Wan Image 2.7 API

Alibaba Tongyi Lab's unified image generation and editing model (Apr 2026), notable for a "thinking mode" that plans composition before generating, plus strong text rendering and multi-reference control.

Integrate Wan Image 2.7 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 API Docs

model: "wan-image-2.7"

Wan Image 2.7 clean e-commerce product shot of a sneaker on a white background with sharp detail

What's special about Wan Image 2.7

A built-in thinking mode

Before generating, it reasons about composition, spatial relationships, and prompt logic, which produces noticeably better results on complex, multi-element scenes.

Unified generation and editing

One model handles text-to-image, multi-reference composition with up to 9 reference images, and region-level editing in a single workflow.

Image Set Mode

It generates a coherent batch of related images from one prompt, ideal for the same character across scenes, product angles, or storyboard sequences.

Dense, multilingual text rendering

It renders thousands of characters across many languages, including readable formulas, tables, signs, and labels, which suits posters and educational visuals.

Precise brand and face control

It locks outputs to exact colors with hex palette control and generates distinct, consistent characters rather than recycling a single "AI face."

Mask-free natural-language editing

You describe a change, like swapping a background, and it preserves everything else, with affordable standard-tier generation up to 2K.

Made with Wan Image 2.7

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

Wan Image 2.7 A4 tech conference poster with a structured layout, readable headings, and a schedule table — An A4 tech conference poster with a structured layout, readable headings, and a schedule table.

Wan Image 2.7 coherent set of four images of the same orange cat across spring, summer, autumn, and winter — A coherent set of four images of the same orange cat across spring, summer, autumn, and winter.

Wan Image 2.7 educational diagram explaining the rock cycle with labeled stages and readable captions — An educational diagram explaining the rock cycle with labeled stages and readable captions.

A brand banner using these exact hex colors, with the headline 'NEW ARRIVALS' in bold type.

Wan Image 2.7 portrait with its background changed to a beach sunset while keeping the face, pose, and clothing unchanged — Change the background of this portrait to a beach sunset, keeping the face, pose, and clothing unchanged.

Overview

Endpoint: POST /v2/images/generate
Model ID: wan-image-2.7
Params key: wanParams
Modality: Image
Provider: Alibaba
Avg. completion: ~15s

Capabilities

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

Image inputSupported

Avg. time~15s

Quick start

Send a single POST /v2/images/generate request with your API key to generate with Wan Image 2.7. 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",
        "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",
        "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",
    "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 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"	"wan-image-2.7"	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 API.

What is Wan Image 2.7?

Alibaba Tongyi Lab's unified image generation and editing model, released in April 2026.

What is "thinking mode"?

A reasoning step where the model analyzes composition and spatial logic before generating, improving adherence on complex prompts.

What is it best at?

Instruction following and dense, readable text, across e-commerce, posters, diagrams, and marketing assets.

How is it different from Wan 2.7 Image Pro?

Pro uses a larger model and dataset for native 4K and stronger composition on complex, dense scenes, while the standard tier covers most work at up to 2K for less cost.

Can it edit images and keep characters consistent?

Yes. It supports mask-free editing, up to 9 reference images, and image sets for consistent characters.

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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