# OpenAI GPT Image 1.5 — Image Edit

> Access openai gpt image 1.5 for elite visual reasoning and OCR. Integrate this powerful gpt image 1.5 API through GPTProto for lower latency and better ROI.

## Overview

- **Endpoint**: `POST https://gptproto.com/api/v3/openai/gpt-image-1.5/image-edit`
- **Result URL**: `GET https://gptproto.com/api/v3/predictions/{result_id}/result` — the submit response also returns the authoritative URL in `data.urls.get`
- **Model ID**: `gpt-image-1.5`
- **Vendor**: OpenAI
- **Scene**: `image-edit`
- **Category**: image-to-image
- **Modalities**: input image → output image
- **Playground**: https://gptproto.com/model/openai/gpt-image-1.5/image-edit
- **API documentation**: https://docs.gptproto.com/docs/allapi/OpenAI/gpt-image-1.5/official-format/image-edit
- **Other scenes of this model**: `text-to-image` — same auth, different endpoint path and input schema

## Authentication

Every request needs a GPTProto API key in the `Authorization` header. Create one at https://gptproto.com/dashboard/api-key, then export it:

```bash
export GPTPROTO_API_KEY="your-api-key"
```

Header: `Authorization: Bearer $GPTPROTO_API_KEY` (plus `Content-Type: application/json` on POST).

## Pricing

Platform price by tier (USD, already includes the GPTProto discount):

- **Image Output** — $0.0224 per 1K tokens
- **Image Input** — $0.0056 per 1K tokens
- **Cached Input** — $0.0014 per 1K tokens
- **Text Input** — $0.0035 per 1K tokens
- **Text Output** — $0.007 per 1K tokens

Price range: $0 – $0 per generation.

Prices may change. The model page always shows the live price: https://gptproto.com/model/openai/gpt-image-1.5/image-edit

## API Information

The API is asynchronous: POST the endpoint to create a prediction, then poll its result URL until `status` is `completed` or `failed`.

### Input Schema

The endpoint accepts the following JSON body parameters:

- **`image`** (`string[]`, _required_):
  The images to edit. A maximum of 16 reference images can be uploaded.
  - Max items: 16

- **`prompt`** (`string`, _required_):
  A text description of the desired image(s). The maximum length is 32000 characters for gpt-image-1.

- **`mask`** (`string`, _optional_):
  An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where image should be edited. If there are multiple images provided, the mask will be applied on the first image. Must be a valid PNG file, less than 4MB, and have the same dimensions as image.

- **`n`** (`range`, _optional_):
  The number of images to generate. Must be between 1 and 10.
  - Default: `1`
  - Range: 1–10

- **`quality`** (`enum`, _optional_):
  The quality of the image that will be generated. high, medium and low are only supported for gpt-image-1
  - Default: `auto`
  - Options: auto, high, medium, low

- **`background`** (`enum`, _optional_):
  Allows to set transparency for the background of the generated image(s). This parameter is only supported for gpt-image-1. Must be one of transparent, opaque or auto (default value). When auto is used, the model will automatically determine the best background for the image.
  - Default: `auto`
  - Options: auto, transparent, opaque

- **`enable_sync_mode`** (`boolean`, _optional_):
  This parameter is only supported for gpt-image-1.
  - Options: true, false

- **`response_format`** (`enum`, _optional_):
  The format in which the generated image result will be returned.
  - Default: `url`
  - Options: b64_json, url

**Required Parameters Example**:

```json
{
  "image": [],
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle"
}
```

**Full Example**:

```json
{
  "image": [],
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
  "mask": "",
  "n": 1,
  "quality": "auto",
  "background": "auto",
  "enable_sync_mode": false,
  "response_format": "url"
}
```

### Output Schema

Both submit and poll return the same envelope:

- **`data.id`** (`string`): Prediction id. Use it as `result_id` when polling for the result.
- **`data.status`** (`string`): One of `created`, `running`, `completed`, `failed`. See Status Values below.
- **`data.outputs`** (`array of string`): Generated files. Empty until `status` is `completed`; then it holds the output URLs (or base64 strings when the model exposes a base64 option).
- **`data.urls.get`** (`string`): Authoritative result URL for this prediction. Prefer it over building the poll URL yourself.
- **`data.error`** (`string | null`): Failure reason when `status` is `failed`, otherwise `null`.
- **`data.executionTime`** (`integer`): Total processing time in milliseconds.
- **`data.timings.inference`** (`integer`): Model inference time in milliseconds.
- **`data.hasNsfwContents`** (`array of boolean`): Per-output moderation flags.
- **`message`** (`string`): `success` on a normal response, otherwise the error message.
- **`code`** (`integer`): Business status code. `200` means the request was accepted.

