# Wan 2.7 Image Generation Pro

> Wan 2.7 Pro generates 4K images with chain-of-thought reasoning, multilingual text rendering, and multi-reference consistency control.


## Overview

- **Endpoint**: `https://api.segmind.com/v1/wan2.7-image-pro`
- **Model ID**: `wan2.7-image-pro`
- **Category**: Text-to-Image Generation
- **Type**: Synchronous (Direct response)
- **Average Latency**: ~38.4s (30-day average)

- **Average Cost**: $0.1073 per run (observed across past runs, not a price — see Pricing)
- **Provider**: DASHSCOPE



## Pricing

- **Cost**: $0.107 per generation

## API Information

This model uses a **synchronous response pattern**:
1. Make a POST request with your parameters
2. Receive the output directly in the response (binary for images/videos/audio, JSON for text)
3. No polling required - response is immediate


### Input Schema

The API accepts the following input parameters:

- **`prompt`** (`string`, _required_):
  Prompt
  Describe image in detail: subject, lighting, style, and mood.
  - Default: `"A breathtaking aerial view of a futuristic city at golden hour, towering glass skyscrapers with lush vertical gardens, flying vehicles, cinematic lighting, ultra-detailed, photorealistic"`

- **`image`** (`File (URL)`, _optional_):
  Image
  Reference image for editing or style transfer guidance.

- **`negative_prompt`** (`string`, _optional_):
  Negative Prompt
  Elements to exclude from output. Removes unwanted artifacts.
  - Default: `"blurry, low quality, distorted, watermark, text"`

- **`size`** (`string`, _optional_):
  Size
  Output resolution. 1K for previews, 2K web, 4K for print.
  - Default: `"2K"`
  - Options: "1K" (1K), "2K" (2K), "4K" (4K)

- **`seed`** (`integer`, _optional_):
  Seed
  Fixed seed for reproducible output. Range: 0-2147483647.
  - Default: `42`
  - Range: 0 to 2147483647

- **`watermark`** (`boolean`, _optional_):
  Watermark
  Overlays AI watermark. Disable for clean professional deliverables.
  - Default: `false`


**Required Parameters Example**:

```json
{
  "prompt": "A breathtaking aerial view of a futuristic city at golden hour, towering glass skyscrapers with lush vertical gardens, flying vehicles, cinematic lighting, ultra-detailed, photorealistic"
}
```


**Full Example**:

```json
{
  "prompt": "A breathtaking aerial view of a futuristic city at golden hour, towering glass skyscrapers with lush vertical gardens, flying vehicles, cinematic lighting, ultra-detailed, photorealistic",
  "image": "https://example.com/image.jpg",
  "negative_prompt": "blurry, low quality, distorted, watermark, text",
  "size": "2K",
  "seed": 42,
  "watermark": false
}
```


### Output Schema

The API returns a synchronous response based on the model type:

**For Image/Video/Audio Models**:
- Response contains binary data (image/png, video/mp4, audio/mp3)
- Content-Type header indicates the media type
- Save the response body directly to a file

**For Text Models**:
- Response is JSON with the generated text
- Structure varies by model

**HTTP Response Codes**:
- **200 - OK**: Request successful, output in response body
- **400 - Bad Request**: Invalid parameters
- **401 - Unauthorized**: Invalid or missing API key
- **404 - Not Found**: Model not found
- **406 - Not Acceptable**: Insufficient credits
- **429 - Too Many Requests**: Rate limit exceeded
- **500 - Server Error**: Internal server error



## About

### Wan 2.7 Image Generation Pro — Text-to-Image AI Model

#### What is Wan 2.7 Image Generation Pro?

Wan 2.7 Image Generation Pro is Alibaba's flagship professional-grade image generation model, built for developers and creators who demand high-fidelity, production-ready visuals. Unlike conventional diffusion models, Wan 2.7 Pro employs a chain-of-thought reasoning mechanism — the model literally thinks before it draws — analyzing composition logic, lighting semantics, and layout relationships before committing to pixels. The result is exceptional detail accuracy, reduced artifacts, and dramatically improved adherence to complex prompts. The Pro variant extends these capabilities with 4K resolution output (up to 4096×4096), making it the right choice for print-grade and high-DPI use cases.

#### Key Features

- **4K Resolution Support** — Output up to 4096×4096 pixels, delivering print-grade quality for professional workflows.
- **Built-in Reasoning Mode** — Chain-of-thought composition planning produces superior spatial logic and fewer hallucinations.
- **12-Language Text Rendering** — Render clear multilingual text, academic formulas, and tables directly within generated images — supporting up to 3,000 tokens of text input.
- **Multi-Reference Consistency** — Supply up to 9 reference images for precise character consistency, background alignment, and style locking across entire image series.
- **Image Editing** — Pass an input image alongside a prompt to perform instruction-based edits with pixel-level accuracy.
- **Deep Personalization** — Fine-tune facial features, enter exact brand color codes, and replicate complex artistic styles.

#### Best Use Cases

Wan 2.7 Image Pro is purpose-built for workflows that require both precision and scale. Brand and marketing teams use it to generate visually consistent assets at 4K quality, matching exact brand color palettes. E-commerce operators leverage multi-reference input to produce consistent product imagery across large catalogs. Character designers and game developers benefit from up to 9 reference images for maintaining facial and costume consistency across scenes. Academic and technical publishers tap the model's multilingual text rendering to generate diagrams, annotated visuals, and poster-grade scientific figures. Film and content studios use the image editing capabilities for storyboarding and style-transfer iterations.

