alibaba/wan-2.7/image-edit-pro

alibaba/wan-2.7/image-edit-pro

WAN 2.7 Image Edit Pro performs prompt-driven image editing with multi-image reference support and up to 2K output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Examples

alibaba/wan-2.7/image-edit-pro Examples 1

Parameters

NameTypeDefaultConstraintsDescription
prompt *Prompttextarea—≤ 5000 charsThe positive prompt for the generation.
images *Imagesimage_upload—image/* · 1–9 itemsList of URLs of input images for editing (1-9 images).
sizeSizetext—≤ 500 charsThe size of the generated image in pixels (width*height). Range: 512-4096 per dimension. Total pixels must be between 768*768 and 2048*2048. Aspect ratio must be between 1:8 and 8:1.

Output fields

FieldTypeDescription
imagesarray<string>Generated image URL(s).

API

Call this model through one unified REST API. Get a key on the API Keys page.

cURL
# 1) Submit — returns { "task_uuid": "..." }
curl -X POST "https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.7/image-edit-pro" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "input": {
    "prompt": "Preserve the subject identity and composition, replace the background with a premium studio setting, and enhance fine details and lighting realism.",
    "images": [
      "https://assets-public.namifusion.com/marketplace/images/2026-06-12/638e1ee18ac7.jpeg"
    ]
  }
}'

# 2) Poll until status is "completed", then read the output URLs
curl "https://www.namifusion.com/api/v1/marketplace/run/tasks/TASK_UUID" \
  -H "Authorization: Bearer YOUR_API_KEY"
Python
import time, requests

API_KEY = "YOUR_API_KEY"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

# 1) Submit
resp = requests.post(
    "https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.7/image-edit-pro",
    headers=HEADERS,
    json={
        "input": {
            "prompt": "Preserve the subject identity and composition, replace the background with a premium studio setting, and enhance fine details and lighting realism.",
            "images": [
                "https://assets-public.namifusion.com/marketplace/images/2026-06-12/638e1ee18ac7.jpeg"
            ]
        }
    },
)
resp.raise_for_status()  # 401/402/429/5xx stop here instead of polling a bad task
task = resp.json()

# 2) Poll until a terminal state (completed / failed / cancelled).
#    This model is allowed up to 300s server-side.
deadline = time.time() + 360
while task.get("status") not in ("completed", "failed", "cancelled"):
    if time.time() > deadline:
        raise TimeoutError(f"still {task.get('status')} — keep the task_uuid and poll later")
    time.sleep(3)
    poll = requests.get(f"https://www.namifusion.com/api/v1/marketplace/run/tasks/{task['task_uuid']}", headers=HEADERS)
    poll.raise_for_status()
    task = poll.json()

print(task["status"], task.get("output"))
JavaScript
const API_KEY = "YOUR_API_KEY";
const HEADERS = { Authorization: `Bearer ${API_KEY}` };

// 1) Submit
const resp = await fetch("https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.7/image-edit-pro", {
  method: "POST",
  headers: { ...HEADERS, "Content-Type": "application/json" },
  body: JSON.stringify({
    "input": {
      "prompt": "Preserve the subject identity and composition, replace the background with a premium studio setting, and enhance fine details and lighting realism.",
      "images": [
        "https://assets-public.namifusion.com/marketplace/images/2026-06-12/638e1ee18ac7.jpeg"
      ]
    }
  }),
});
if (!resp.ok) throw new Error(`submit failed: ${resp.status} ${await resp.text()}`);
let task = await resp.json();

// 2) Poll until a terminal state (completed / failed / cancelled).
//    This model is allowed up to 300s server-side.
const deadline = Date.now() + 360 * 1000;
while (!["completed", "failed", "cancelled"].includes(task.status)) {
  if (Date.now() > deadline) throw new Error(`still ${task.status} — keep the task_uuid and poll later`);
  await new Promise((r) => setTimeout(r, 3000));
  const poll = await fetch(`https://www.namifusion.com/api/v1/marketplace/run/tasks/${task.task_uuid}`, { headers: HEADERS });
  if (!poll.ok) throw new Error(`poll failed: ${poll.status}`);
  task = await poll.json();
}

console.log(task.status, task.output);

Documentation

alibaba/wan-2.7/image-edit-pro

Professional prompt-driven image editing with multi-image references and up to 2K output.

alibaba/wan-2.7/image-edit-pro is a production-oriented image editing model designed for high-fidelity, controllable edits. It supports natural-language editing instructions, multiple reference images, and high-resolution output while preserving subject identity, composition, and overall scene structure. With no cold start behavior and affordable per-run pricing, it is well suited for reliable creative workflows at scale.

🚀 Key Features

  • Production-grade quality: Optimized for higher-fidelity results in workflows where detail retention and visual consistency matter.
  • Multi-image reference support: Use 1–9 input images for subject, style, background, or fusion guidance in more complex edits.
  • Up to 2K output: Supports effective output sizes up to approximately 2048×2048, suitable for high-DPI assets and print-ready visuals.
  • Natural-language editing: Describe what to change and what to preserve in plain language for intuitive editing control.
  • Composition preservation: Designed to maintain subject identity, pose, and layout while applying localized or stylistic changes.
  • No cold start: Ready for responsive production usage without cold-start delays.

🛠️ Technical Specifications

ItemDetails
Model architectureWAN 2.7 Image Edit Pro(professional prompt-driven image editing model)
Task typeImage editing
Input formatPrompt + reference images(1–9 images)
Output formatEdited image
Input image count1–9
Resolution512–4096 pixels per dimension; total pixels must be between 768×768 and 2048×2048
Aspect Ratio1:8 to 8:1
Default output sizeIf size is not specified, output typically follows the original image dimensions
Quality tierPro / high-fidelity output
LatencyNo fixed public benchmark; higher resolutions generally take longer
Runtime behaviorNo cold start

Sample Prompts

  • “Change the jacket to black leather, keep the face, pose, and background unchanged.”
  • “Color-match the skirt in the first image to the bird in the second image, while keeping the clothing style and model unchanged.”
  • “Replace the product background with a minimal studio setting, preserving the product shape, label text, and lighting direction.”

💰 Pricing

ItemPrice
Base price$0.075 / run

💡 Best Use Cases

  • E-commerce and product photography: Retouch products, swap backgrounds, and generate high-resolution commercial assets.
  • Fashion and apparel visualization: Modify clothing color, material, or style while preserving pose and identity.
  • Marketing and brand creative: Produce polished campaign visuals for ads, landing pages, and social media.
  • Print and high-DPI design: Create edited assets suitable for posters, packaging, and large-format display workflows.

🔗 Related Models

  • Wan 2.7 Image Edit: Lower-cost standard version for everyday editing and faster iteration.
  • Wan 2.6 Image Edit: Previous-generation model with a similar prompt-driven workflow.
  • Qwen Image Edit: General-purpose image editing model for everyday creative and product use cases.
  • Google Nano Banana Pro Edit: High-fidelity editing model with strong composition preservation and text handling.

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