# Z-Image Turbo Seamless Tiling API

> Mudell veloċi minn test għal immaġni li jipproduċi output li jista' jiġi tiled, b'tiling orizzontali, vertikali jew fiż-żewġ direzzjonijiet u inpainting

Jiġġenera immaġnijiet li jirrepetu ruħhom mat-truf, ikkontrollati minn `tiling_mode` (both, horizontal jew vertical), `tile_size` u `tile_stride`. Jaħdem sa 8 passi ta' inferenza u jirritorna 1 sa 4 immaġnijiet f'png, jpeg jew webp. Il-forniment ta' `image_url` jippermetti image-to-image, u ż-żieda ta' `mask_image_url` tippermetti inpainting. `strength` jiddetermina kemm tinbidel l-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.ru/v1/run/z-image/turbo/tiling`
- Quote: `POST https://api.doitong.ru/v1/quote/z-image/turbo/tiling`
- Docs page: https://doitong.com/mt/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.ru/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 li jiggwida l-ġenerazzjoni tal-immaġni. |
| `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` | Dimensjonijiet tal-immaġni ġġenerata, fejn 'auto' jagħżel 1024x1024 sakemm ma tiġix ipprovduta immaġni tal-input; f'dak il-każ jintużaw id-dimensjonijiet tagħha. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Għadd ta’ passi ta’ inference li għandhom jitwettqu. |
| `seed` |  | integer \| null | no |  |  | Żerriegħa għal immaġnijiet riproduċibbli: prompt u żerriegħa identiċi jipproduċu immaġni identika meta l-verżjoni tal-mudell ma tinbidilx. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Għadd ta’ immaġnijiet mitlub għall-ġenerazzjoni. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Kontroll tas-sikurezza, li jirritorna immaġnijiet suwed minflok kwalunkwe immaġni mmarkata bħala mhux sikura. Valur ta’ true jippermetti l-kontroll; false jiddiżattivah biss għal kontijiet awtorizzati, filwaqt li t-talbiet mingħajr awtorizzazzjoni jiġu kkontrollati xorta waħda. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Format tal-fajl għall-immaġni li tirriżulta. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high` | Livell ta’ aċċelerazzjoni applikat għall-ipproċessar. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Jikkontrolla jekk l-espansjoni tal-prompt hijiex attivata. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL tal-immaġni użat jew għall-ġenerazzjoni minn immaġni għal immaġni jew għall-inpainting. Il-provvista ta' mask_image_url tagħżel l-inpainting; jekk ma jiġix ipprovdut, tintgħażel il-ġenerazzjoni minn immaġni għal immaġni. |
| `mask_image_url` |  | string (image URL) \| null | no |  |  | URL tal-maskra tal-inpainting ipprovduta flimkien mal-image_url meħtieġ. Il-maskra żżomm iż-żoni suwed mhux mibdula u tiġġenera mill-ġdid iż-żoni bojod. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Saħħa tat-trasformazzjoni applikata biss għal immaġni pprovduta permezz ta’ image_url; inkella ma tintużax. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Daqs tal-maduma fl-ispazju latent, fejn 64 jikkorrispondi għal 512px, 128 għal 1024px, u 256 għal 2048px. Id-dimensjonijiet tal-immaġni ġġenerata jillimitaw awtomatikament id-daqs tul l-assi kkonsinnati bil-madum; il-patchification teħtieġ valur pari, diviżibbli bi 2. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Pass tal-madum fl-ispazju latent, bl-ekwivalenti f'pixels ta' 32 = 256px, 64 = 512px, u 128 = 1024px. Huma validi biss multipli ta' 2; kwalunkwe valur 'il fuq minn nofs id-daqs effettiv tal-maduma jitnaqqas awtomatikament għal dak il-limitu. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Direzzjoni tal-madum: 'both' tkopri d-direzzjonijiet kollha, 'horizontal' tkopri biss mix-xellug għal-lemin, u 'vertical' tkopri biss minn fuq għal isfel. |

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.ru/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.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/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.ru/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.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": "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.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} | Informazzjoni tal-fajl għall-immaġnijiet iġġenerati. |
| `timings` | object | Informazzjoni dwar il-ħin tal-proċess tal-ġenerazzjoni. |
| `seed` | integer | Seed tal-ġenerazzjoni tal-immaġni, inkluż il-valur magħżul b’mod każwali jekk l-input ma kienx fih seed; inkella, jirrepeti l-valur ipprovdut. |
| `has_nsfw_concepts` | array of boolean | Jindika jekk kunċetti NSFW jidhrux fl-immaġnijiet ġġenerati. |
| `prompt` | string | Prompt użat waqt il-ġenerazzjoni tal-immaġni. |

## 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.ru/v1/models/z-image/turbo/tiling