**Example Response — submit (task accepted)**:

```json
{
  "data": {
    "id": "pred_example_01",
    "model": "gpt-image-1.5",
    "outputs": [],
    "urls": {
      "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result"
    },
    "hasNsfwContents": [],
    "status": "created",
    "createdAt": "2026-01-01T12:00:00Z",
    "executionTime": 0,
    "timings": {
      "inference": 0
    }
  },
  "message": "success",
  "code": 200
}
```

**Example Response — poll (completed)**:

```json
{
  "data": {
    "id": "pred_example_01",
    "model": "gpt-image-1.5",
    "outputs": [
      "https://oss-us.gptproto.com/example/output.png"
    ],
    "urls": {
      "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result"
    },
    "status": "completed",
    "error": null,
    "executionTime": 12345,
    "timings": {
      "inference": 12000
    },
    "has_nsfw_contents": [],
    "created_at": "2026-01-01T12:00:00Z"
  },
  "message": "success",
  "code": 200
}
```

### Status Values

- `created` — Task accepted. Use `data.id` as `result_id` for polling.
- `running` — Generation is in progress. Keep polling.
- `completed` — Finished successfully. Generated files are in `data.outputs`.
- `failed` — Generation failed. Read `data.error` for the reason.

## Usage Examples

### 1. Submit a request

```bash
curl --request POST "https://gptproto.com/api/v3/openai/gpt-image-1.5/image-edit" \
  --header "Authorization: Bearer $GPTPROTO_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "image": [],
    "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
    "mask": "",
    "n": 1,
    "quality": "auto",
    "background": "auto",
    "enable_sync_mode": false,
    "response_format": "url"
  }'
```

```python
import os
import requests

url = "https://gptproto.com/api/v3/openai/gpt-image-1.5/image-edit"
headers = {
  "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}",
  "Content-Type": "application/json"
}
payload = {
  "image": [],
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
  "mask": "",
  "n": 1,
  "quality": "auto",
  "background": "auto",
  "enable_sync_mode": False,
  "response_format": "url"
}

response = requests.request("POST", url, headers=headers, json=payload)
print(response.json())
```

```typescript
const response = await fetch("https://gptproto.com/api/v3/openai/gpt-image-1.5/image-edit", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    image: [],
    prompt: "A tiny origami fox sailing a teacup across a moonlit puddle",
    mask: "",
    n: 1,
    quality: "auto",
    background: "auto",
    enable_sync_mode: false,
    response_format: "url",
  }),
});

const data = await response.json();
console.log(data);
```

### 2. Poll until the task finishes

Replace `YOUR_RESULT_ID` with `data.id` from the submit response (or call `data.urls.get` directly), and keep polling every 1–3 seconds while `status` is `created` or `running`.

```bash
result_id="YOUR_RESULT_ID"

curl --request GET "https://gptproto.com/api/v3/predictions/$result_id/result" \
  --header "Authorization: Bearer $GPTPROTO_API_KEY"
```

```python
import os
import requests

result_id = "YOUR_RESULT_ID"
url = f"https://gptproto.com/api/v3/predictions/{result_id}/result"
headers = {
  "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}"
}
response = requests.request("GET", url, headers=headers)
print(response.json())
```

```typescript
const result_id = "YOUR_RESULT_ID";
const response = await fetch(`https://gptproto.com/api/v3/predictions/${result_id}/result`, {
  method: "GET",
  headers: {
    "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
  },
});

const data = await response.json();
console.log(data);
```

## Example Prompts

- Transform this painting into a Japanese manga style
- Her hair was half white and half black, she took off her glasses, and wore a turtleneck sweater.
- Replace your glasses with sunglasses and a black beret, and change the background to red.

## HTTP Status Codes

- `400` — malformed body, a parameter or value this model does not accept, or input blocked by the provider's content moderation
- `401` — missing or invalid API key
- `403` — insufficient credits
- `413` — request body too large
- `429` — rate limited; retry with backoff
- `500` — An internal server error occurred
- `502` — An internal server error occurred
- `504` — Gateway timeout — upstream service did not respond in time; retry later

## Additional Resources

- [Model playground](https://gptproto.com/model/openai/gpt-image-1.5/image-edit)
- [API documentation](https://docs.gptproto.com/docs/allapi/OpenAI/gpt-image-1.5/official-format/image-edit)
- [All models](https://gptproto.com/model)
- [API keys](https://gptproto.com/dashboard/api-key)
- [Platform overview for LLMs](https://gptproto.com/llm-full.txt)
- Any other model: `https://gptproto.com/model/{vendor}/{model}/{scene}/llms.txt`