.
If you are turning stills into motion, gentle camera moves on a consistent still often work better than asking a video model to animate a character. Our guide to the Ken Burns effect shows how.
Rights and responsibility
Do not build a "consistent character" from a real person's likeness without their consent, and avoid prompts that name living people or copyrighted characters. If you publish realistic synthetic imagery on YouTube, check whether it needs to be disclosed; our YouTube AI disclosure guide explains the rules.
Quick checklist
- Write one fixed character description and paste it unchanged into every prompt.
- Generate and lock a character sheet before making scenes.
- Use the sheet as a character reference, plus a style reference for the look.
- Keep style wording, aspect ratio and model version fixed for the project.
- Favour medium shots; use colour signatures for wide shots.
- Fix faces and details with inpainting rather than regenerating good scenes.
- Compare every image against the sheet before it goes into the edit.
FAQ
Can I get perfect consistency from text prompts alone?
Rarely. A detailed, unchanged description helps a lot, but without a reference image or a trained model, small differences in face and outfit will almost always creep in.
Does using the same seed keep my character the same?
It helps reduce variation in tools that expose seeds, but any change to the prompt produces a different image. Treat seeds as a minor aid, not the main technique.
How many reference images do I need?
For character-reference features, one clear character sheet is often enough. For training a LoRA, you typically need a varied set of roughly 15 to 30 good images.
Why does my character's outfit keep changing?
Complex clothing is hard to reproduce. Simplify it to solid colours with one or two distinctive details, describe those details identically every time, and include the outfit clearly in your reference image.