Browse ModelsBytedanceBytedance Seedream V4.5 Edit Sequential

Bytedance Seedream V4.5 Edit Sequential

Bytedance Seedream V4.5 Edit Sequential

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Try it on WavespeedAI!

Seedream 4.5 Edit Sequential performs multi-image editing while locking character and object identity across shots. It detects main subjects, preserves continuity, and applies controlled edits with up to 4K output. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Features

bytedance/seedream-v4.5/edit-sequential

Seedream 4.5 Edit Sequential is ByteDance’s multi-image editing model designed to apply the same edit across a whole set of images. It automatically tracks the main subject through the series, keeps identity stable, and generates clean, high-resolution results—ideal for campaigns, product sets, and character line-ups.


Model highlights

  • Multi-image subject tracking – Detects the main subject across all input images and treats them as the same person or object.
  • Character consistency lock – Preserves facial structure, proportions, and overall identity across every edited output.
  • High reference fidelity – Maintains lighting, colour balance, and key visual details while applying the requested changes.
  • Controlled, repeatable edits – One prompt drives a consistent transformation across the entire batch.
  • 4K-ready resolution – Supports sizes up to 4096 × 4096 for print-adjacent and hero visual use.
  • Production quality – Sharp edges, low artifacts, and stable composition suitable for professional workflows.

Best suited for

  • Batch portrait editing with a fixed style or look
  • Product series images that must feel like one coherent set
  • Brand or ad campaign iterations with the same model or hero product
  • Character design variations (outfits, moods, lighting)
  • E-commerce catalog refreshes and seasonal updates
  • Social / marketing visual series where continuity matters

Pricing

Billing is per output image, scaled by the max_images you request.

  • Base price: $0.04 per image
  • Formula: total_price = $0.04 × max_images

Example costs:

max_imagesTotal price
1$0.04
4$0.16
8$0.32

How to use

  1. Upload source images Add the images you want to edit sequentially (all should contain the same main subject or product).

  2. Write the edit prompt Describe the shared change you want across the whole set, e.g. “Change outfit to a black suit, add soft studio lighting, keep poses and background the same.”

  3. Set max_images Specify how many edited outputs you want the model to generate from your input set.

  4. Choose size Select the target resolution, up to 4096 × 4096 for maximum detail.

  5. Run and review Submit the job, inspect the edited series, and optionally refine the prompt for another pass.


Tips for best results

  • Use clear, global instructions in the prompt (“add winter outfit and snow ambience”) rather than per-image directions.
  • Keep input images reasonably consistent in framing and lighting so the model can lock onto the same subject.
  • Put your cleanest, clearest reference image first; the model tends to rely on it most strongly for identity.
  • For campaign work, generate at the highest resolution you need once, then downscale for web or social formats.

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)


More Models to Try!

  • Nano Banana Pro

    Google’s ultra, fast text-to-image model for generating many ideas from scratch; great for large batches of new images, not for editing existing photo series.

  • Seedream V4

    ByteDance’s high-resolution text-to-image generator with rich detail and diverse styles; ideal when you want new scenes in the Seedream aesthetic rather than editing your own photos.

  • Qwen Image Edit Plus

    Single-image, prompt-based editing with strong semantic understanding; perfect for one-off or small-batch edits where you don’t need strict identity matching across many images.

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-v4.5/edit-sequential" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "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.
imagesarrayYes[]1 ~ 10 itemsThe images to edit. A maximum of 10 reference images can be uploaded.
sizestringNo-1024 ~ 4096 per dimensionSpecify the width and height pixel values of the generated image.
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

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray 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.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
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