# LTX Video-0.9.7 13B Distilled API

> Text-to-video se starším destilovaným modelem 0.9.7 13B s podporou LoRA a dlouhých sekvencí snímků

Generuje video z povinného `prompt` pomocí destilovaného modelu 0.9.7. Rozlišení je 480p nebo 720p, poměr stran 9:16, 1:1 nebo 16:9 a `num_frames` může být 9 až 1441 při 1 až 60 fps. Každý ze dvou vzorkovacích průchodů trvá 2 až 12 kroků. K dispozici jsou volitelné `loras`, dodatečný průchod detailů a rozšíření promptu.

- Model id: `ltx-video-13b-distilled`
- Made by: Lightricks
- Category: Text to Video
- Output: video
- Price per second of your output video: from $0.04 / second of output video (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.com/v1/run/ltx-video-13b-distilled`
- Quote: `POST https://api.doitong.com/v1/quote/ltx-video-13b-distilled`
- Docs page: https://doitong.com/cs/developers/models/ltx-video-13b-distilled

## Pricing

Price: **from $0.04 / second of output video** (the lowest tier; the quote prices your exact input). Price per second of your output video: 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 $0.202 = 202 API credits (5.0417 s output video × $0.04).

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/ltx-video-13b-distilled` 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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Textové pokyny řídící generování. |
| `negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | Negativní textové pokyny pro generování. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | Váhy LoRA použité během generování. |
| `loras[].path` |  | string | yes |  |  | Umístění vah LoRA zadané jako URL nebo cesta. |
| `loras[].weight_name` |  | string \| null | no |  |  | Název váhy LoRA pro výběr z více vah v repozitáři HuggingFace; vyžadují jej pouze repozitáře obsahující více vah. Toto nastavení nemá účinek, pokud `path` neurčuje repozitář HuggingFace. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Násobitel škálující váhu LoRA při načítání. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | Rozlišení výstupního videa. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `9:16`, `1:1`, `16:9` | Poměr stran výsledného videa. |
| `seed` |  | integer \| null | no |  |  | Seed řídící náhodnost během generování. |
| `num_frames` |  | integer | no | `121` | 9 – 1,441 | Celkový počet snímků videa. |
| `first_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Počet inferenčních kroků v prvním průchodu. |
| `second_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Počet inferenčních kroků ve druhém průchodu. |
| `second_pass_skip_initial_steps` |  | integer | no | `5` | 1 – 11 | Počáteční počet inferenčních kroků vynechaných během druhého průchodu, čímž se tento průchod zaměří spíše na jemné detaily než na velké změny. |
| `frame_rate` |  | integer | no | `24` | 1 – 60 | Snímková frekvence videa. |
| `expand_prompt` |  | boolean | no | `false` |  | Rozšíření promptu pomocí jazykového modelu. |
| `reverse_video` |  | boolean | no | `false` |  | Obrácení pořadí přehrávání videa. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Přepínač kontroly bezpečnosti, jehož vypnutí se respektuje pouze u autorizovaných účtů. U všech požadavků bez tohoto oprávnění se provádějí bezpečnostní kontroly. |
| `enable_detail_pass` |  | boolean | no | `false` |  | Volitelný druhý průchod vylepšením, který po zapnutí zlepší detaily videa. |
| `temporal_adain_factor` |  | number | no | `0.5` | 0 – 1 | Síla adaptivní normalizace instance (AdaIN), která při vyšších hodnotách vyvažuje konzistenci barev a při nižších větší barevnou variabilitu. Funguje na vygenerovaných blocích kromě prvního a normalizuje rozložení barev v celém videu, aby pomohla omezit postupný nárůst sytosti nebo kontrastu. |
| `tone_map_compression_ratio` |  | number | no | `0` | 0 – 1 | Úroveň komprese mapování tónů od bez komprese při 0.0 po maximální kompresi při 1.0. Komprese dynamického rozsahu videa tímto způsobem zlepšuje vizuální kvalitu. |

## 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/ltx-video-13b-distilled?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/ltx-video-13b-distilled?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/ltx-video-13b-distilled", 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": "ltx-video-13b-distilled",
      "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": "ltx-video-13b-distilled",
  "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": 202,
    "usd": "0.202",
    "charged": 202,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    },
    "prompt": "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene.",
    "seed": 42
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "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 |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | Video soubor vytvořený generováním. |
| `prompt` | string | Prompt použitý k vygenerování výstupu. |
| `seed` | integer | Hodnota seedu použitá při generování. |

## Related models

- [LTX Video-0.9.7 13B Distilled · Image to Video](https://doitong.com/developers/models/ltx-video-13b-distilled/image-to-video.md) (`ltx-video-13b-distilled/image-to-video`): from $0.04 / second of output video
- [LTX Video-0.9.7 13B Distilled · Extend](https://doitong.com/developers/models/ltx-video-13b-distilled/extend.md) (`ltx-video-13b-distilled/extend`): $0.04 / video
- [LTX Video-0.9.7 13B Distilled · Multiconditioning](https://doitong.com/developers/models/ltx-video-13b-distilled/multiconditioning.md) (`ltx-video-13b-distilled/multiconditioning`): from $0.04 / second of output video
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second

## Links

- HTML page: https://doitong.com/developers/models/ltx-video-13b-distilled
- 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=ltx-video-13b-distilled
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/ltx-video-13b-distilled