#### Prompt Tips and Output Quality

For best results, write prompts that specify subject, setting, lighting, mood, and artistic style explicitly. Wan 2.7 Pro's reasoning mode handles ambiguity better than most models, but highly specific prompts yield the tightest composition. Use the `negative_prompt` to suppress recurring artifacts or unwanted stylistic bleed. At 4K size, expect rich surface detail — ideal for cropping into multiple derivative assets. Set a `seed` value to lock a composition and iterate with minor prompt variations for controlled creative exploration.

## Usage Guide

### How to Use Wan 2.7 Image Generation Pro

Wan 2.7 Image Generation Pro combines chain-of-thought reasoning with 4K output to deliver professional-grade image generation and editing. Here is how to get the most out of it.

#### Writing Effective Prompts

Wan 2.7 Pro excels with specific, structured prompts. Include subject (what or who is in the image), setting (location, environment, time of day), lighting (golden hour, studio lighting, overcast, neon-lit), style (photorealistic, oil painting, isometric 3D, editorial photography), and mood (dramatic, serene, tense, minimalist).

Example for brand work: "A sleek matte black coffee mug on a white marble surface, studio lighting, minimalist product photography, no shadows"

#### Choosing the Right Size

Use 1K for fast previews and rapid iteration — good for prompt testing. Use 2K (default) for balanced quality for web assets, social media, and app UI. Use 4K for maximum detail for print, large-format banners, or high-DPI displays, especially when the output will be cropped into multiple derivative assets.

#### Image Editing Mode

Pass a reference image via the `image` parameter and describe your edit in the prompt. The model performs instruction-based editing while preserving the overall composition. Great for product retouching, background swaps, and style transfer.

#### Using Negative Prompts

Suppress common artifacts by adding terms like "blurry, distorted, extra limbs, watermark, overexposed". For character work, add "multiple faces, duplicate subjects" to keep outputs clean.

#### Reproducibility with Seeds

Set a fixed `seed` value to reproduce a specific output exactly. Use the same seed with a slightly modified prompt to create controlled variations — useful for generating A/B options for client review without losing a strong composition.

#### Text Inside Images

For outputs containing readable text, posters, or diagrams: describe the exact text in your prompt and specify language and layout. The model supports 12 languages and handles formulas, tables, and multilingual labels natively.

## FAQ

### What makes Wan 2.7 Pro different from standard Wan 2.7?

The Pro variant adds 4K resolution output, more stable composition, and sharper prompt understanding compared to the standard model.

### Does Wan 2.7 Pro support image editing, not just generation?

Yes — pass an image via the `image` parameter alongside a prompt to perform instruction-based edits on existing images.

### Can I render text inside generated images?

Yes. The model supports 12 languages and up to 3,000 tokens of text input, including academic formulas and complex tables.

### How many reference images can I use?

Up to 9 reference images can be provided for consistency control across character appearance, scene style, and background.

### What resolution should I choose?

Use 1K for rapid prototyping, 2K for web-ready outputs, and 4K for print, large-format displays, or high-DPI deliverables.

### Is the reasoning mode always active?

Yes, chain-of-thought composition reasoning is built into the model inference pipeline and activates automatically on every generation.

## Usage Examples

### cURL

```bash
curl -X POST "https://api.segmind.com/v1/wan2.7-image-pro" \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "prompt": "A breathtaking aerial view of a futuristic city at golden hour, towering glass skyscrapers with lush vertical gardens, flying vehicles, cinematic lighting, ultra-detailed, photorealistic",
  "image": "https://example.com/image.jpg",
  "negative_prompt": "blurry, low quality, distorted, watermark, text",
  "size": "2K",
  "seed": 42,
  "watermark": false
}'
```

### Python

```python
import requests
import json

api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/wan2.7-image-pro"

data = {
  "prompt": "A breathtaking aerial view of a futuristic city at golden hour, towering glass skyscrapers with lush vertical gardens, flying vehicles, cinematic lighting, ultra-detailed, photorealistic",
  "image": "https://example.com/image.jpg",
  "negative_prompt": "blurry, low quality, distorted, watermark, text",
  "size": "2K",
  "seed": 42,
  "watermark": false
}

response = requests.post(
    url,
    json=data,
    headers={
        'x-api-key': api_key,
        'Content-Type': 'application/json'
    }
)

if response.status_code == 200:
    # For image/video/audio models, response.content contains the binary data
    with open('output.png', 'wb') as f:
        f.write(response.content)
    print('Generation complete, saved to output.png')
else:
    print(f"Error: {response.status_code}")
    print(response.text)
```

### JavaScript

```javascript
const apiKey = 'YOUR_API_KEY';
const url = 'https://api.segmind.com/v1/wan2.7-image-pro';

const data = {
  "prompt": "A breathtaking aerial view of a futuristic city at golden hour, towering glass skyscrapers with lush vertical gardens, flying vehicles, cinematic lighting, ultra-detailed, photorealistic",
  "image": "https://example.com/image.jpg",
  "negative_prompt": "blurry, low quality, distorted, watermark, text",
  "size": "2K",
  "seed": 42,
  "watermark": false
};

const response = await fetch(url, {
  method: 'POST',
  headers: {
    'x-api-key': apiKey,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify(data),
});

if (response.ok) {
  // For image/video/audio models, response contains binary data
  const blob = await response.blob();
  const downloadUrl = URL.createObjectURL(blob);

  // Create download link
  const a = document.createElement('a');
  a.href = downloadUrl;
  a.download = 'output.png';
  a.click();

  console.log('Generation complete');
}
```


## Additional Resources

### Documentation

- [Model Playground](https://www.segmind.com/models/wan2.7-image-pro)
- [API Documentation](https://www.segmind.com/models/wan2.7-image-pro/api)
- [Pricing Details](https://www.segmind.com/models/wan2.7-image-pro/pricing)
- [Platform Documentation](https://docs.segmind.com/)