Seedream 5.5 Edit by ByteDance edits and generates images from single-image or multi-reference inputs, supporting up to 10 reference images, consistent multi-turn edits, native transparent-background output, and 1K, 1.5K and 2K output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
En attente
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$0.0266par exécution·~37 / $1
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Transform only the billiard balls into miniature realistic planets, each with distinct clouds, oceans, rings, rocky surfaces, or atmospheric patterns, while preserving their original size, position, shadows, and glossy reflections. Preserve the woman, face, hairstyle, clothing, cue, pose, table, lighting, and camera angle.
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Change the scene to a rainy blue-hour evening: rain on the window, warm lamps glowing inside the cafe, keep the barista, the customer, the chalkboard and the composition unchanged
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Print the fox mascot from the second image as a small label on the frosted glass bottle from the first image, keep the bottle, the stone, the lighting and the composition unchanged
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Extract the sneaker on its own, remove the backdrop and the floor shadow
Seedream 5.5 Edit edits and composes images from one or several reference images. It is designed to preserve unedited areas across repeated edits, supports output up to 2K, and can return a result with a transparent background.
Consistent edits
Built to preserve unedited areas, so you can refine an image over several rounds.
Multi-image reference editing
Use up to 10 reference images for complex edits, compositions, and visual guidance.
Natural language editing
Describe the desired edit in plain text and let the model transform the input images accordingly.
Native transparent background
Set background to transparent to extract a subject onto a transparent PNG. The inputs do not need an alpha channel.
Flexible resolution tiers up to 2K
Choose 1k or 1.5k for lower-cost edits, or 2k for higher-resolution output.
PNG by default
Output is PNG unless you ask for jpeg.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the desired edit. |
| images | Yes | Reference image URLs or Base64 strings. Supports up to 10 images. |
| aspect_ratio | No | Output aspect ratio: 1:1, 1:2, 2:1, 1:3, 3:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 9:21, or 21:9. Leave empty to keep the aspect ratio of the first input image. |
| resolution | No | Output resolution tier: 1k, 1.5k or 2k. Default: 1k. |
| output_format | No | Output format: png (default) or jpeg. |
| background | No | auto (default), transparent, or opaque. transparent returns an image with an alpha channel and needs png. |
1k or 1.5k for lower-cost edits, or 2k for higher-resolution output.transparent to extract a subject or make a cut-out.Pricing is the output price of the selected resolution plus $0.008 for each input image.
| Resolution | Output Price |
|---|---|
| 1k | $0.02 |
| 1.5k | $0.02 |
| 2k | $0.035 |
| Resolution | Input Images | Cost |
|---|---|---|
| 1k | 1 | $0.028 |
| 1k | 2 | $0.036 |
| 1k | 10 | $0.10 |
| 1.5k | 1 | $0.028 |
| 1.5k | 2 | $0.036 |
| 1.5k | 10 | $0.10 |
| 2k | 1 | $0.043 |
| 2k | 2 | $0.051 |
| 2k | 10 | $0.115 |
background to transparent.1k or 1.5k for iteration and 2k for the final render.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.5/edit with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Seedream v5.5 Edit below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "png",
"background": "auto"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.5/edit" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.5/edit";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "png",
"background": "auto"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "png",
"background": "auto"
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.5/edit", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout", "deleted"}:
raise RuntimeError(result)
time.sleep(2)Seedream v5.5 Edit is a ByteDance model for image editing, exposed as a REST API on WaveSpeedAI. Seedream 5.5 Edit by ByteDance edits and generates images from single-image or multi-reference inputs, supporting up to 10 reference images, consistent multi-turn edits, native transparent-background output, and 1K, 1.5K and 2K output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/bytedance/bytedance-seedream-v5.5-edit.
Seedream v5.5 Edit starts at $0.0266 per run or per second. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `images`, `aspect_ratio`, `resolution`, `background`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/bytedance/bytedance-seedream-v5.5-edit.
Reported generation time on WaveSpeedAI is around 19 seconds per request. This is an estimate, not a latency guarantee; queue time and input settings can change the total wait. live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (ByteDance). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.