# LTX Video-0.9.7 13B Distilled API

> Text-zu-Video mit dem älteren destillierten 0.9.7-13B-Modell, mit LoRA-Unterstützung und langen Frame-Anzahlen

Erzeugt ein Video aus einem erforderlichen `prompt` mit dem destillierten 0.9.7-Modell. Die Auflösung ist 480p oder 720p, das Seitenverhältnis 9:16, 1:1 oder 16:9, und `num_frames` kann bei 1 bis 60 fps zwischen 9 und 1441 liegen. Jeder der beiden Sampling-Durchläufe benötigt 2 bis 12 Schritte. Optionale `loras`, ein zusätzlicher Detaildurchlauf und Prompt-Erweiterung sind verfügbar.

- 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/de/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 |  |  | Textanweisungen zur Steuerung der Generierung. |
| `negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | Negative Textanweisungen für die Generierung. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | Während der Generierung angewendete LoRA-Gewichte. |
| `loras[].path` |  | string | yes |  |  | Speicherort der LoRA-Gewichte, angegeben als URL oder Pfad. |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA-Gewichtsname zur Auswahl aus mehreren Gewichten in einem HuggingFace-Repository; nur Repositorys mit mehreren Gewichten benötigen ihn. Diese Einstellung hat keine Wirkung, sofern `path` kein HuggingFace-Repository bezeichnet. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Multiplikator zur Skalierung des LoRA-Gewichts beim Laden. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | Auflösung des Ausgabevideos. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `9:16`, `1:1`, `16:9` | Seitenverhältnis des resultierenden Videos. |
| `seed` |  | integer \| null | no |  |  | Startwert zur Steuerung der Zufälligkeit während der Generierung. |
| `num_frames` |  | integer | no | `121` | 9 – 1,441 | Gesamtzahl der Frames des Videos. |
| `first_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Anzahl der Inferenzschritte im ersten Durchlauf. |
| `second_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Anzahl der Inferenzschritte im zweiten Durchlauf. |
| `second_pass_skip_initial_steps` |  | integer | no | `5` | 1 – 11 | Anfängliche Anzahl von Inferenzschritten, die im zweiten Durchlauf übersprungen werden; dadurch konzentriert sich dieser stärker auf feine Details statt auf großflächige Änderungen. |
| `frame_rate` |  | integer | no | `24` | 1 – 60 | Frame-Rate des Videos. |
| `expand_prompt` |  | boolean | no | `false` |  | Prompt-Erweiterung durch ein Sprachmodell. |
| `reverse_video` |  | boolean | no | `false` |  | Umkehrung der Wiedergabereihenfolge des Videos. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Schalter für die Sicherheitsprüfung, dessen Deaktivierung nur für autorisierte Konten berücksichtigt wird. Alle Anfragen ohne diese Autorisierung werden Sicherheitsprüfungen unterzogen. |
| `enable_detail_pass` |  | boolean | no | `false` |  | Optionaler zweiter Verfeinerungsdurchlauf, der bei Aktivierung Videodetails verbessert. |
| `temporal_adain_factor` |  | number | no | `0.5` | 0 – 1 | Stärke der adaptiven Instanznormalisierung (AdaIN), die bei höheren Werten Farbkonsistenz und bei niedrigeren Werten stärkere Farbvariation ermöglicht. Sie wird auf generierte Chunks außer dem ersten angewendet und normalisiert die Farbverteilungen im gesamten Video, um einem fortschreitenden Anstieg von Sättigung oder Kontrast entgegenzuwirken. |
| `tone_map_compression_ratio` |  | number | no | `0` | 0 – 1 | Kompressionsstufe des Tonemappings, von keiner Kompression bei 0.0 bis zur maximalen Kompression bei 1.0. Diese Kompression des Dynamikbereichs verbessert die visuelle Qualität des Videos. |

## 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} | Durch die Generierung erzeugte Videodatei. |
| `prompt` | string | Zur Generierung der Ausgabe verwendeter Prompt. |
| `seed` | integer | Während der Generierung angewendeter Seed-Wert. |

## 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