# Openai GPT Image 1.5 Text-to-Image — Atlas Cloud API

> GPT Image 1.5 text to image is OpenAI’s fast, cost-efficient text-to-image generator powered by GPT-5 guidance. Create photorealistic shots, product renders, concept art, and stylized graphics from natural-language prompts (optionally conditioned with an image). Supports custom aspect ratios, seeds, negative prompts, hex color hints, and style presets. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

This is the machine-readable API reference for **Openai GPT Image 1.5 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-1.5/text-to-image`
- **Built by**: OpenAI
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/openai/gpt-image-1.5/text-to-image
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.008 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-1.5/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-1.5/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-1.5/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_):
  The size of the generated media in pixels (width*height).
  - Default: `"1024x1024"`
  - Options: "1024x1024", "1024x1536", "1536x1024"

- **`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-1.5/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "openai/gpt-image-1.5/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-1.5/text-to-image"`

- **`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-1.5/text-to-image",
  "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-1.5/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-1.5/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._

### GPT 1.5 Text to Image

**GPT Image 1.5 Text to Image** 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 Prompt Understanding
Accurately interprets complex prompts, styles, and constraints to produce coherent, context-aware images.

##### 🎨 Efficient Image Generation
Generates polished, high-fidelity images with low latency and cost-friendly performance.

##### 💡 Multimodal-Ready Foundation
Built for workflows that benefit from both text guidance and visual reasoning.

##### 💰 Cost-Effective at Scale
Great for rapid iteration, A/B creative testing, and production pipelines.

##### 🧩 UI/UX Friendly Outputs
Performs well on clean compositions, modern design aesthetics, and structured layouts.

#### ⚙️ Parameters

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

#### 💡 Example Prompt

> Street food market in Tokyo at night, chef tossing flaming wok with vegetables mid-air, steam rising, colorful paper lanterns overhead, motion blur on crowd in background, vibrant neon signs, photojournalism style

#### 🎯 Use Cases

- **UI / UX Design Concepts** – Generate layouts, interface inspirations, and design directions.
- **Product & Marketing Visuals** – Create campaign-ready images and fast mockups.
- **Creative Ideation** – Explore styles, moodboards, and concept art quickly.
- **Education & Presentations** – Produce illustrative visuals for decks, demos, and teaching materials.

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/openai/gpt-image-1.5/text-to-image · Docs: https://www.atlascloud.ai/docs