# Openai GPT Image 1 Mini Edit — Atlas Cloud API

> GPT Image 1 Mini is a cost-efficient, natively multimodal OpenAI model that pairs GPT-5 language understanding with compact image editing and generation from text and image inputs to produce high-quality images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

This is the machine-readable API reference for **Openai GPT Image 1 Mini Edit** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `openai/gpt-image-1-mini/edit`
- **Built by**: OpenAI
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/openai/gpt-image-1-mini/edit
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.004 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: "openai/gpt-image-1-mini/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 openai/gpt-image-1-mini/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**: `openai/gpt-image-1-mini/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:

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation.

- **`images`** (`array[string]`, _required_):
  The images to edit.
  - Min items: 1
  - Max items: 4

- **`quality`** (`string`, _optional_):
  The quality of the generated image.
  - Default: `"medium"`
  - Options: "high", "medium", "low"

- **`size`** (`string`, _optional_):
  The size of the generated media in pixels (width*height).
  - Default: `"1024x1024"`
  - Options: "1024x1024", "1024x1536", "1536x1024"

- **`enable_sync_mode`** (`boolean`, _optional_):
  If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.
  - Default: `false`

- **`enable_base64_output`** (`boolean`, _optional_):
  If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "openai/gpt-image-1-mini/edit",
  "images": [
    ""
  ],
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "openai/gpt-image-1-mini/edit",
  "prompt": "",
  "images": [
    ""
  ],
  "quality": "medium",
  "size": "1024x1024",
  "enable_sync_mode": false,
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`model`** (`string`, _optional_):
  model name
  - Default: `"openai/gpt-image-1-mini/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": "openai/gpt-image-1-mini/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": "openai/gpt-image-1-mini/edit",
  "prompt": "",
  "images": [
    ""
  ],
  "quality": "medium",
  "size": "1024x1024",
  "enable_sync_mode": false,
  "enable_base64_output": false
}'

# 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/openai/gpt-image-1-mini/edit)

## About this model

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

### openai/gpt-image-1-mini/edit

**GPT Image 1 Mini (Edit)** is a cost-efficient multimodal image editing model powered by OpenAI’s GPT-5 architecture. It enables users to refine, modify, or transform existing images using natural language instructions, while maintaining the original style, composition, and visual integrity.

#### 🌟 Key Features

##### 🧠 GPT-5-Powered Visual Understanding
Understands complex textual instructions and applies targeted edits that match intent and context.

##### 🎨 Intelligent Image Editing
Add, remove, or modify elements in an image with precision — from subtle adjustments to full stylistic transformations.

##### 🖼 Multi-Image Support
Accepts one or more image inputs to guide the edit or style reference process.

##### 💡 Context-Aware Refinement
Preserves the key artistic or photographic features, such as lighting, tone, and pose, while applying changes only where needed.

##### 💰 Efficient and Accessible
Offers professional-quality visual editing at a low cost, ideal for rapid prototyping, design iteration, or creative workflows.

#### ⚙️ Parameters

| Parameter | Description |
|---|---|
| `prompt`* | Describe how you want to edit or modify the image (e.g. “change outfit colors to pastel tones, add neon city lights in the background”) |
| `images`* | Upload one or more reference images (`JPG` / `PNG`) to be edited or used as visual input |

#### 💡 Example Prompt

> Three fashionable young women in a nighttime urban scene, showcasing Y2K and streetwear aesthetics. Each has distinct styling: plaid shirt with ripped jeans, off-shoulder top with retro socks and chunky sneakers, crop top with cowboy boots and accessories. Enhance lighting and color balance for a cinematic look.

#### 🎯 Use Cases

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

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/openai/gpt-image-1-mini/edit · Docs: https://www.atlascloud.ai/docs