# LTX-2.3 22B Distilled · Text to Video · LoRA API

> Text-to-video distillato che applica LoRA personalizzate dal campo `loras` obbligatorio

Crea una clip da un `prompt` e da un elenco `loras` obbligatorio. `video_size` offre forme predefinite, `num_frames` va da 9 a 481 e `fps` da 1 a 60. Sono disponibili la generazione audio opzionale, la camera LoRA e una scala LoRA distillata per il secondo passaggio.

- Model id: `ltx-2.3-22b/distilled/text-to-video/lora`
- Made by: Lightricks
- Category: Text to Video
- Output: video
- Price per megapixel of your output video: $0.00141 / megapixel of output video (cheapest run $0.002 (2 API credits))
- Run: `POST https://api.doitong.ru/v1/run/ltx-2.3-22b/distilled/text-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/distilled/text-to-video/lora`
- Docs page: https://doitong.com/it/developers/models/ltx-2.3-22b/distilled/text-to-video/lora

## Pricing

Price: **$0.00141 / megapixel of output video**. Price per megapixel 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 $0.158 = 158 API credits (112 MP output video × $0.001405).

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/ltx-2.3-22b/distilled/text-to-video/lora` 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 |  |  | Prompt usato come base per la generazione del video. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Numero di fotogrammi dell'output generato. |
| `video_size` |  | object {width, height} \| enum (string) | no | `landscape_16_9` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Dimensioni del video generato. |
| `generate_audio` |  | boolean | no | `true` |  | Controlla se il video include audio generato. |
| `use_multiscale` |  | boolean | no | `true` |  | Attiva la generazione multiscala per migliorare coerenza e dettaglio. Con True, un video preliminare più piccolo guida una seconda generazione le cui dimensioni soddisfano o superano quelle richieste. |
| `fps` |  | number | no | `24` | 1 – 60 | Frequenza dei fotogrammi del video di output, misurata in fotogrammi al secondo. |
| `scheduler` |  | enum (string) | no | `ltx2` | `ltx2`, `linear_quadratic`, `beta` | Selezione dello scheduler. |
| `acceleration` |  | enum (string) | no | `none` | `none`, `regular`, `high`, `full` | Livello di accelerazione applicato all'elaborazione. |
| `camera_lora` |  | enum (string) | no | `none` | `dolly_in`, `dolly_out`, `dolly_left`, `dolly_right`, `jib_up`, `jib_down`, `static`, `none` | Selezione della LoRA della fotocamera per controllare il movimento nel video generato con maggiore precisione rispetto ai soli prompt sul movimento della fotocamera. |
| `camera_lora_scale` |  | number | no | `1` | 0 – 1 | Intensità della LoRA della fotocamera per controllare il movimento nel video generato con maggiore precisione rispetto ai soli prompt sul movimento della fotocamera. |
| `negative_prompt` |  | string | no | `news broadcast, 3d animation, computer graphics, pc game, console game, video game, cartoon, childish, watermark, logo, text, on screen text, subtitles, titles, signature, slowmo, static` |  | Prompt negativo usato durante la generazione del video. |
| `seed` |  | integer \| null | no |  |  | Valore seed che inizializza la generazione di numeri casuali. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Controlla se l'espansione del prompt è abilitata. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Controlla se il controllo di sicurezza è abilitato. |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | Tipo di output per il video risultante. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Livello di qualità del video risultante. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Modalità di scrittura del video risultante. |
| `loras` |  | array of object {path, weight_name, scale} | yes |  |  | Selezione della LoRA per la generazione. |
| `loras[].path` |  | string | yes |  |  | Posizione dei pesi LoRA, fornita come URL o ID di un repository HuggingFace nel formato owner/repo. |
| `loras[].weight_name` |  | string \| null | no |  |  | Nome del peso LoRA per selezionare uno tra più pesi in un repository HuggingFace; è richiesto solo per repository che contengono più pesi. Questa impostazione non ha effetto a meno che `path` non identifichi un repository HuggingFace. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Fattore di scala applicato alla LoRA, da 0.0 a 4.0. |
| `distill_lora_second_pass_scale` |  | number | no | `0.5` | 0 – 1 | Controlla il ridimensionamento della LoRA distill per ogni passaggio successivo al primo. |

## Example input

Required parameters only:

```json
{
  "loras": [
    {
      "path": "https://example.com/your-file.safetensors"
    }
  ],
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "loras": [
    {
      "path": "https://example.com/your-file.safetensors"
    }
  ],
  "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/ltx-2.3-22b/distilled/text-to-video/lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "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/ltx-2.3-22b/distilled/text-to-video/lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "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 = {
    "loras": [
        {
            "path": "https://example.com/your-file.safetensors",
        },
    ],
    "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-2.3-22b/distilled/text-to-video/lora", 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": "ltx-2.3-22b/distilled/text-to-video/lora",
      "input": {
        "loras": [
          {
            "path": "https://example.com/your-file.safetensors"
          }
        ],
        "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-2.3-22b/distilled/text-to-video/lora",
  "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": 158,
    "usd": "0.158",
    "charged": 158,
    "refunded": 0
  },
  "input": {
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "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,
      "width": 1024,
      "height": 768,
      "fps": 1.0,
      "duration": 5,
      "num_frames": 1
    },
    "seed": 42,
    "prompt": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain."
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames} | Video prodotto dal modello. |
| `seed` | integer | Valore del seed usato per inizializzare la generazione di numeri casuali. |
| `prompt` | string | Prompt usato per guidare la generazione. |

## Related models

- [LTX-2.3 22B Distilled · Text to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/text-to-video.md) (`ltx-2.3-22b/distilled/text-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Image to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/image-to-video.md) (`ltx-2.3-22b/distilled/image-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Image to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/distilled/image-to-video/lora.md) (`ltx-2.3-22b/distilled/image-to-video/lora`): $0.00141 / megapixel of output video
- [LTX-2.3 22B Distilled · Reference Video to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/reference-video-to-video.md) (`ltx-2.3-22b/distilled/reference-video-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Reference Video to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/distilled/reference-video-to-video/lora.md) (`ltx-2.3-22b/distilled/reference-video-to-video/lora`): $0.00141 / megapixel of output video
- [LTX-2.3 22B Distilled · Video to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/video-to-video.md) (`ltx-2.3-22b/distilled/video-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Video to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/distilled/video-to-video/lora.md) (`ltx-2.3-22b/distilled/video-to-video/lora`): $0.00141 / megapixel of output video
- [LTX-2.3 22B Distilled · Audio to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/audio-to-video.md) (`ltx-2.3-22b/distilled/audio-to-video`): $0.00121 / megapixel of output video

## Links

- HTML page: https://doitong.com/developers/models/ltx-2.3-22b/distilled/text-to-video/lora
- 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-2.3-22b/distilled/text-to-video/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/ltx-2.3-22b/distilled/text-to-video/lora