Qwen Image 3.0 Pro is the pro tier of Alibaba's July 2026 Qwen Image 3.0, tuned for dense text and layout work: menus, newspapers, storyboards and exam papers. It shares the standard tier's parameters, with prompts of about 4.5k tokens, 1-3 reference images, 1-4 images per request and a negative prompt. Output is 1K or 2K, and 2K is billed at twice the 1K rate. Choose it when a page is packed with small type and every line has to read correctly.
Best for
- Restaurant menus with dishes, descriptions and prices
- Worksheets, quizzes and exam-style pages
- Newspaper front pages and editorial mockups
- Storyboards with dialogue under each panel
Prompting tips
- Supply the full text of every section in the prompt; the model can only render words you give it.
- Draft at 1K and switch to 2K for pages with many small lines.
- Use
negative_promptfor things to avoid, such as "watermark, blurry text". - Attach 1-3 references of an existing layout to match its grid.
FAQ
How much does Qwen Image 3.0 Pro cost?
It costs from $0.0857 per image, and 2K images cost twice as much as 1K. Failed generations are not charged.
How is Pro different from Qwen Image 3.0?
The inputs and limits are the same; Pro is tuned for denser text and layout. Qwen Image 3.0 charges one price for both 1K and 2K.
How many images can I get per request?
Between 1 and 4, set with num_images.
How to call Qwen Image 3.0 Pro via API
curl https://jantaris.com/v1/generate?wait=60 \
-H "Authorization: Bearer $JANTARIS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen-image-3.0-pro",
"input": {
"prompt": "Product photo of a matte black ceramic coffee cup on a travertine table, soft window light, 50mm",
"aspect_ratio": "1:1",
"resolution": "1K"
}
}'import os, time, requests
API = "https://jantaris.com/v1"
H = {"Authorization": f"Bearer {os.environ['JANTARIS_API_KEY']}"}
task = requests.post(f"{API}/generate", headers=H, json={
"model": "qwen-image-3.0-pro",
"input": {
"prompt": "Product photo of a matte black ceramic coffee cup on a travertine table, soft window light, 50mm",
"aspect_ratio": "1:1",
"resolution": "1K"
}
}).json()
while task["status"] in ("queued", "running"):
time.sleep(3)
task = requests.get(f"{API}/tasks/{task['id']}", headers=H).json()
print(task["status"], task["cost"], [o["url"] for o in task["output"]])const API = "https://jantaris.com/v1";
const headers = { Authorization: `Bearer ${process.env.JANTARIS_API_KEY}`, "Content-Type": "application/json" };
let task = await (await fetch(`${API}/generate`, {
method: "POST",
headers,
body: JSON.stringify({
"model": "qwen-image-3.0-pro",
"input": {
"prompt": "Product photo of a matte black ceramic coffee cup on a travertine table, soft window light, 50mm",
"aspect_ratio": "1:1",
"resolution": "1K"
}
}),
})).json();
while (task.status === "queued" || task.status === "running") {
await new Promise((r) => setTimeout(r, 3000));
task = await (await fetch(`${API}/tasks/${task.id}`, { headers })).json();
}
console.log(task.status, task.cost, task.output.map((o) => o.url));
Parameters
| Parameter | Type | Allowed | Default |
|---|---|---|---|
prompt * | string | ||
negative_prompt | string | ||
aspect_ratio | string | 1:1 4:3 3:4 16:9 9:16 3:2 2:3 | 1:1 |
resolution | string | 1K 2K | 1K |
num_images | integer | 1-4 | 1 |
image_urls | array | max 3 |
The same schema is available from GET /v1/models/qwen-image-3.0-pro.









