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Qwen Image 3.0 Text to Image

alibaba/

Qwen Image 3.0 Text to Image is a high-quality 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

Siap

A young violinist performing alone on a rooftop at twilight, city skyline glowing behind her, wind moving her long coat, dramatic clouds above, emotional cinematic scene, elegant pose, realistic photography, wide-angle composition, soft blue and orange lighting.

$0.03per run·~33 / $1

Selanjutnya:

ContohLihat semua

A young violinist performing alone on a rooftop at twilight, city skyline glowing behind her, wind moving her long coat, dramatic clouds above, emotional cinematic scene, elegant pose, realistic photography, wide-angle composition, soft blue and orange lighting.

A young violinist performing alone on a rooftop at twilight, city skyline glowing behind her, wind moving her long coat, dramatic clouds above, emotional cinematic scene, elegant pose, realistic photography, wide-angle composition, soft blue and orange lighting.

Model Terkait

README

Qwen Image 3.0 Text-to-Image

Qwen Image 3.0 generates high-quality images from text prompts with strong prompt adherence, detailed rendering, and flexible output sizing. It supports simple resolution tiers, common aspect ratios, prompt expansion, and seed control for reproducible image generation workflows.

Why Choose This?

  • High-quality image generation
    Create polished images from natural-language prompts.

  • Strong prompt adherence
    Follow detailed prompts for subjects, composition, style, lighting, and visual details.

  • Flexible output sizing
    Choose 1k or 2k resolution and select the aspect ratio that matches your target layout.

  • Prompt expansion support
    Enable intelligent prompt expansion to enrich the prompt before generation.

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

Parameters

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

How to Use

  1. Write your prompt — Describe the subject, composition, lighting, style, mood, and key visual details.
  2. Choose resolution optional — Use 1k for standard generation or 2k when higher-resolution output is needed.
  3. Choose aspect ratio optional — Select the layout that matches your target format.
  4. Set prompt expansion optional — Keep prompt expansion enabled for richer prompt interpretation, or disable it for stricter prompt control.
  5. Set seed optional — Use a fixed seed when you need reproducible results.
  6. Submit — Generate the image and retrieve the output URL.

Pricing

OutputCost
1k image$0.03
2k image$0.03

Best Use Cases

  • Production image generation — Create high-quality visuals for creative and commercial workflows.
  • Detailed character art and portraits — Generate characters, faces, outfits, poses, and visual details from text prompts.
  • Fashion and beauty visuals — Create editorial-style imagery, product looks, accessories, and styling concepts.
  • Marketing assets — Generate campaign visuals, social graphics, thumbnails, and promotional images.
  • Creative concept development — Explore visual ideas, scenes, styles, and compositions quickly.

Pro Tips

  • Use detailed prompts with subject, composition, lighting, style, mood, and background details.
  • Use 1k for fast iteration and 2k when final image detail matters.
  • Keep enable_prompt_expansion enabled when you want richer prompt interpretation.
  • Disable prompt expansion when you need stricter control over the exact prompt.
  • Use a fixed seed when comparing prompt variations or reproducing similar outputs.
  • Match the aspect ratio to the final use case, such as square, portrait, or landscape layouts.

Related Models

Catatan:Situs web ini menggunakan model AI yang disediakan oleh pihak ketiga.

Qwen Image 3.0 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/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 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/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/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/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 Text To Image API — Frequently asked questions

What is the Qwen Image 3.0 Text To Image API?

Qwen Image 3.0 Text To Image is a Alibaba model for image generation, exposed as a REST API on WaveSpeedAI. Qwen Image 3.0 Text to Image is a high-quality 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 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-text-to-image.

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

Qwen Image 3.0 Text To Image 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 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-text-to-image.

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