Bytedance Seedream V4.5 Edit Sequential
Playground
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_images | Total price |
|---|---|
| 1 | $0.04 |
| 4 | $0.16 |
| 8 | $0.32 |
How to use
-
Upload source images Add the images you want to edit sequentially (all should contain the same main subject or product).
-
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.”
-
Set max_images Specify how many edited outputs you want the model to generate from your input set.
-
Choose size Select the target resolution, up to 4096 × 4096 for maximum detail.
-
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!
-
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.
-
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.
-
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
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| images | array | Yes | [] | 1 ~ 10 items | The images to edit. A maximum of 10 reference images can be uploaded. |
| size | string | No | - | 1024 ~ 4096 per dimension | Specify the width and height pixel values of the generated image. |
| max_images | integer | No | 1 | 1 ~ 15 | The 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_output | boolean | No | false | - | 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_mode | boolean | No | false | - | 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
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Array of URLs to the generated content (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
| data.model | string | Model ID used for the prediction |
| data.outputs | string | Array of URLs to the generated content (empty when status is not completed). |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |