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Qwen Image Text to Image

wavespeed-ai /

Qwen-Image is a 20B MMDiT next-gen text-to-image model that generates images from text prompts. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-image
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Bookstore window display. A sign displays "New Arrivals This Week". Below, a shelf tag with the text "Best-Selling Novels Here". To the side, a colorful poster advertises "Author Meet And Greet on Saturday" with a central portrait of the author. There are four books on the bookshelf, namely "The light between worlds" "When stars are scattered" "The slient patient" "The night circus"

$0.02cho mỗi lần chạy·~50 / $1

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A beautiful Chinese woman wearing a "WaveSpeedAI" T-shirt is smiling at the camera with a black marker. Behind her, a glass panel reads in handwriting, "Meet Qwen Image - a powerful image foundation model capable of complex text rendering and precise image editing."

A beautiful Chinese woman wearing a "WaveSpeedAI" T-shirt is smiling at the camera with a black marker. Behind her, a glass panel reads in handwriting, "Meet Qwen Image - a powerful image foundation model capable of complex text rendering and precise image editing."

Bookstore window display. A sign displays "New Arrivals This Week". Below, a shelf tag with the text "Best-Selling Novels Here". To the side, a colorful poster advertises "Author Meet And Greet on Saturday" with a central portrait of the author. There are four books on the bookshelf, namely "The light between worlds" "When stars are scattered" "The slient patient" "The night circus"

Bookstore window display. A sign displays "New Arrivals This Week". Below, a shelf tag with the text "Best-Selling Novels Here". To the side, a colorful poster advertises "Author Meet And Greet on Saturday" with a central portrait of the author. There are four books on the bookshelf, namely "The light between worlds" "When stars are scattered" "The slient patient" "The night circus"

A man in a suit is standing in front of the window, looking at the bright moon outside the window. The man is holding a yellowed paper with handwritten words on it: "A lantern moon climbs through the silver night, Unfurling quiet dreams across the sky, Each star a whispered promise wrapped in light, That dawn will bloom, though darkness wanders by." There is a cute cat on the windowsill.

A man in a suit is standing in front of the window, looking at the bright moon outside the window. The man is holding a yellowed paper with handwritten words on it: "A lantern moon climbs through the silver night, Unfurling quiet dreams across the sky, Each star a whispered promise wrapped in light, That dawn will bloom, though darkness wanders by." There is a cute cat on the windowsill.

A Victorian noble lady with an elegant updo and a gentle gaze, wearing a deep red velvet dress, sitting in an ornate library. Warm candlelight illuminates her face and the surrounding bookshelves. In the style of John Singer Sargent, classic oil painting, expressive brushstrokes, masterpiece, rich textures.

A Victorian noble lady with an elegant updo and a gentle gaze, wearing a deep red velvet dress, sitting in an ornate library. Warm candlelight illuminates her face and the surrounding bookshelves. In the style of John Singer Sargent, classic oil painting, expressive brushstrokes, masterpiece, rich textures.

A movie poster. The first row is the movie title, which reads "Imagination Unleashed". The second row is the movie subtitle, which reads "Enter a world beyond your imagination". The third row reads "Cast: Qwen-Image". The fourth row reads "Director: The Collective Imagination of Humanity". The central visual features a sleek, futuristic computer from which radiant colors, whimsical creatures, and dynamic, swirling patterns explosively emerge, filling the composition with energy, motion, and surreal creativity. The background transitions from dark, cosmic tones into a luminous, dreamlike expanse, evoking a digital fantasy realm. At the bottom edge, the text "Launching in the Cloud, August 2025" appears in bold, modern sans-serif font with a glowing, slightly transparent effect, evoking a high-tech, cinematic aesthetic. The overall style blends sci-fi surrealism with graphic design flair—sharp contrasts, vivid color grading, and layered visual depth—reminiscent of visionary concept art and digital matte painting, 32K resolution, ultra-detailed.

A movie poster. The first row is the movie title, which reads "Imagination Unleashed". The second row is the movie subtitle, which reads "Enter a world beyond your imagination". The third row reads "Cast: Qwen-Image". The fourth row reads "Director: The Collective Imagination of Humanity". The central visual features a sleek, futuristic computer from which radiant colors, whimsical creatures, and dynamic, swirling patterns explosively emerge, filling the composition with energy, motion, and surreal creativity. The background transitions from dark, cosmic tones into a luminous, dreamlike expanse, evoking a digital fantasy realm. At the bottom edge, the text "Launching in the Cloud, August 2025" appears in bold, modern sans-serif font with a glowing, slightly transparent effect, evoking a high-tech, cinematic aesthetic. The overall style blends sci-fi surrealism with graphic design flair—sharp contrasts, vivid color grading, and layered visual depth—reminiscent of visionary concept art and digital matte painting, 32K resolution, ultra-detailed.

