Wan 2.7 Image Pro is the higher tier of Alibaba's April 2026 Wan 2.7 Image family and uses the same parameters as the standard version. The difference is resolution: text-to-image goes up to 4K, while editing with reference images stays capped at 2K. Everything else carries over: up to 9 reference images, up to 4 images per request, 7 aspect ratios, an optional negative prompt and seed, and prompts up to 5,000 characters. Region edits, color palettes and 12-image group series are not available in Jantaris yet.
Best for
- 4K key art and print visuals generated from text
- Large backgrounds for video, web and presentations
- Final renders of prompts drafted at 1K with a fixed seed
- Detailed edits where the standard tier falls short
Prompting tips
- 4K works only for plain text-to-image, without
image_urls. - The default resolution is 2k, so set
resolution: 4kexplicitly for the largest output. - Prototype prompts on Wan 2.7 Image, then render finals on Pro.
- Describe small detail you want visible at 4K, such as fabric texture or signage.
FAQ
What does Wan 2.7 Image Pro cost?
It is priced at $0.154 per image. You pay only for delivered images; failed generations are not charged.
Can Wan 2.7 Image Pro edit at 4K?
No. Editing with image_urls is limited to 2K; 4K applies to text-to-image only.
How is Pro different from standard Wan 2.7 Image?
The parameters are identical. Pro adds 4K text-to-image, while the standard tier tops out at 2K in every mode.
How to call Wan 2.7 Image Pro via API
curl https://jantaris.com/v1/generate?wait=60 \
-H "Authorization: Bearer $JANTARIS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "wan-2.7-image-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": "2k"
}
}'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": "wan-2.7-image-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": "2k"
}
}).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": "wan-2.7-image-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": "2k"
}
}),
})).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 | ≤ 5000 chars | |
negative_prompt | string | ||
aspect_ratio | string | 1:1 16:9 9:16 4:3 3:4 3:2 2:3 | 1:1 |
resolution | string | 1k 2k 4k | 2k |
num_images | integer | 1-4 | 1 |
image_urls | array | max 9 | |
seed | integer |
The same schema is available from GET /v1/models/wan-2.7-image-pro.









