Seedream Character Consistency: Multi-Reference Editing for Personas

Seedream character consistency comes from reference images: upload approved views of your persona, tell the model which image supplies the character and what must stay the same, then describe the new scene. ByteDance's documentation sets the limit at 10 reference images per request on Seedream 5.0 pro and flash, and 14 on Seedream 5.0 lite, 4.5 and 4.0, which can also return a whole set of related images from one request.

Built from ByteDance's own pages, checked October 2026: the BytePlus ModelArk image generation tutorial, image generation API reference, Seedream prompt guide, Seedream 5.0 pro and flash tutorial, model pricing and Acceptable Use Policy, plus ByteDance Seed's Seedream 5.0 Pro and Seedream 4.5 pages. We have not scored Seedream's identity accuracy; the last section shows how to run that comparison on your own character.

If you came here for Seedream 4, the line has moved: Seedream 5.0 pro is the model ByteDance Seed now lists, and 4.5 and 4.0 are still offered beside it with different strengths. This tutorial covers which one to pick for a persona, the reference workflow, the prompt rules from the official guide, and what each request costs. For how reference models compare with ID adapters and LoRAs, start at our consistent character AI guide.

What you will have at the end

A hero image, a small set of approved views, prompt patterns for scenes and outfit swaps, and a rough cost per keeper.

Seedream 4 character consistency or Seedream 5.0: pick the model

All five current models accept reference images. They differ in how many, and in whether one request can return a set.

• Seedream 5.0 pro and flash are the newest. They generate one image per request, take up to 10 references, and add interactive editing: you mark a region with a box, arrow or doodle and the edit lands there. ByteDance describes pro as the higher-quality option and flash as faster and cheaper.
• Seedream 5.0 lite, 4.5 and 4.0 take up to 14 references and support batch output, which the prompt guide describes as image sequences with consistent character continuity and a unified style.
• Seedream 4.5 is the version ByteDance Seed describes as preserving the reference image's facial features, lighting and colour tone, and accurately identifying target elements across multiple inputs.

A practical split: build the hero and the reference views on the model whose look you prefer, then use a batch-capable model when you need a week of posts from one reference set. On Seedream 5.0 pro, BytePlus notes that 1.5K costs the same as 1K and gives better quality, so there is no reason to render at 1K.

Seedream character consistency, step by step

These are prompt patterns adapted from the examples in ByteDance's documentation. Swap the bracketed parts for your own; they are starting points, not prompts we scored.

1. Hero (text only)
A photorealistic studio portrait of a fictional 28-year-old woman with [identity block]. Front-facing, neutral expression, soft even light, plain light-grey background, head and shoulders.

2. Reference view (one image in)
Based on the character in the reference image, generate a studio portrait in profile facing right. Keep her face, hair and skin unchanged. Plain light-grey background.

3. New scene (reference set in)
Based on the character in Image 1 and Image 2, keeping her facial features, hair and build, generate a photo of her [action] in [place]. [Light]. [Framing], vertical 4:5.

4. Outfit swap (persona plus garment)
Dress the character in Image 1 with the outfit from Image 2, keeping her face, hair and pose unchanged.

5. Batch set (Seedream 5.0 lite, 4.5 or 4.0)
Referring to Image 1, generate a set of 4 photos of the same woman: reading at a cafe window, walking a city street, cooking at home, on a balcony at sunset. Keep her face, hair and build identical in every image.

In the API, references go in the image field as URLs or Base64 strings, and the documentation's examples number them in the order you pass them. For step 6, set sequential_image_generation to auto; the model then decides how many images to return from the prompt, up to max_images. To write the identity block for step 1, our free AI influencer prompt generator builds one from a persona brief.

Seedream 4.5 prompt guide: the rules that matter for a persona

BytePlus publishes a prompt guide written for Seedream 4.5 and 4.0, and the API reference points all models to it. Five of its rules do most of the work for character consistency:

1. Write natural language, not tags. Describe subject, action and environment in coherent sentences. The guide says concise, precise prompts usually beat stacked ornate vocabulary.
2. Say what stays fixed. For edits, use unambiguous instructions and, if other elements should remain unchanged, specify that explicitly.
3. Avoid vague pronouns. The guide's own example of what not to write is "Put that one in pink clothes".
4. Name the reference target and the new scene. With a reference image, describe what to extract and keep, such as the character design, and then the scene you want.
5. Give each image a role. With several inputs, state what to reference or edit from each one, by image number.