Real style, three different looking puppies have a camera in front of them and the puppies look at it curiously. Elevated view

Real style, three different looking puppies have a camera in front of them and the puppies look at it curiously. Elevated view

A female athlete with defined muscles and a tight ponytail, preparing for a run. She is wearing a black sports top and leggings, her gaze focused and determined. The background is a city running track at dawn with a light mist on the ground. Dynamic action shot, strong rim lighting outlining her silhouette, powerful and energetic, high contrast.

A female athlete with defined muscles and a tight ponytail, preparing for a run. She is wearing a black sports top and leggings, her gaze focused and determined. The background is a city running track at dawn with a light mist on the ground. Dynamic action shot, strong rim lighting outlining her silhouette, powerful and energetic, high contrast.

A girl with little freckles and messy red hair sitting on a rooftop during sunset, denim jacket slightly worn, holding a Polaroid camera, city skyline glowing in soft hues behind her

A girl with little freckles and messy red hair sitting on a rooftop during sunset, denim jacket slightly worn, holding a Polaroid camera, city skyline glowing in soft hues behind her

An elven queen with long silver hair and glowing blue eyes, wearing a magnificent white gown adorned with jewels. She stands in an ancient, mystical forest surrounded by luminous plants and mist. Moonlight filtering through the canopy, creating magical light and shadows. Fantasy art, epic, intricate details, masterpiece, digital painting.

An elven queen with long silver hair and glowing blue eyes, wearing a magnificent white gown adorned with jewels. She stands in an ancient, mystical forest surrounded by luminous plants and mist. Moonlight filtering through the canopy, creating magical light and shadows. Fantasy art, epic, intricate details, masterpiece, digital painting.

Mô hình liên quan

README

Qwen-Image (Text-to-Image)

Qwen-Image is a 20B MMDiT-based text-to-image generation model, especially strong at native text rendering in both English and Chinese. It is a powerful creative tool for posters, comics, and visual storytelling, while also excelling at general image generation from photorealism to anime.

Why it looks great

  • SOTA text rendering: Rivals GPT-4o in English and best-in-class for Chinese.
  • In-pixel text generation: Text is fully integrated into the image (no overlays).
  • Bilingual typography: Handles diverse fonts, styles, and complex layouts.
  • General image capability: Excels across styles—photorealistic, anime, impressionist, minimalist.

Limits and Performance

  • Max resolution per job: up to 1536 × 1536 pixels
  • Custom size: manually set width & height
  • Output formats: JPEG / PNG / WEBP
  • Processing speed: ~5–8 seconds per image (depends on size & queue)
  • Input prompt: supports detailed, multi-line descriptions

Price

Only $0.02 per image!!!

How to Use

  1. Write a prompt describing the image (can include embedded text).
  2. Adjust size (width & height, up to 1536×1536).
  3. Set a seed for reproducibility.
  4. Choose output_format.
  5. Run the job and download the generated image.

Pro tips for best quality

  • For poster design, explicitly describe font style, placement, and mood.
  • For bilingual text, specify both Chinese and English in the prompt.
  • Use consistent seeds to regenerate similar layouts with slight variations.
  • Keep height:width ratio balanced for best typography results.
Lưu ý:Trang web này sử dụng các mô hình AI do bên thứ ba cung cấp.

Qwen Image Text To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/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 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",
    "size": "1024*1024",
    "seed": -1,
    "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/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/wavespeed-ai/qwen-image/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "size": "1024*1024",
        "seed": -1,
        "output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "size": "1024*1024",
    "seed": -1,
    "output_format": "jpeg"
}

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/wavespeed-ai/qwen-image/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 Text To Image API — Frequently asked questions

What is the Qwen Image Text To Image API?

Qwen Image Text To Image is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. Qwen-Image is a 20B MMDiT next-gen text-to-image model that generates images from text prompts. 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 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/wavespeed-ai/qwen-image-text-to-image.

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

Qwen Image Text To Image starts at $0.020 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 Text To Image accept?

Key inputs: `prompt`, `size`, `seed`, `enable_base64_output`, `enable_sync_mode`, `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/wavespeed-ai/qwen-image-text-to-image.

How long does Qwen Image Text To Image take to generate?

Median end-to-end generation time on WaveSpeedAI is around 18 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Qwen Image Text To Image outputs commercially?

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

Qwen Image Text to Image | High-Quality Text-to-Image API | WaveSpeedAI