# GPT Image 2 Developer Text-to-Image — Atlas Cloud API

> GPT Image 2 Developer Text-to-Image generates polished visuals from natural-language prompts, with common aspect ratios and 1k, 2k, or supported 4k output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

This is the machine-readable API reference for **GPT Image 2 Developer Text-to-Image** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `openai/gpt-image-2-developer/text-to-image`
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/openai/gpt-image-2-developer/text-to-image
- **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-2-developer/text-to-image"`.
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-2-developer/text-to-image -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-2-developer/text-to-image`


## 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.

- **`size`** (`string`, _optional_):
  optional string or auto or 1024x1024 or 1536x1024 or 5 moreThe size ofthe generated images.For gpt-image-2 and gpt-image-2-2026-04-21,arbitraryresolutions are supported as WIDTHxHEIGHT strings,for example 1536x864 . Width and height mustboth be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1.Resolutions above2560x1440 are experimental, and the maximum supported resolution is 3840x2160 .The requesteosize must also satisfy the model's current pixel and edge limits.The standard sizes 1024x1024.1536x1024 ,and 1024x1536 are supported by the GPT image models; auto is supported for modelsthat allow automatic sizing.For dall-e-2,use oneof 256x256,512x512,or 1024x1024.Fordall-e-3,use oneof 1024x1024,1792x1024,or 1024x1792.
  - Default: `"1024x1024"`
  - Options: "1024x1024", "1024x768", "768x1024", "1024x1536", "1536x1024", "2048x2048", "2048x1152", "1152x2048", "2560x1088", "1088x2560", "2880x2160", "2160x2880", "3840x2160", "2160x3840"

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

- **`output_format`** (`string`, _optional_):
  The format of the output image.
  - Default: `"jpeg"`
  - Options: "jpeg", "png"

- **`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-2-developer/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "openai/gpt-image-2-developer/text-to-image",
  "prompt": "",
  "size": "1024x1024",
  "quality": "medium",
  "output_format": "jpeg",
  "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-2-developer/text-to-image"`

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

- **`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-2-developer/text-to-image",
  "created_at": "",
  "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-2-developer/text-to-image",
  "prompt": "",
  "size": "1024x1024",
  "quality": "medium",
  "output_format": "jpeg",
  "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-2-developer/text-to-image)

## 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 2 Text-to-Image Model

**GPT Image 2 Text-to-Imave** is a cost-efficient multimodal text-to-image generation model powered by OpenAI’s GPT image technology. It combines strong prompt understanding with optimized image synthesis to generate high-quality visuals from natural language, making it ideal for UI design, concept art, product mockups, and creative visualization.

#### 🌟 Key Features

##### 🧠 Strong 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
Professional-quality visual editing at low cost, ideal for rapid prototyping, design iteration, or creative workflows.

#### ⚙️ Parameters

| Parameter | Description |
|---|---|
| `prompt`* | Text description of the desired image (e.g. “street food market at night, photojournalism style...”) |
| `quality` | Output quality tier: `low`, `medium`, or `high` |
| `size` | Output size: `1024×1024`, `1024×1536`, or `1536×1024` |

#### 💳 Pricing

Billing is token-based. The total cost per image is:

**Total = (Input cost + Output cost) × n**

##### Output tokens
Calculated from the requested output `size` and `quality`:

```
tokens = ceil( base × round(base × short_side / long_side) × (2,000,000 + W×H) / 4,000,000 )
```

**Output cost = output\_tokens × $0.00003**

##### Input tokens

**Input cost = prompt x $0.000005**

#### 🎯 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-2-developer/text-to-image · Docs: https://www.atlascloud.ai/docs