# Z-Image Turbo Seamless Tiling API

> Model teks-ke-imej pantas yang menghasilkan output boleh jubin, dengan jubin mendatar, menegak atau dua arah serta inpainting

Menjana imej yang berulang merentasi tepi, dikawal oleh `tiling_mode` (both, horizontal atau vertical), `tile_size` dan `tile_stride`. Menjalankan sehingga 8 langkah inferens dan mengembalikan 1 hingga 4 imej dalam png, jpeg atau webp. Membekalkan `image_url` membolehkan imej-ke-imej, manakala menambah `mask_image_url` membolehkan inpainting. `strength` menetapkan tahap perubahan pada input.

- Model id: `z-image/turbo/tiling`
- Made by: Alibaba
- Category: Text to Image
- Output: image
- Price per megapixel of your output image: $0.02 / megapixel of output image (cheapest run $0.02 (20 API credits))
- Run: `POST https://api.doitong.com/v1/run/z-image/turbo/tiling`
- Quote: `POST https://api.doitong.com/v1/quote/z-image/turbo/tiling`
- Docs page: https://doitong.com/ms/developers/models/z-image/turbo/tiling

## Pricing

Price: **$0.02 / megapixel of output image**. Price per megapixel of your output image: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.02 = 20 API credits (1 MP output image × $0.02).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/z-image/turbo/tiling` 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 |  |  | Prompt yang memandu penjanaan imej. |
| `image_size` |  | object {width, height} \| enum (string) | no | `square_hd` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9`, `auto` | Dimensi imej yang dijana, dengan 'auto' memilih 1024x1024 melainkan imej input dibekalkan; dalam keadaan itu, dimensinya digunakan. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Bilangan langkah inferens yang perlu dijalankan. |
| `seed` |  | integer \| null | no |  |  | Seed untuk imej yang boleh dihasilkan semula: prompt dan seed yang sama menghasilkan imej yang sama apabila versi model tidak berubah. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Bilangan imej yang diminta untuk penjanaan. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Pemeriksaan keselamatan, yang mengembalikan imej hitam menggantikan imej yang ditandai tidak selamat. Nilai true mendayakan pemeriksaan; false melumpuhkannya hanya untuk akaun yang dibenarkan, manakala permintaan tanpa kebenaran tetap diperiksa. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Format fail untuk imej yang terhasil. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high` | Tahap pecutan yang digunakan pada pemprosesan. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Mengawal sama ada pengembangan prompt didayakan. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL imej yang digunakan untuk penjanaan imej-ke-imej atau inpainting. Membekalkan mask_image_url memilih inpainting; meninggalkannya memilih penjanaan imej-ke-imej. |
| `mask_image_url` |  | string (image URL) \| null | no |  |  | URL topeng inpainting yang dibekalkan bersama image_url yang diperlukan. Topeng mengekalkan kawasan hitam tanpa perubahan dan menjana semula kawasan putih. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Kekuatan transformasi yang hanya digunakan pada imej yang dibekalkan melalui image_url; jika tidak, tidak digunakan. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Saiz jubin ruang laten, dengan 64 bersamaan 512px, 128 bersamaan 1024px dan 256 bersamaan 2048px. Dimensi imej yang dijana mengehadkan saiz secara automatik sepanjang paksi berjubin; patchification memerlukan nilai genap yang boleh dibahagi dengan 2. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Langkah jubin ruang laten, dengan kesetaraan piksel 32 = 256px, 64 = 512px dan 128 = 1024px. Hanya gandaan 2 yang sah; sebarang nilai melebihi separuh saiz jubin berkesan akan dikurangkan secara automatik kepada had tersebut. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Arah penjubinan: 'both' meliputi semua arah, 'horizontal' hanya dari kiri ke kanan, dan 'vertical' hanya dari atas ke bawah. |

File parameters (`image`, `mask_image_url`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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.com/v1/run/z-image/turbo/tiling?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

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

### JavaScript

```javascript
const API = "https://api.doitong.com/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/z-image/turbo/tiling?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
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.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/z-image/turbo/tiling", 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.com/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": "z-image/turbo/tiling",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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": "z-image/turbo/tiling",
  "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": 20,
    "usd": "0.02",
    "charged": 20,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "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
      }
    ],
    "timings": {},
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "prompt": "string"
  },
  "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Maklumat fail untuk imej yang dijana. |
| `timings` | object | Maklumat masa untuk proses penjanaan. |
| `seed` | integer | Seed penjanaan imej, termasuk nilai yang dipilih secara rawak jika input tidak membekalkan seed; jika tidak, nilai yang dibekalkan diulang. |
| `has_nsfw_concepts` | array of boolean | Menunjukkan sama ada konsep NSFW muncul dalam imej yang dijana. |
| `prompt` | string | Prompt yang digunakan semasa penjanaan imej. |

## Related models

- [Z Image Base](https://doitong.com/developers/models/z-image/base.md) (`z-image/base`): $0.01 / megapixel
- [Z Image Base Lora](https://doitong.com/developers/models/z-image/base/lora.md) (`z-image/base/lora`): $0.012 / megapixel
- [Z Image Turbo](https://doitong.com/developers/models/z-image/turbo.md) (`z-image/turbo`): $0.005 / megapixel
- [Z Image Turbo Lora](https://doitong.com/developers/models/z-image/turbo/lora.md) (`z-image/turbo/lora`): $0.0085 / megapixel
- [Z-Image Turbo Seamless Tiling Lora](https://doitong.com/developers/models/z-image/turbo/tiling/lora.md) (`z-image/turbo/tiling/lora`): $0.025 / megapixel of output image
- [Z Image Turbo Controlnet](https://doitong.com/developers/models/z-image/turbo/controlnet.md) (`z-image/turbo/controlnet`): $0.013 / image
- [Z Image Turbo Controlnet Lora](https://doitong.com/developers/models/z-image/turbo/controlnet/lora.md) (`z-image/turbo/controlnet/lora`): $0.04 / image
- [Z Image Turbo Image To Image](https://doitong.com/developers/models/z-image/turbo/image-to-image.md) (`z-image/turbo/image-to-image`): $0.015 / image

## Links

- HTML page: https://doitong.com/developers/models/z-image/turbo/tiling
- 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=z-image/turbo/tiling
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/z-image/turbo/tiling