# LTX Video-0.9.7 13B Distilled API

> پرانے 0.9.7 distilled 13B ماڈل کے ساتھ متن سے ویڈیو، LoRA اور طویل فریم تعداد کی معاونت کے ساتھ

لازمی `prompt` کے ذریعے 0.9.7 ڈسٹلڈ ماڈل استعمال کرتے ہوئے ویڈیو تخلیق کرتا ہے۔ ریزولوشن 480p یا 720p، نسبتِ ابعاد 9:16، 1:1 یا 16:9، اور `num_frames` 1 سے 60 fps پر 9 سے 1441 تک ہو سکتا ہے۔ دونوں سیمپلنگ پاسز میں سے ہر ایک 2 سے 12 مراحل لیتا ہے۔ اختیاری `loras`، اضافی تفصیلی پاس اور پرامپٹ کی توسیع دستیاب ہیں۔

- 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/ur/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 |  |  | تخلیق کی رہنمائی کرنے والی text instructions۔ |
| `negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | تخلیق کے لیے منفی text instructions۔ |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | تخلیق کے دوران لاگو ہونے والے LoRA weights۔ |
| `loras[].path` |  | string | yes |  |  | LoRA weights کا مقام، URL یا path کے طور پر دیا جاتا ہے۔ |
| `loras[].weight_name` |  | string \| null | no |  |  | HuggingFace repository میں متعدد وزنوں کے درمیان انتخاب کے لیے LoRA وزن کا نام؛ یہ صرف متعدد وزنوں والی repositories کے لیے درکار ہے۔ اس ترتیب کا کوئی اثر نہیں جب تک `path` کسی HuggingFace repository کی شناخت نہ کرے۔ |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | LoRA weight کے load ہونے پر اسے scale کرنے والا multiplier۔ |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | آؤٹ پٹ ویڈیو کا ریزولوشن۔ |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `9:16`, `1:1`, `16:9` | نتیجہ خیز ویڈیو کا aspect ratio۔ |
| `seed` |  | integer \| null | no |  |  | تخلیق کے دوران randomness کو کنٹرول کرنے والا seed۔ |
| `num_frames` |  | integer | no | `121` | 9 – 1,441 | ویڈیو کی کل فریم count۔ |
| `first_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | پہلے pass کے inference steps کی count۔ |
| `second_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | دوسرے pass کے inference steps کی count۔ |
| `second_pass_skip_initial_steps` |  | integer | no | `5` | 1 – 11 | دوسرے pass کے دوران چھوڑے جانے والے ابتدائی inference-step count، جس سے یہ pass بڑی تبدیلیوں کے بجائے fine-detail کام کی طرف منتقل ہوتا ہے۔ |
| `frame_rate` |  | integer | no | `24` | 1 – 60 | ویڈیو کا فریم rate۔ |
| `expand_prompt` |  | boolean | no | `false` |  | Language ماڈل کے ذریعے پرامپٹ expansion۔ |
| `reverse_video` |  | boolean | no | `false` |  | ویڈیو کے playback order کو الٹنا۔ |
| `enable_safety_checker` |  | boolean | no | `true` |  | حفاظتی جانچ کا سوئچ؛ بند ترتیب صرف مجاز اکاؤنٹس کے لیے قابلِ قبول ہے۔ ایسی اجازت کے بغیر تمام درخواستوں کی حفاظتی جانچ ہوتی ہے۔ |
| `enable_detail_pass` |  | boolean | no | `false` |  | فعال ہونے پر ویڈیو detail بہتر کرنے والا اختیاری دوسرا refinement pass۔ |
| `temporal_adain_factor` |  | number | no | `0.5` | 0 – 1 | Adaptive instance normalization (AdaIN) strength، زیادہ سیٹنگز پر color consistency اور کم سیٹنگز پر زیادہ color variation کے درمیان توازن قائم کرتی ہے۔ یہ پہلے کے علاوہ تخلیق شدہ chunks پر کام کرتی ہے اور پوری ویڈیو میں color distributions normalize کر کے saturation یا contrast میں بتدریج اضافے کو کم کرنے میں مدد دیتی ہے۔ |
| `tone_map_compression_ratio` |  | number | no | `0` | 0 – 1 | Tone-mapping compression level، 0.0 پر compression نہ ہونے سے 1.0 پر maximum compression تک۔ اس طرح ویڈیو کی dynamic range compress کرنے سے visual quality بہتر ہوتی ہے۔ |

## 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} | تخلیق سے تیار کردہ ویڈیو فائل۔ |
| `prompt` | string | آؤٹ پٹ تخلیق کرنے کے لیے استعمال کیا گیا پرامپٹ۔ |
| `seed` | integer | تخلیق کے دوران لاگو ہونے والی سیڈ قدر۔ |

## 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