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Qwen Image 3.0 Edit

alibaba/

Qwen Image 3.0 Edit is a high-quality image editing model that transforms existing images with natural-language instructions, delivering advanced instruction understanding, superior visual quality, and up to 2K output for creative and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-image
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就緒

Replace the reflection and interior of the astronaut’s helmet with a lush miniature garden. Add flowers, butterflies, green plants, and warm sunlight inside the helmet while preserving the suit, pose, planet, and overall composition.

$0.03每次運行·~33 / $1

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Replace the reflection and interior of the astronaut’s helmet with a lush miniature garden. Add flowers, butterflies, green plants, and warm sunlight inside the helmet while preserving the suit, pose, planet, and overall composition.

Replace the reflection and interior of the astronaut’s helmet with a lush miniature garden. Add flowers, butterflies, green plants, and warm sunlight inside the helmet while preserving the suit, pose, planet, and overall composition.

相關模型

README

Qwen Image 3.0 Edit

Qwen Image 3.0 Edit transforms 1 to 3 reference images using natural-language instructions. Upload source images, describe the desired edit, and generate a refined output while preserving the requested visual context.

Why Choose This?

  • Instruction-based image editing
    Edit images using clear natural-language instructions.

  • Multi-image input
    Use 1 to 3 reference images to provide visual context for the edit.

  • Reference-guided refinement
    Preserve important subject, style, composition, or identity details from the input images.

  • Flexible output sizing
    Choose 1k or 2k resolution and optionally set the output aspect ratio.

  • Prompt expansion support
    Enable intelligent prompt expansion for richer edit interpretation.

  • Seed control
    Use a fixed seed for reproducible results, or -1 for random generation.

Parameters

ParameterRequiredDescription
promptYesText instruction describing the desired edit.
imagesYes1 to 3 input images for editing.
resolutionNoOutput resolution tier: 1k or 2k. Default: 1k.
aspect_ratioNoOutput aspect ratio. Leave empty to use the first input image ratio.
enable_prompt_expansionNoEnable intelligent prompt expansion. Default: true.
seedNoRandom seed for reproducibility. Use -1 for a random seed.

How to Use

  1. Upload input images — Provide 1 to 3 images for editing or reference guidance.
  2. Write your edit prompt — Describe the change you want and what should remain unchanged.
  3. Choose resolution optional — Use 1k for standard output or 2k when higher detail is needed.
  4. Choose aspect ratio optional — Set a specific aspect ratio or leave it empty to follow the first input image ratio.
  5. Set prompt expansion optional — Keep prompt expansion enabled for richer interpretation, or disable it for stricter prompt control.
  6. Set seed optional — Use a fixed seed when you need reproducible results.
  7. Submit — Generate the edited image and retrieve the output URL.

Pricing

Pricing includes input image cost and output image cost.

ItemCost
Input image$0.003 each
1k output image$0.03
2k output image$0.03

Example Costs

Input Images1k Output2k Output
1 image$0.033$0.033
2 images$0.036$0.036
3 images$0.039$0.039

Best Use Cases

  • Photo retouching — Adjust appearance, lighting, background, or composition.
  • Creative image edits — Change style, mood, objects, clothing, or environment.
  • Product image refinement — Improve product visuals for ecommerce, marketing, and campaigns.
  • Character and portrait edits — Preserve identity while changing details or visual style.
  • Reference-guided editing — Use multiple images to guide the final edited result.

Pro Tips

  • Use clear edit prompts that describe both what should change and what should stay the same.
  • Upload only the images needed for the edit.
  • Use multiple input images when reference context matters.
  • Leave aspect_ratio empty when you want the first input image ratio to guide the output.
  • Keep enable_prompt_expansion enabled for richer interpretation.
  • Disable prompt expansion when you need stricter control over the exact prompt.
  • Use a fixed seed when comparing edit variations.

Related Models

提示:本網站部分功能由第三方 AI 模型提供支援。

Qwen Image 3.0 Edit API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/alibaba/qwen-image-3.0/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 Qwen Image 3.0 Edit below.

HTTP example
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",
    "enable_prompt_expansion": true,
    "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/alibaba/qwen-image-3.0/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=$(printf '%s' "$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' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/alibaba/qwen-image-3.0/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "images": [
                "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
        ],
        "aspect_ratio": "1:1",
        "resolution": "1k",
        "enable_prompt_expansion": true,
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
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",
    "enable_prompt_expansion": True,
    "seed": -1
}

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/alibaba/qwen-image-3.0/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 = task.get("urls", {}).get("get") or 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"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Qwen Image 3.0 Edit API — Frequently asked questions

What is the Qwen Image 3.0 Edit API?

Qwen Image 3.0 Edit is a Alibaba model for image editing, exposed as a REST API on WaveSpeedAI. Qwen Image 3.0 Edit is a high-quality image editing model that transforms existing images with natural-language instructions, delivering advanced instruction understanding, superior visual quality, and up to 2K output for creative and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Qwen Image 3.0 Edit API?

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 production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/alibaba/alibaba-qwen-image-3.0-edit.

How much does Qwen Image 3.0 Edit cost per run?

Qwen Image 3.0 Edit starts at $0.030 per run. 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.

What inputs does Qwen Image 3.0 Edit accept?

Key inputs: `prompt`, `images`, `aspect_ratio`, `resolution`, `seed`, `enable_prompt_expansion`. 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/alibaba/alibaba-qwen-image-3.0-edit.

How do I get started with the Qwen Image 3.0 Edit API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use Qwen Image 3.0 Edit outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Alibaba). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Qwen Image 3.0 Edit API on WaveSpeedAI