Keep the whole prompt under 600 English words. BytePlus warns that very long prompts scatter information, so the model keeps the main elements and drops details, and the details are where a face lives.

Seedream multi image fusion: outfits, products and shared scenes

Multi-image fusion, which the tutorial calls multi-image blending, generates one image from several inputs. BytePlus describes merging clothing, shoes and accessories with model photos, or combining people with landscapes. For a persona it does three jobs.

• Outfit swaps. The documented pattern is "Replace the clothing in image 1 with the outfit from image 2." Give the garment its own image instead of describing it; a pattern or logo is easier to copy than to describe.
• Product shots. Persona in image 1, product in image 2, and a line saying how she holds it and that the label stays legible.
• Two personas in one frame. One image per person, each named by number, with left and right stated. Every extra identity is another face to mix up, so check both against their own references.

On Seedream 5.0 pro and flash you can go further and mark the edit region on the image with a box or arrow, which tells the model exactly where the change belongs. The same naming discipline works in other reference models; our Gemini face consistency prompts use it for Nano Banana, and consistent characters without a LoRA ranks the no-training methods side by side.

How many references? Run the 1, 4 and 10 test yourself

More references is not automatically better: each one is more for the model to reconcile, and near-duplicates add little. We have not measured where the returns flatten, and the answer depends on your character, so measure it on yours.

1. Write one scene prompt that names the character and what to keep. Do not change it during the test.
2. Run it with 1 reference (the hero), then 4 (hero plus three views), then 10 (add approved scene outputs).
3. Generate the same number of images at each count, on the same model and size.
4. Score each output against the hero on two things: identity landmarks (eyes, nose, jaw, hairline) and garment detail (fabric, print, fit).
5. Count keepers per count, then divide the spend by the keepers.

That arithmetic uses BytePlus's published rates (checked October 2026): on Seedream 5.0 pro the first input image is free and each further one is $0.003. On flash, lite, 4.5 and 4.0, input images are free, so reference count does not change the bill. The number worth tracking is cost per keeper, not cost per request.

Limits and troubleshooting

• No batch on pro or flash. BytePlus says sequential image generation is not currently supported on Seedream 5.0 pro and flash. Use lite, 4.5 or 4.0 for sets.
• No seed or negative prompt in the API reference. The request parameters it lists are the model, prompt, images, size, prompt optimization, output format, background, sequential generation, streaming and watermark. Describe what you want positively.
• A watermark you did not expect. The watermark parameter defaults to true and adds an "AI-generated" mark in the lower-right corner.
• A broken link the next day. Image URLs are kept for 24 hours. Download on generation.
• The face holds in portraits and slips in wide shots. The face has too few pixels. Render larger, crop tighter, or add a reference at that distance.
• The set drifts by image four. Ask for fewer images per request and restate "identical in every image". For causes that are not specific to Seedream, see our AI face consistency guide.

Other hosts offer Seedream models too. Their reference limits, prices and content rules are their own, so read the host's page instead of assuming these numbers.

When references are not enough, and what to do with the stills

Reference editing rereads the face on every request. When you need the same persona across hundreds of images and unusual angles, a trained LoRA on an open model stores the face in weights; the approved Seedream outputs become your dataset, and our character LoRA dataset checklist shows what to collect. When you need motion, consistent stills are the input: see AI video character consistency for the grid-sheet method and Seedance AI video for ByteDance's own video model.

The AI Influencers program goes deeper where this tutorial stops, with lessons on creating the persona, LoRA training for consistent faces, photorealism and image-to-video pipelines.

Whose face you can use

An original persona or your own. BytePlus's Acceptable Use Policy (effective September 30, 2026) prohibits depicting any person's voice or likeness without appropriate consent or rights, and impersonating a person without legal authorization or explicit disclosure. Check a new hero for accidental resemblance to a real person before you build a feed on it; our AI likeness rights guide explains why that matters.

Seedream character consistency: FAQ