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

> Maandishi hadi video yanayotumia LoRA zako kupitia ingizo la lazima la `loras`

Hupokea `prompt` na orodha ya lazima ya `loras` za LoRA maalum. `video_size` hutoa mipangilio ya mraba, picha wima na mlalo, `num_frames` ni 9 hadi 481, na `fps` ni 1 hadi 60. Uundaji wa sauti, camera LoRA na kiwango cha distill LoRA cha awamu ya kwanza vinapatikana pia.

- Model id: `ltx-2.3-22b/text-to-video/lora`
- Made by: Lightricks
- Category: Text to Video
- Output: video
- Price per megapixel of your output video: $0.00181 / megapixel of output video (cheapest run $0.002 (2 API credits))
- Run: `POST https://api.doitong.ru/v1/run/ltx-2.3-22b/text-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/text-to-video/lora`
- Docs page: https://doitong.com/sw/developers/models/ltx-2.3-22b/text-to-video/lora

## Pricing

Price: **$0.00181 / 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 $0.203 = 203 API credits (112 MP output video × $0.001805).

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/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 |  |  | Kidokezo kinachotumika kama msingi wa uzalishaji wa video. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Idadi ya fremu za tokeo lililozalishwa. |
| `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` | Vipimo vya video iliyozalishwa. |
| `generate_audio` |  | boolean | no | `true` |  | Hudhibiti ikiwa video itajumuisha sauti iliyozalishwa. |
| `use_multiscale` |  | boolean | no | `true` |  | Kigeuzi cha uzalishaji wa mizani mingi kwa mshikamano na maelezo bora. Kwa True, video ndogo ya awali huongoza uzalishaji wa pili ambao ukubwa wake unafikia au kuzidi vipimo vilivyoombwa. |
| `fps` |  | number | no | `24` | 1 – 60 | Kasi ya fremu ya video ya tokeo, iliyopimwa kwa fremu kwa sekunde. |
| `num_inference_steps` |  | integer | no | `40` | 8 – 50 | Idadi ya hatua za uelekezaji zilizotekelezwa. |
| `video_cfg_scale` |  | number | no | `3` | 1 – 20 | Mpangilio wa mwongozo wa video: uinue kwa mshikamano na umakini zaidi katika maudhui yaliyozalishwa. Hutumia mwongozo usio na classifier (CFG). |
| `video_stg_scale` |  | number | no | `0` | 0 – 20 | Hudhibiti mshikamano na umakini wa video kupitia kipimo cha Spatiotemporal Guidance (STG); ongeza mpangilio huu ili kuimarisha sifa zote mbili. |
| `video_rescaling_scale` |  | number | no | `0.7` | 0 – 1 | Marekebisho ya kuongeza au kupunguza video kwa kusawazisha mwongozo usio na classifier na mwongozo wa spatiotemporal kama uwiano. |
| `video_modality_scale` |  | number | no | `3` | 0 – 10 | Marekebisho ya modality ya video kwa kusawazisha michango ya video na sauti kama uwiano. |
| `audio_cfg_scale` |  | number | no | `7` | 1 – 20 | Mpangilio wa mwongozo wa sauti: uinue kwa mshikamano na umakini zaidi katika maudhui yaliyozalishwa. Hutumia mwongozo usio na classifier (CFG). |
| `audio_stg_scale` |  | number | no | `0` | 0 – 20 | Hudhibiti mshikamano na umakini wa sauti kupitia kipimo cha Spatiotemporal Guidance (STG); ongeza mpangilio huu ili kuimarisha sifa zote mbili. |
| `audio_rescaling_scale` |  | number | no | `0.7` | 0 – 1 | Marekebisho ya kuongeza au kupunguza sauti kwa kusawazisha mwongozo usio na classifier na mwongozo wa spatiotemporal kama uwiano. |
| `audio_modality_scale` |  | number | no | `3` | 0 – 10 | Marekebisho ya modality ya sauti kwa kusawazisha michango ya video na sauti kama uwiano. |
| `gradient_estimation_gamma` |  | number | no | `2` | 0 – 10 | Mpangilio wa makadirio ya gradient ya kuondoa kelele: 0 huzima makadirio; vinginevyo, thamani hubainisha gamma. |
| `use_restart_sampling` |  | boolean | no | `false` |  | Kigeuzi cha kuanza upya sampuli kwa ubora bora wa video: kukiwasha huongeza kelele kidogo katika kila hatua ya kuondoa kelele. |
| `scheduler` |  | enum (string) | no | `ltx2` | `ltx2`, `linear_quadratic`, `beta` | Uteuzi wa scheduler. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high`, `full` | Kiwango cha kuongeza kasi kinachotumika kwenye uchakataji. |
| `camera_lora` |  | enum (string) | no | `none` | `dolly_in`, `dolly_out`, `dolly_left`, `dolly_right`, `jib_up`, `jib_down`, `static`, `none` | Uteuzi wa Camera LoRA kwa kudhibiti mwendo katika video iliyozalishwa kwa usahihi zaidi kuliko vidokezo vya mwendo wa kamera pekee. |
| `camera_lora_scale` |  | number | no | `1` | 0 – 1 | Nguvu ya Camera LoRA kwa kudhibiti mwendo katika video iliyozalishwa kwa usahihi zaidi kuliko vidokezo vya mwendo wa kamera pekee. |
| `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` |  | Kidokezo hasi kinachotumika wakati wa uzalishaji wa video. |
| `seed` |  | integer \| null | no |  |  | Thamani ya mbegu inayoanzisha uzalishaji wa nambari nasibu. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Hudhibiti ikiwa upanuzi wa kidokezo umewashwa. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Hudhibiti ikiwa ukaguzi wa usalama umewashwa. |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | Aina ya tokeo la video inayotokana. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Kiwango cha ubora wa video inayotokana. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Hali ya kuandika ya video inayotokana. |
| `loras` |  | array of object {path, weight_name, scale} | yes |  |  | Uteuzi wa LoRA kwa uzalishaji. |
| `loras[].path` |  | string | yes |  |  | Mahali pa uzani wa LoRA, palipotolewa kama URL au kitambulisho cha hazina ya HuggingFace katika muundo wa owner/repo. |
| `loras[].weight_name` |  | string \| null | no |  |  | Jina la uzani wa LoRA kwa kuchagua kati ya uzani wengi katika hazina ya HuggingFace; ni hazina zilizo na uzani wengi pekee zinahitaji hii. Mpangilio huu hauna athari isipokuwa `path` itambue hazina ya HuggingFace. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Kipengele cha kuongeza/kupunguza ukubwa kinachotumika kwenye LoRA, kuanzia 0.0 hadi 4.0. |
| `distill_lora_first_pass_scale` |  | number | no | `0.2` | 0 – 1 | Dhibiti kuongeza au kupunguza kwa distill LoRA ya pass ya kwanza, ukitumia 0 kuizima. |
| `distill_lora_second_pass_scale` |  | number | no | `0.5` | 0 – 1 | Dhibiti kuongeza au kupunguza kwa distill LoRA kwa kila pass baada ya ya kwanza. |

