Consistent Characters: Which AI Platform for What Job

One good image of a character is easy. Twenty images of the same character, in different poses, outfits and places, is the hard part, and it is what any real project needs: a picture book, a campaign, a short film, a brand mascot. Every major platform now has a tool aimed at it, but they work in different ways and suit different jobs. This guide compares them by what they are known for, then gives a workflow that holds up whichever tool you use. For platform-specific detail, follow the links to the individual guides.

The platforms at a glance

Names and limits change with every release. Where a platform retires a feature (Midjourney has changed its character tool twice), look for the function, not the label.

Stills: reference images versus a trained identity

Most image tools work from reference images. You attach one or more pictures of the character and the model keeps it recognisable in a new scene. Nano Banana 2.1 is the most generous here, accepting up to 14 references and keeping up to four characters consistent, which makes it the obvious pick for group scenes. FLUX.2 takes up to eight references through its API and ten in the BFL playground, with output up to 4 megapixels. Midjourney splits by version: Omni Reference works only in V7 and takes a single image, while the V8.2 Edit Model takes up to four references and replaces Omni Reference for V8. See How to Make Consistent Characters in Midjourney. ChatGPT Images 2.5 works conversationally, and OpenAI says details now stay consistent across multiple edits; the approach is covered in ChatGPT Image Edits and References.

A trained identity is different. Higgsfield Soul ID asks for 20 or more photos of one person and stores a reusable identity that holds across styles and angles. Higgsfield is clear that it is for real people’s photos, covers one person per ID, and stays inside Higgsfield. It suits a creator who wants themselves, or a consenting model, in many images. For invented characters, reference-based tools are simpler. Dzine and SeaArt have their own approaches, covered in Dzine Consistent Characters and SeaArt Consistent Characters.

Video: the same character across shots

In video, the character must survive movement, new angles and cuts. Runway Gen-4 References keeps characters, objects and places recognisable across new shots; see Runway Gen-4 References. Kling 3.0 accepts reference videos and several image references, and its Omni model can take a character’s visual traits and voice from a reference video and carry them into new scenes. Google Flow offers Ingredients for Veo 3.1, and Google says Gemini Omni Flash preserves identity and voice across every scene. Seedance 2.0 lets you tag each reference with a role in the prompt. Vidu is also known for reference-to-video.

Voice is the new part of consistency. If a character speaks in more than one clip, a tool that keeps the voice as well as the face saves a lot of re-dubbing.

A workflow that holds up

1. Design once. Generate the character until you have one strong, well-lit, front-facing image you are happy with. This is your master.
2. Make a character sheet. From the master, produce a front view, a profile, a three-quarter view and a full-length shot. These become your references.
3. Fix the description. Write the character’s description once (age, hair, clothing, one distinctive detail) and paste it unchanged into every prompt.
4. Animate approved stills. For video, start each shot from an approved still of the character rather than from text alone. See Image to Video: Which AI Platform for What Job.
5. Keep the references with the results. When a shot works, you need to know exactly which reference images and settings produced it. Dreamdrive keeps every image and clip with its prompt, model and settings, which makes the winning combination easy to find again.

For real people, get written consent before using their likeness, and check each platform’s rules on depicting real individuals.

Try it

Create a master image of an invented character, then run this prompt with that image as the reference on two or three tools.

The same woman from the reference, now sitting on a tram at night, looking out of the window, city lights reflected on the glass, wearing the same green scarf, medium shot, soft practical light

Compare three things: is the face recognisably the same person, did the scarf survive, and did the new lighting change her features? Then animate the best result in two video tools and check whether she still looks like herself after three seconds of movement. Write down which model and version you used, because consistency is one of the fastest-moving areas in AI.