Bytedance Seedream V4 Edit Sequential
Playground
Try it on WaveSpeedAI!Seedream 4.0: 4K image generation and editing with character and object consistency and sequential multi-image outputs. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
What is it?
Seedream v4 Edit Sequential is 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
- Inputs: Upload several source images.
- 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.
- Count: Set max_images = N for the number of images.
- Control the size: the max size is 8192 * 8192.
- Generate → review → iterate (reuse or change seed for A/B).
Please Note: Declare the number of images twice — max_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)
Recommended Resolutions
| Aspect Ratio | Exact (W×H) | Exact Pixels | Rounded (W×H, ÷64) | Rounded Pixels |
|---|---|---|---|---|
| 1:1 | 1448 × 1448 | 2,096,704 | 1408 × 1408 | 1,982,464 |
| 3:2 | 1773 × 1182 | 2,095,686 | 1728 × 1152 | 1,990,656 |
| 4:3 | 1672 × 1254 | 2,096,688 | 1664 × 1216 | 2,023,424 |
| 16:9 | 1936 × 1089 | 2,108,304 | 1920 × 1088 | 2,088,960 |
| 21:9 | 2212 × 948 | 2,096,976 | 2176 × 960 | 2,088,960 |
| 1:1 | 1024 × 1024 | 1,048,576 | 1024 × 1024 | 1,048,576 |
| 3:2 | 1254 × 836 | 1,048,344 | 1216 × 832 | 1,011,712 |
| 4:3 | 1182 × 887 | 1,048,434 | 1152 × 896 | 1,032,192 |
| 16:9 | 1365 × 768 | 1,048,320 | 1344 × 768 | 1,032,192 |
| 21:9 | 1564 × 670 | 1,047,880 | 1536 × 640 | 983,040 |
| 1:1 | 323 × 323 | 104,329 | 320 × 320 | 102,400 |
| 3:2 | 397 × 264 | 104,808 | 384 × 256 | 98,304 |
| 4:3 | 374 × 280 | 104,720 | 448 × 320 | 143,360 |
| 16:9 | 432 × 243 | 104,976 | 448 × 256 | 114,688 |
| 21:9 | 495 × 212 | 104,940 | 576 × 256 | 147,456 |
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic ocean wave at sunrise, highly detailed",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"max_images": 1
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/bytedance/seedream-v4/edit-sequential" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
-H "Content-Type: application/json" \
-d "${REQUEST_BODY}")
TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body \
"${RESULT_URL}" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}")
RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')
case "${STATUS}" in
completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
esac
doneParameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| images | array<string> | Yes | - | 1 ~ 10 items | The images to edit. A maximum of 10 reference images can be uploaded. |
| 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 set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN. |
| enable_sync_mode | boolean | No | false | - | If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models. |
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 | Output values, usually URL strings; some models return text strings or structured result objects (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 |
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 |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<string | object> | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to poll for the prediction result |
| data.status | string | Status: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created |
| 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 |