# GPT Image 2.5 Text to Image API

> He tauira whakaahua nā OpenAI e tino whai ana i ngā tohutohu, e pai ana te tā tuhinga, ā, e tautoko ana i ngā papamuri pūataata.

He kaiwhakaputa whakaahua whānui nā OpenAI: ka whai ia i ngā tohutohu roa, motuhake hoki, ka āta whakarite i te tuhinga me ngā hoahoa, ā, ka taea te whakahoki PNG, WebP rānei me tētahi papamuri pūataata mō ngā whakapiri, ata me ngā tapahanga hua. E rima ngā taumata kounga hei whakawhiti i te tere me te utu mō te taipitopito. Ka eke ngā rahinga ki te 3840 px i te tapa roa (he whakareatanga o te 16, ko te mōrahi 3:1); kia tekau ngā whakaahua mō ia tono.

- Model id: `openai/gpt-image-2.5/flare/text-to-image`
- Made by: OpenAI
- Category: Text to Image
- Output: image
- Price: from $0.008 / image (cheapest run $0.008 (8 API credits))
- Run: `POST https://api.doitong.ru/v1/run/openai/gpt-image-2.5/flare/text-to-image`
- Quote: `POST https://api.doitong.ru/v1/quote/openai/gpt-image-2.5/flare/text-to-image`
- Docs page: https://doitong.com/mi/developers/models/openai/gpt-image-2.5/flare/text-to-image

## Pricing

Price: **from $0.008 / image** (the lowest tier; the quote prices your exact input). Billed per generated image (`num_images`, default 1).

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `image_size` is landscape_4_3, portrait_4_3: by `quality`, low: $0.008, medium: $0.013, high: $0.04, xhigh: $0.068, max: $0.148, auto: $0.148 / image
- When `image_size` is square_hd, square, portrait_16_9, landscape_16_9: by `quality`, low: $0.009, medium: $0.017, high: $0.056, xhigh: $0.097, max: $0.214, auto: $0.214 / image
- When `quality` is low, medium, high, xhigh, max, auto: by `quality`, low: $0.015, medium: $0.029, high: $0.104, xhigh: $0.181, max: $0.404, auto: $0.404 / image

The full example input below costs $0.017 = 17 API credits (1 image × 17 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.ru/v1/quote/openai/gpt-image-2.5/flare/text-to-image` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  | 1 – 32000 characters | Tohutohu i whakamahia hei whakaputa atahanga. |
| `image_size` |  | object {width, height} \| enum (string) | no | `landscape_4_3` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9`, `auto` | Ka whakaaetia e ngā rahinga putanga he ingoa tatūkē, he ahanoa {width, height}, he 'auto' rānei mō te kōwhiringa rahinga pai rawa a te tauira. Me whakawehe ngā rahinga tūturu katoa ki te 16, kaua ngā tapa e roa ake i te 3840px, kaua te ōwehenga āhuatanga e nui ake i te 3:1, ā, me 655,360–8,294,400 te tapeke pika. |
| `background` |  | enum (string) | no | `auto` | `auto`, `transparent`, `opaque` | Papamuri o te atahanga hua. |
| `quality` |  | enum (string) | no | `high` | `auto`, `low`, `medium`, `high`, `xhigh`, `max` | Te kōwhiringa kounga atahanga, mā te 'auto' ka waiho te whakatau ki te tauira. Ko ngā tautuhinga teitei ake he taipitopito anō, engari he roa ake te whakautu, he nui ake hoki te whakamahinga tohu. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 10 | Te maha o ngā atahanga hei whakaputa. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Hōputu kōnae o ngā atahanga putanga. |
| `output_compression` |  | integer \| null | no |  | 0 – 100 | Te tautuhinga kōpeketanga e wātea ana mō te 'jpeg', 'webp' rānei i output_format anake; ko te awhe e whakaaetia ana ko 0–100. |

## Example input

Required parameters only:

```json
{
  "prompt": "A flat vector sticker of a smiling cactus wearing sunglasses, thick white outline, no background"
}
```

A fuller example:

```json
{
  "prompt": "A flat vector sticker of a smiling cactus wearing sunglasses, thick white outline, no background",
  "image_size": "square_hd",
  "quality": "medium",
  "background": "transparent"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/openai/gpt-image-2.5/flare/text-to-image?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A flat vector sticker of a smiling cactus wearing sunglasses, thick white outline, no background",
    "image_size": "square_hd",
    "quality": "medium",
    "background": "transparent"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/openai/gpt-image-2.5/flare/text-to-image?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A flat vector sticker of a smiling cactus wearing sunglasses, thick white outline, no background",
    "image_size": "square_hd",
    "quality": "medium",
    "background": "transparent"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A flat vector sticker of a smiling cactus wearing sunglasses, thick white outline, no background",
    "image_size": "square_hd",
    "quality": "medium",
    "background": "transparent",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/openai/gpt-image-2.5/flare/text-to-image", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.ru/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "openai/gpt-image-2.5/flare/text-to-image",
      "input": {
        "prompt": "A flat vector sticker of a smiling cactus wearing sunglasses, thick white outline, no background",
        "image_size": "square_hd",
        "quality": "medium",
        "background": "transparent"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "openai/gpt-image-2.5/flare/text-to-image",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 17,
    "usd": "0.017",
    "charged": 17,
    "refunded": 0
  },
  "input": {
    "prompt": "A flat vector sticker of a smiling cactus wearing sunglasses, thick white outline, no background",
    "image_size": "square_hd",
    "quality": "medium",
    "background": "transparent"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ]
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Ngā atahanga i whakaputaina e te tauira. |

## Related models

- [GPT Image 2.5 Sunburst Text to Image](https://doitong.com/developers/models/openai/gpt-image-2.5/sunburst/text-to-image.md) (`openai/gpt-image-2.5/sunburst/text-to-image`): $0.054 / image
- [GPT Image 2.5 Edit](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/edit.md) (`openai/gpt-image-2.5/flare/edit`): from $0.12 / image
- [GPT Image 2.5 Sunburst Edit](https://doitong.com/developers/models/openai/gpt-image-2.5/sunburst/edit.md) (`openai/gpt-image-2.5/sunburst/edit`): $0.128 / image
- [FLUX.1 \[dev\]](https://doitong.com/developers/models/flux/dev.md) (`flux/dev`): $0.025 / megapixel
- [FLUX.1 \[schnell\]](https://doitong.com/developers/models/flux/schnell.md) (`flux/schnell`): $0.003 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [Ideogram V4.5](https://doitong.com/developers/models/ideogram/v4.5.md) (`ideogram/v4.5`): from $0.03 / image

## Links

- HTML page: https://doitong.com/developers/models/openai/gpt-image-2.5/flare/text-to-image
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=openai/gpt-image-2.5/flare/text-to-image
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/openai/gpt-image-2.5/flare/text-to-image