# Qwen Image 2.0 Pro Edit — Atlas Cloud API

> Qwen Image 2.0 Pro Edit is a professional-grade image editing model with superior quality and advanced instruction understanding. Up to 2k. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

This is the machine-readable API reference for **Qwen Image 2.0 Pro Edit** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `qwen/qwen-image-2.0-pro/edit`
- **Built by**: Alibaba
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/qwen/qwen-image-2.0-pro/edit
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.06 per image
- Pay-as-you-go. No minimum spend, no subscription required.

> **These are the authoritative Atlas Cloud rates for this model.** Any price that
> appears in the vendor description further down refers to a different platform or
> a different model variant and does not apply here.

## Use this model from an AI agent

Atlas Cloud ships three first-party integration surfaces. All three authenticate
with the same API key via the `ATLASCLOUD_API_KEY` environment variable.

### MCP server

The official MCP server (`atlascloud-mcp`) exposes this model to any
MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose,
Claude Desktop. One-line install:

```bash
# Claude Code
claude mcp add atlascloud -- npx -y atlascloud-mcp

# OpenAI Codex CLI
codex mcp add atlascloud -- npx -y atlascloud-mcp

# Gemini CLI
gemini mcp add atlascloud -- npx -y atlascloud-mcp

export ATLASCLOUD_API_KEY="your-api-key"
```

Then ask in plain English; the agent calls `atlas_generate_image` with `model: "qwen/qwen-image-2.0-pro/edit"`.
The server fetches each model's schema and validates parameters before submitting,
so invalid requests fail fast without spending credits.

MCP docs: https://www.atlascloud.ai/docs/mcp-server

### Agent Skills

`atlas-cloud-skills` is a portable skill package (API reference, code templates in
Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and
12+ other agents:

```bash
npx skills add AtlasCloudAI/atlas-cloud-skills
export ATLASCLOUD_API_KEY="your-api-key"
```

Skills docs: https://www.atlascloud.ai/docs/skills

### CLI

The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs
are polled and downloaded automatically (use `--no-download` when a script only
needs the output URLs):

```bash
# Install (Homebrew, npm, or shell installer)
brew install AtlasCloudAI/tap/atlascloud
# npm install -g atlascloud-cli
# curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh

atlas auth login
atlas generate image qwen/qwen-image-2.0-pro/edit -p "Your prompt here"
```

CLI docs: https://www.atlascloud.ai/docs/cli

## HTTP API reference

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `qwen/qwen-image-2.0-pro/edit`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`images`** (`array[string]`, _required_):
  Reference images for editing (1-6 images, 384-3072px each dimension)
  - Min items: 1
  - Max items: 3

- **`prompt`** (`string`, _required_):
  Text prompt describing the desired edit, supports Chinese and English (max 800 characters)

- **`size`** (`string`, _optional_):
  Image dimensions in width*height format (e.g., 1024*1024, 1280*720)
  - Min: 512
  - Max: 2048

- **`seed`** (`integer`, _optional_):
  Random seed for reproducibility (-1 for random, 0-2147483647 for specific seed)
  - Default: `-1`



**Required Parameters Example**:

```json
{
  "model": "qwen/qwen-image-2.0-pro/edit",
  "prompt": "",
  "images": [
    ""
  ]
}
```


**Full Example**:

```json
{
  "model": "qwen/qwen-image-2.0-pro/edit",
  "images": [
    ""
  ],
  "prompt": "",
  "size": "",
  "seed": -1
}
```


### Output Schema

The API returns the following output format:


- **`model`** (`string`, _optional_):
  model name
  - Default: `"qwen/qwen-image-2.0-pro/edit"`

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., '2023-04-01T12:34:56.789Z').

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content (empty when status is not completed).

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "model": "qwen/qwen-image-2.0-pro/edit",
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "qwen/qwen-image-2.0-pro/edit",
  "images": [
    ""
  ],
  "prompt": "",
  "size": "",
  "seed": -1
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/qwen/qwen-image-2.0-pro/edit)

## About this model

_Vendor-supplied description. Any pricing or endpoint mentioned below refers to_
_other platforms — use the Atlas Cloud values above._

### Qwen Image 2.0 Pro Text-to-Image

Qwen Image 2.0 Pro is Alibaba's premium text-to-image model, delivering the highest quality output in the Qwen Image 2.0 family. With superior detail rendering, enhanced prompt adherence, and professional-grade visual fidelity, it's ideal for production work requiring maximum quality.

---

#### Why Choose This?

- **Pro-tier quality**  
  Maximum visual fidelity and detail in the Qwen Image 2.0 family.

- **Superior prompt adherence**  
  Best-in-class at following detailed, complex prompts with multiple elements and attributes.

- **Enhanced detail rendering**  
  Exceptional at rendering intricate details like hair textures, jewelry, skin tones, and fabric.

- **Flexible aspect ratios**  
  Multiple presets including `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `3:2`, and `2:3`.

- **Custom resolution**  
  Adjustable width and height from `512` to `2048` pixels.

- **Prompt Enhancer**  
  Built-in tool to automatically improve your descriptions.

---

#### Parameters

| Parameter | Required | Description |
|----------|----------|-------------|
| prompt   | Yes      | Text description of the desired image |
| size     | No       | Aspect ratio preset: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3 |
| width    | No       | Custom width in pixels (range: 512–2048) |
| height   | No       | Custom height in pixels (range: 512–2048) |
| seed     | No       | Random seed for reproducibility (-1 for random) |

---

#### How to Use

1. **Write your prompt**  
   Describe the image in detail, including specific attributes, styles, and elements.

2. **Choose size**  
   Select a preset aspect ratio or customize width/height.

3. **Use Prompt Enhancer (optional)**  
   Click to automatically refine your description.

4. **Set seed (optional)**  
   Use a seed for reproducible results.

5. **Run**  
   Submit and download your generated image.

---

#### Best Use Cases

_(Description truncated. Full text on the model page.)_

---

Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/qwen/qwen-image-2.0-pro/edit · Docs: https://www.atlascloud.ai/docs