WaveSpeedAI APIBytedanceBytedance Seedream V4 Edit Sequential

Bytedance Seedream V4 Edit Sequential

Bytedance Seedream V4 Edit Sequential

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Seedream 4.0, Image Generation with 4K Resolution · Editing · Character & Object Consistency · Multi-Image Generation in Sequence. Price = unit_price * max_images

Features

bytedance/seedream-v4/edit-sequential

What is it?

Seedream v4 Edit Sequential is ByteDance’s image-to-image model for editing a source image and generating a sequence/group of consistent outputs in one pass. It’s built for high feature retention (identity, logos, layout) and cross-image style continuity—ideal for matched sets, story panels, or product variants.

What makes it stand out?

  • I2I + sequential in one pipeline – Edit a single source and produce N coherent images (series/panels) without switching models.
  • Five core strengths – Precise instruction editing, high feature retention, deep scene understanding, ultra-fast inference, ultra-high-res output.
  • Consistency controls – Strong identity/style preservation across all images in the set.
  • Rich edit ops – Add/remove elements, attribute/style change, structural tweaks (e.g., pose/face swap), texture/brush/frame edits.

Designed for

  • Commercial design — Posters, apparel, packaging, e-commerce sets; fast, brand-safe varianting.
  • Entertainment IP — Character look-dev, key art sequences with locked identity.
  • Fine art & Illustration — Multi-piece series with coherent palette and linework.
  • Architecture — Material/lighting variations across consistent viewpoints.
  • Brand content — Campaign sets and social carousels with fixed logo/palette.

How to use

  1. Inputs: Upload several source images.
  2. Prompt: Write the instruction and repeat the same N in text (e.g., “a series of N images / Panels 1–N”) to lock count & continuity.
  3. Count: Set max_images = N for the number of images.
  4. Control the size: the max size is 4096 * 4096.
  5. Generate → review → iterate (reuse or change seed for A/B).

Please Note: Declare the number of images twicemax_images = N and inside the prompt!

Price

  • $0.027 per image.
  • Total price = max_images * $0.027

Prompting guide

  • Edit instruction (per set) Replace [object A] with [object B]; keep [logo/identity/features]; preserve [lighting/style].

  • Sequential consistency (count locked) Generate a series of [N] edited images (Panels 1–[N]) from the source, maintaining the same [character/product/logo] identity, palette, and composition style.

    Panel 1 — [edit/shot] Panel 2 — [edit/shot] … Panel N — [edit/shot]

  • Terminology Use precise, domain-native terms (photography, fashion, architecture) to match expectations.

Example (product variant set, N=4)

Set max_images = 4 and use:

Generate a series of 4 edited images (Panels 1–4) from the source photo, keeping the same shoe model and logo placement. Maintain identical angle, lighting, and background; change only the colorway per panel:

Panel 1 — classic white + black swoosh

Panel 2 — navy + gold accents

Panel 3 — matte red + white outsole

Panel 4 — forest green + gum sole

Ensure consistent proportions, stitching detail, and material texture across all 4 panels.

Note

Please set the max_image first, and then input how many images you want to generate in prompt! Such as:

  • max_image = 4.
  • Prompt: I want to generate 4 images… + (your prompt)
Aspect RatioExact (W×H)Exact PixelsRounded (W×H, ÷64)Rounded Pixels
1:11448 × 14482,096,7041408 × 14081,982,464
3:21773 × 11822,095,6861728 × 11521,990,656
4:31672 × 12542,096,6881664 × 12162,023,424
16:91936 × 10892,108,3041920 × 10882,088,960
21:92212 × 9482,096,9762176 × 9602,088,960
1:11024 × 10241,048,5761024 × 10241,048,576
3:21254 × 8361,048,3441216 × 8321,011,712
4:31182 × 8871,048,4341152 × 8961,032,192
16:91365 × 7681,048,3201344 × 7681,032,192
21:91564 × 6701,047,8801536 × 640983,040
1:1323 × 323104,329320 × 320102,400
3:2397 × 264104,808384 × 25698,304
4:3374 × 280104,720448 × 320143,360
16:9432 × 243104,976448 × 256114,688
21:9495 × 212104,940576 × 256147,456

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/bytedance/seedream-v4/edit-sequential" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "size": "2048*2048",
    "max_images": 1,
    "enable_base64_output": false,
    "enable_sync_mode": false
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagesarrayNo[]-The images to edit. A maximum of 10 reference images can be uploaded.
sizestringNo2048*20481024 ~ 4096 per dimensionThe size of the generated media in pixels (width*height).
max_imagesintegerNo11 ~ 15The maximum number of images that can be generated (up to 15). This value must align with the number of images specified in the prompt above.
enable_base64_outputbooleanNofalse-If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.
enable_sync_modebooleanNofalse-If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

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