Wan Image 2.7 Pro API

The premium tier of Alibaba Tongyi Lab's Wan 2.7 image model (Apr 2026), built for native 4K output and the structural coherence that print and large-format production demand.

Integrate Wan Image 2.7 Pro with a single API call — one key, one unified endpoint, and shared billing across every model on Apiframe.

Get API Key Use in Apiframe Studio View Wan Image 2.7 Pro API Docs

model: "wan-image-2.7-pro"

Wan Image 2.7 Pro native 4K splash art of a fantasy castle on a cliff at sunset in a cinematic 16:9 composition

What's special about Wan Image 2.7 Pro

The high-end tier of the family

Trained on a larger dataset with a larger model size, it delivers more stable composition and stronger semantic understanding than the standard version.

Native 4K resolution

It generates genuine 4096x4096 detail rather than upscaled output, suited to print, large-format, and magazine-cover-quality work.

Keeps the thinking mode

It retains Wan 2.7's reasoning step, planning composition and spatial relationships before generating, which pays off most on complex, multi-subject scenes.

Superior dense text rendering

It handles demanding layouts cleanly, including dense text, formulas, and tables, keeping typography legible at high resolution.

Built for complex scenes

The larger model holds structure better across busy, multi-element compositions where the standard tier can drift.

Production-focused workflow

It pairs naturally with the standard tier, letting you iterate cheaply on Wan 2.7 Image and switch to Pro for final, high-resolution deliverables.

Made with Wan Image 2.7 Pro

A few outputs generated through the Wan Image 2.7 Pro API on Apiframe.

Wan Image 2.7 Pro magazine cover reading 'HORIZON' with a bold masthead, cover lines, and a striking portrait — A magazine cover reading 'HORIZON' with a bold masthead, cover lines, and a striking portrait.

Wan Image 2.7 Pro print-ready product poster with a dense feature list, a comparison table, and clean hierarchy — A print-ready product poster with a dense feature list, a comparison table, and clean hierarchy.

Wan Image 2.7 Pro high-resolution promotional key art with three characters, each with a distinct, consistent look — A high-resolution promotional key art with three characters, each with a distinct, consistent look.

Wan Image 2.7 Pro educational A4 page with labeled diagrams, math formulas, and bilingual captions in crisp text — An educational A4 page with labeled diagrams, math formulas, and bilingual captions, crisp text.

Wan Image 2.7 Pro 4K interior render of a modern living room with accurate lighting and fine material texture — A 4K interior render of a modern living room, accurate lighting, fine material texture.

Overview

Endpoint: POST /v2/images/generate
Model ID: wan-image-2.7-pro
Params key: wanParams
Modality: Image
Provider: Alibaba
Avg. completion: ~20s

Capabilities

Aspect ratios1:1, 2:3, 3:2, 3:4, 4:3, 9:16, 16:9, 21:9

Image inputSupported

Avg. time~20s

Quick start

Send a single POST /v2/images/generate request with your API key to generate with Wan Image 2.7 Pro. The call returns a jobId you can poll or receive via webhook.

curl -X POST https://api.apiframe.ai/v2/images/generate \
  -H "X-API-Key: afk_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{
        "prompt": "a sleek silver sports car on a coastal highway at sunset, hyper-realistic",
        "model": "wan-image-2.7-pro",
        "wanParams": {
            "image": "https://example.com/input.jpg",
            "thinking_mode": false,
            "seed": 1
        }
    }'

import requests

response = requests.post(
    "https://api.apiframe.ai/v2/images/generate",
    headers={
        "X-API-Key": "afk_your_api_key_here",
        "Content-Type": "application/json",
    },
    json={
        "prompt": "a sleek silver sports car on a coastal highway at sunset, hyper-realistic",
        "model": "wan-image-2.7-pro",
        "wanParams": {
            "image": "https://example.com/input.jpg",
            "thinking_mode": False,
            "seed": 1
        }
    },
)
print(response.json())  # { "jobId": "...", "status": "QUEUED" }

const response = await fetch("https://api.apiframe.ai/v2/images/generate", {
  method: "POST",
  headers: {
    "X-API-Key": "afk_your_api_key_here",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "prompt": "a sleek silver sports car on a coastal highway at sunset, hyper-realistic",
    "model": "wan-image-2.7-pro",
    "wanParams": {
      "image": "https://example.com/input.jpg",
      "thinking_mode": false,
      "seed": 1
    }
  }),
});
const { jobId } = await response.json();
console.log(jobId);

Response & job lifecycle

Generation is asynchronous. A successful submission returns 202 Accepted with a jobId. Poll GET /v2/jobs/{id} (or supply a webhook_url) until the status is COMPLETED; the result field then holds the output URL(s).

1. Submission response (202)

{
  "jobId": "b2c3d4e5-f6a7-8901-bcde-f23456789012",
  "status": "QUEUED"
}

2. Poll for the result

curl https://api.apiframe.ai/v2/jobs/JOB_ID \
  -H "X-API-Key: afk_your_api_key_here"

import requests, time

while True:
    job = requests.get(
        "https://api.apiframe.ai/v2/jobs/JOB_ID",
        headers={"X-API-Key": "afk_your_api_key_here"},
    ).json()
    if job["status"] in ("COMPLETED", "FAILED"):
        break
    time.sleep(2)
print(job["result"])

let job;
do {
  await new Promise((r) => setTimeout(r, 2000));
  job = await fetch("https://api.apiframe.ai/v2/jobs/JOB_ID", {
    headers: { "X-API-Key": "afk_your_api_key_here" },
  }).then((r) => r.json());
} while (job.status !== "COMPLETED" && job.status !== "FAILED");
console.log(job.result);

Input schema

Request parameters accepted by the Wan Image 2.7 Pro endpoint. Model-specific options are nested under the params object shown below.

Parameter	Type	Required	Default	Allowed / range	Description
prompt	string	required	—	—	Text description of what to generate.
model	string	required	"wan-image-2.7-pro"	"wan-image-2.7-pro"	The model identifier for this endpoint.
wanParams.image	string (URL)	optional	—	—	Reference image (URL)
wanParams.thinking_mode	boolean	optional	false	—	Slower, more deliberate generation.
wanParams.seed	number	optional	—	step 1	Reuse a number to reproduce the same result.

Frequently Asked Questions

Common questions about the Wan Image 2.7 Pro API.

What is Wan Image 2.7 Pro?

The premium tier of Alibaba's Wan 2.7 image model, built for production-grade, high-resolution output.

How is it different from standard Wan Image 2.7?

Pro uses a larger model and dataset for native 4K, more stable composition, and stronger semantic understanding, while the standard tier covers most work at up to 2K for less cost.

What resolution does it produce?

Native 4K, at 4096x4096, with 4K aspect ratios like cinematic 16:9.

What is it best at?

Final marketing materials, print and large-format assets, key art, and complex, dense-text layouts.

Does it still have thinking mode?

Yes. It keeps Wan 2.7's reasoning step for composition and spatial coherence.

Where can you access it?

Through Apiframe, as well as Alibaba Cloud Model Studio and major hosting partners.

Still have questions?

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