# LTX Video-0.9.7 13B Distilled API

> Test għal vidjo bil-mudell 13B distillat eqdem 0.9.7, b'appoġġ għal LoRAs u għadd twil ta' frejms

Jiġġenera vidjo minn `prompt` meħtieġ billi juża l-mudell distilled 0.9.7. Ir-riżoluzzjoni hija 480p jew 720p, il-proporzjon huwa 9:16, 1:1 jew 16:9, u `num_frames` jista’ jkun minn 9 sa 1441 b’1 sa 60 fps. Kull wieħed miż-żewġ passi ta’ sampling jieħu minn 2 sa 12-il pass. `loras` fakultattivi, pass addizzjonali tad-dettall u espansjoni tal-prompt huma disponibbli.

- 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/mt/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 |  |  | Istruzzjonijiet testwali li jiggwidaw il-ġenerazzjoni. |
| `negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | Istruzzjonijiet testwali negattivi għall-ġenerazzjoni. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | Piżijiet LoRA applikati waqt il-ġenerazzjoni. |
| `loras[].path` |  | string | yes |  |  | Post tal-piżijiet LoRA, mogħti bħala URL jew mogħdija. |
| `loras[].weight_name` |  | string \| null | no |  |  | Isem tal-piż tal-LoRA għall-għażla bejn piżijiet multipli f'repożitorju HuggingFace; meħtieġ biss għal repożitorji b'piżijiet multipli. Dan is-setting m'għandu l-ebda effett sakemm `path` ma jidentifikax repożitorju HuggingFace. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Multiplikatur li jiskala l-piż LoRA hekk kif jitgħabba. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | Riżoluzzjoni tal-vidjo output. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `9:16`, `1:1`, `16:9` | Ratio tal-aspett għall-vidjo li jirriżulta. |
| `seed` |  | integer \| null | no |  |  | Seed li jikkontrolla l-każwalità waqt il-ġenerazzjoni. |
| `num_frames` |  | integer | no | `121` | 9 – 1,441 | Għadd totali ta' frejms għall-vidjo. |
| `first_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Għadd ta' passi ta' inferenza għall-ewwel pass. |
| `second_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Għadd ta' passi ta' inferenza għat-tieni pass. |
| `second_pass_skip_initial_steps` |  | integer | no | `5` | 1 – 11 | Għadd inizjali ta' passi ta' inferenza li jitħallew barra matul it-tieni pass, u b'hekk dak il-pass jiffoka fuq xogħol ta' dettall finflok bidliet fuq skala kbira. |
| `frame_rate` |  | integer | no | `24` | 1 – 60 | Rata tal-frejms għall-vidjo. |
| `expand_prompt` |  | boolean | no | `false` |  | Espansjoni tal-prompt permezz ta' mudell tal-lingwa. |
| `reverse_video` |  | boolean | no | `false` |  | Treġġigħ lura tal-ordni tal-qari tal-vidjo. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Swiċċ tal-verifika tas-sikurezza li s-setting mitfi tiegħu jiġi rispettat biss għal kontijiet awtorizzati. It-talbiet kollha mingħajr dik l-awtorizzazzjoni jgħaddu minn verifiki tas-sikurezza. |
| `enable_detail_pass` |  | boolean | no | `false` |  | It-tieni pass fakultattiv ta' raffinar li jtejjeb id-dettall tal-vidjo meta jkun attivat. |
| `temporal_adain_factor` |  | number | no | `0.5` | 0 – 1 | Saħħa tan-normalizzazzjoni adattiva tal-istanzi (AdaIN), li tibbilanċja konsistenza akbar tal-kulur f'issettjar għoli ma' varjazzjoni akbar tal-kulur f'issettjar baxx. Taħdem fuq chunks ġġenerati ħlief l-ewwel wieħed, u tinnormalizza d-distribuzzjonijiet tal-kulur matul il-vidjo biex tgħin tikkontrobatti żieda progressiva fis-saturazzjoni jew fil-kuntrast. |
| `tone_map_compression_ratio` |  | number | no | `0` | 0 – 1 | Livell tal-kompressjoni tat-tone mapping, minn ebda kompressjoni f'0.0 sa kompressjoni massima f'1.0. Il-kompressjoni tal-medda dinamika tal-vidjo b'dan il-mod ittejjeb il-kwalità viżiva. |

## 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} | Fajl vidjo prodott mill-ġenerazzjoni. |
| `prompt` | string | Prompt li ntuża biex jiġi ġġenerat l-output. |
| `seed` | integer | Valur ta’ seed applikat waqt il-ġenerazzjoni. |

## 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