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Qwen Image 3.0 Pro Text to Image

alibaba/

Qwen Image 3.0 Pro Text-to-Image is a professional-grade image generation model that creates high-quality images from text prompts, with advanced prompt understanding, strong visual quality, and up to 2K output for creative and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-image
Input

Inattivo

A young woman carrying a candle explores an abandoned palace at night. She enters a long hall of mirrors and notices that one reflection is moving differently from her. The camera begins behind her shoulder, glides smoothly between the mirrors, and repeatedly changes focus between her real body and the false reflection. The reflection suddenly turns and runs deeper into the mirrored corridor. She follows it until every mirror reveals a different version of her life. Gothic mystery, elegant Steadicam movement, candlelit shadows, slow-building tension, highly detailed production design.

$0.04per esecuzione·~25 / $1

Successivo:

EsempiVedi tutto

A young woman carrying a candle explores an abandoned palace at night. She enters a long hall of mirrors and notices that one reflection is moving differently from her. The camera begins behind her shoulder, glides smoothly between the mirrors, and repeatedly changes focus between her real body and the false reflection. The reflection suddenly turns and runs deeper into the mirrored corridor. She follows it until every mirror reveals a different version of her life. Gothic mystery, elegant Steadicam movement, candlelit shadows, slow-building tension, highly detailed production design.

A young woman carrying a candle explores an abandoned palace at night. She enters a long hall of mirrors and notices that one reflection is moving differently from her. The camera begins behind her shoulder, glides smoothly between the mirrors, and repeatedly changes focus between her real body and the false reflection. The reflection suddenly turns and runs deeper into the mirrored corridor. She follows it until every mirror reveals a different version of her life. Gothic mystery, elegant Steadicam movement, candlelit shadows, slow-building tension, highly detailed production design.

Modelli correlati

README

Qwen Image 3.0 Pro Text-to-Image

Qwen Image 3.0 Pro is a high-quality text-to-image model built for production-grade visual creation, with strong detail rendering, prompt adherence, and flexible output resolution.

Parameters

ParameterRequiredDescription
promptYesText description of the desired image.
resolutionNoOutput resolution tier: 1k or 2k. Default: 1k.
aspect_ratioNoOutput aspect ratio. Default: 1:1.
enable_prompt_expansionNoEnable intelligent prompt expansion. Default: true.
seedNoRandom seed for reproducibility. Use -1 for a random seed.

How to Use

  1. Write a detailed prompt.
  2. Optionally set resolution and aspect_ratio.
  3. Submit and retrieve the generated image.

Pricing

OutputCost
1k image$0.04
2k image$0.075

Best Use Cases

  • Production image generation
  • Detailed character art and portraits
  • Fashion, beauty, and commercial visuals
  • Marketing assets and creative concept development
Nota:Questo sito web utilizza modelli di intelligenza artificiale forniti da terze parti.

Qwen Image 3.0 Pro Text To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/alibaba/qwen-image-3.0-pro/text-to-image 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 Pro Text To Image 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",
    "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-pro/text-to-image" \
  -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-pro/text-to-image";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "1:1",
        "resolution": "1k",
        "enable_prompt_expansion": true,
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "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-pro/text-to-image", 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 Pro Text To Image API — Frequently asked questions

What is the Qwen Image 3.0 Pro Text To Image API?

Qwen Image 3.0 Pro Text To Image is a Alibaba model for image generation, exposed as a REST API on WaveSpeedAI. Qwen Image 3.0 Pro Text-to-Image is a professional-grade image generation model that creates high-quality images from text prompts, with advanced prompt understanding, strong 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 Pro Text To Image 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-pro-text-to-image.

How much does Qwen Image 3.0 Pro Text To Image cost per run?

Qwen Image 3.0 Pro Text To Image starts at $0.040 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 Pro Text To Image accept?

Key inputs: `prompt`, `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-pro-text-to-image.

How do I get started with the Qwen Image 3.0 Pro Text To Image 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 Pro Text To Image 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 Pro Text to Image API on WaveSpeedAI