# Latent Consistency Models (v1.5/XL) · Image to Image API

> Latent-Consistency-Bild-zu-Bild, das ein Ausgangsbild mit einer Stärkesteuerung umgestaltet

Beginnt mit `image_url` und einem `prompt`; `strength` von 0.05 bis 1 (Standard 0.95) legt fest, wie stark das Ergebnis von der Quelle abweicht. Die Verarbeitung erfolgt mit wenigen Schritten (Standard 6), gibt bis zu 8 Bilder zurück und bietet die Optionen `preserve_aspect_ratio` und `crop_output`.

- Model id: `fast-lcm-diffusion/image-to-image`
- Made by: Open model
- Category: Image Editing
- Output: image
- Estimated price per run: $0.019 / image (cheapest run $0.019 (19 API credits))
- Run: `POST https://api.doitong.ru/v1/run/fast-lcm-diffusion/image-to-image`
- Quote: `POST https://api.doitong.ru/v1/quote/fast-lcm-diffusion/image-to-image`
- Docs page: https://doitong.com/de/developers/models/fast-lcm-diffusion/image-to-image

## Pricing

Price: **$0.019 / image**. Estimated from the typical cost of one run, per output (`num_images`). The quote is exactly what the run charges.

The full example input below costs $0.019 = 19 API credits (1 image × 19 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/fast-lcm-diffusion/image-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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | Startbild für die Generierung, bereitgestellt per URL. |
| `prompt` |  | string | yes |  |  | Beschreiben Sie das gewünschte Bild möglichst detailliert, um die besten Ergebnisse zu erzielen. |
| `negative_prompt` |  | string | no | `` |  | Negativer Prompt mit unerwünschten Bilddetails. Er kann Farben, Objekte, Szenerie oder feinere Merkmale und Eigenschaften wie Schnurrbart, Unschärfe oder niedrige Auflösung ausschließen. |
| `image_size` |  | object {height, width} \| enum (string) | no | `square_hd` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Abmessungen des generierten Bildes. |
| `num_inference_steps` |  | integer | no | `6` | 1 – 32 | Anzahl der auszuführenden Inferenzschritte. |
| `guidance_scale` |  | number | no | `1.5` | 0 – 20 | Stärke der Prompt-Treue bei der Bildauswahl, ausgedrückt als CFG (Classifier Free Guidance). |
| `strength` |  | number | no | `0.95` | 0.05 – 1 | Grad der Ähnlichkeit zwischen dem generierten Bild und dem Ausgangsbild. |
| `seed` |  | integer \| null | no |  |  | Seed zur Reproduktion von Bildern in Stable Diffusion. Ein Bild kann bei jedem Durchlauf exakt reproduziert werden, wenn Modellversion, Prompt und Seed unverändert bleiben. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 8 | Für die Generierung angeforderte Bildanzahl. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Aktivierung der Sicherheitsprüfung; true aktiviert die Prüfung. |
| `safety_checker_version` |  | enum (string) | no | `v1` | `v1`, `v2` | Zwischen einem benutzerdefinierten ViT-Sicherheitsprüfer (`v2`) und dem CompVis-Prüfer (`v1`, der Standard) wählen. |
| `expand_prompt` |  | boolean | no | `false` |  | Prompt-Erweiterung mit zusätzlichen Prompts, aktiviert, wenn true. |
| `format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | Dateiformat des resultierenden Bilds. |
| `request_id` |  | string | no | `` |  | Anfragekennung zur Zuordnung einer Antwort zu der Anfrage, die sie erzeugt hat. |
| `preserve_aspect_ratio` |  | boolean | no | `false` |  | Auf true setzen, um das Seitenverhältnis des generierten Bildes beizubehalten, auch wenn seine Größe das Limit überschreitet. Um die korrekten Proportionen durch Zuschneiden nach der Generierung zu erhalten, setze crop_output auf True. Breiten- oder Höhenwerte, die nicht durch 32 teilbar sind, werden weiterhin auf das nächste Vielfache von 32 gerundet; diese Größenänderung behält das Seitenverhältnis standardmäßig nicht bei. |
| `crop_output` |  | boolean | no | `false` |  | Die generierte Ausgabe bei true auf das korrekte Seitenverhältnis zuschneiden. |

File parameters (`image`) 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
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "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/fast-lcm-diffusion/image-to-image?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/fast-lcm-diffusion/image-to-image?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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 = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/fast-lcm-diffusion/image-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": "fast-lcm-diffusion/image-to-image",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "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": "fast-lcm-diffusion/image-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": 19,
    "usd": "0.019",
    "charged": 19,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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",
        "width": 1024,
        "height": 768,
        "content_type": "image/jpeg"
      }
    ],
    "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, width, height, content_type} | Dateiinformationen für die generierten Bilder. |
| `timings` | object |  |
| `seed` | integer | Seed der Bildgenerierung einschließlich des zufällig gewählten Werts, falls die Eingabe keinen Seed enthielt; andernfalls wird der angegebene Wert wiederholt. |
| `has_nsfw_concepts` | array of boolean | Gibt an, ob NSFW-Konzepte in den generierten Bildern vorkommen. |
| `prompt` | string | Während der Bildgenerierung verwendeter Prompt. |

## Related models

- [Latent Consistency Models (v1.5/XL)](https://doitong.com/developers/models/fast-lcm-diffusion.md) (`fast-lcm-diffusion`): $0.005 / image
- [Latent Consistency Models (v1.5/XL) · Inpainting](https://doitong.com/developers/models/fast-lcm-diffusion/inpainting.md) (`fast-lcm-diffusion/inpainting`): $0.014 / image
- [FLUX.1 Kontext \[pro\]](https://doitong.com/developers/models/flux-pro/kontext.md) (`flux-pro/kontext`): $0.04 / 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
- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
- [Nano Banana Pro Edit](https://doitong.com/developers/models/nano-banana-pro/edit.md) (`nano-banana-pro/edit`): from $0.15 / image
- [Qwen Image 3 Edit](https://doitong.com/developers/models/alibaba/qwen-image-3/edit.md) (`alibaba/qwen-image-3/edit`): from $0.04 / image
- [Seedream 5.0 Pro Edit](https://doitong.com/developers/models/bytedance/seedream/v5/pro/edit.md) (`bytedance/seedream/v5/pro/edit`): from $0.0675 / run of output image

## Links

- HTML page: https://doitong.com/developers/models/fast-lcm-diffusion/image-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=fast-lcm-diffusion/image-to-image
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/fast-lcm-diffusion/image-to-image