## 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/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/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/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/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/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": 203,
    "usd": "0.203",
    "charged": 203,
    "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 iliyozalishwa na modeli. |
| `seed` | integer | Thamani ya seed inayotumika kuanzisha uzalishaji wa nambari nasibu. |
| `prompt` | string | Kidokezo kinachotumika kuongoza uzalishaji. |

## Related models

- [LTX-2.3 22B · Text to Video](https://doitong.com/developers/models/ltx-2.3-22b/text-to-video.md) (`ltx-2.3-22b/text-to-video`): $0.00161 / megapixel of output video
- [LTX-2.3 22B · Image to Video](https://doitong.com/developers/models/ltx-2.3-22b/image-to-video.md) (`ltx-2.3-22b/image-to-video`): $0.00161 / megapixel of output video
- [LTX-2.3 22B · Image to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/image-to-video/lora.md) (`ltx-2.3-22b/image-to-video/lora`): $0.00181 / megapixel of output video
- [LTX 2.3 22B](https://doitong.com/developers/models/ltx-2.3-22b/reference-video-to-video/lora.md) (`ltx-2.3-22b/reference-video-to-video/lora`): $0.00181 / megapixel of output video
- [LTX-2.3 22B · Extend Video](https://doitong.com/developers/models/ltx-2.3-22b/extend-video.md) (`ltx-2.3-22b/extend-video`): $0.00161 / megapixel of output video
- [LTX-2.3 22B · Extend Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/extend-video/lora.md) (`ltx-2.3-22b/extend-video/lora`): $0.00181 / megapixel of output video
- [LTX-2.3 22B · Reference Video to Video](https://doitong.com/developers/models/ltx-2.3-22b/reference-video-to-video.md) (`ltx-2.3-22b/reference-video-to-video`): $0.00161 / megapixel of output video
- [LTX-2.3 22B · Video to Video](https://doitong.com/developers/models/ltx-2.3-22b/video-to-video.md) (`ltx-2.3-22b/video-to-video`): $0.00161 / megapixel of output video

## Links

- HTML page: https://doitong.com/developers/models/ltx-2.3-22b/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/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/text-to-video/lora