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

> Image-to-video che utilisescha LoRAs persunalisads dal champ `loras` obligatoric per l'animaziun

Animescha `image_url` tenor in `prompt` e pretenda `loras` per l'estil u il cumportament LoRA persunalisà. `end_image_url` è facultativ per definir il davos maletg. `num_frames` è da 9 a 481, cun generaziun d'audio, opziuns da camera LoRA e las configuraziuns usualas da guidance e scheduler.

- Model id: `ltx-2.3-22b/image-to-video/lora`
- Made by: Lightricks
- Category: Image 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/image-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/image-to-video/lora`
- Docs page: https://doitong.com/rm/developers/models/ltx-2.3-22b/image-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 $0.23 = 230 API credits (127 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/image-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

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Prompt utilisà per dirigir la generaziun. |
| `image_url` | `image` | string (image URL) | yes |  |  | URL dal maletg d’origin utilisà per generar il video. |
| `end_image_url` | `end_image` | string (image URL) \| null | no |  |  | URL dal maletg che definescha il frame final dal video. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Dumber da frames per l'output generà. |
| `video_size` |  | object {width, height} \| enum (string) | no | `auto` | `auto`, `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Dimensiuns dal video generà. |
| `generate_audio` |  | boolean | no | `true` |  | Controlla sche il video cuntegna audio generà. |
| `use_multiscale` |  | boolean | no | `true` |  | Interrupziun per la generaziun multiscala per meglier coherenza e detagl. Cun True gida in video preliminar pli pitschen ina segunda generaziun, la quala cuntanscha u surpassa las dimensiuns dumandadas. |
| `fps` |  | number | no | `24` | 1 – 60 | Frame rate dal video d'output, mesirà en frames per secunda. |
| `num_inference_steps` |  | integer | no | `40` | 8 – 50 | Dumber da pass d'inferenza exequids. |
| `video_cfg_scale` |  | number | no | `3` | 1 – 20 | Configuraziun da guida dal video: auzai ella per dapli consistenza e focus en il cuntegn generà. Utilisescha classifier-free guidance (CFG). |
| `video_stg_scale` |  | number | no | `0` | 0 – 20 | Controlla la consistenza e il focus dal video tras la scala Spatiotemporal Guidance (STG); auzai la configuraziun per rinforzar omadus. |
| `video_rescaling_scale` |  | number | no | `0.7` | 0 – 1 | Ajustament da rescalaziun dal video per equilibrar la classifier-free guidance cun la guida spaziotemporala sco ratio. |
| `video_modality_scale` |  | number | no | `3` | 0 – 10 | Ajustament da la modalitad dal video per equilibrar las contribuziuns dal video e da l’audio sco ratio. |
| `audio_cfg_scale` |  | number | no | `7` | 1 – 20 | Configuraziun da guida da l’audio: auzai ella per dapli consistenza e focus en il cuntegn generà. Utilisescha classifier-free guidance (CFG). |
| `audio_stg_scale` |  | number | no | `0` | 0 – 20 | Controlla la consistenza e il focus da l’audio tras la scala Spatiotemporal Guidance (STG); auzai la configuraziun per rinforzar omadus. |
| `audio_rescaling_scale` |  | number | no | `0.7` | 0 – 1 | Ajustament da rescalaziun da l’audio per equilibrar la classifier-free guidance cun la guida spaziotemporala sco ratio. |
| `audio_modality_scale` |  | number | no | `3` | 0 – 10 | Ajustament da la modalitad da l’audio per equilibrar las contribuziuns dal video e da l’audio sco ratio. |
| `gradient_estimation_gamma` |  | number | no | `2` | 0 – 10 | Configuraziun da l’estimaziun dal gradient da denoisaziun: 0 deactivescha l’estimaziun; autramain definescha il valur gamma. |
| `use_restart_sampling` |  | boolean | no | `false` |  | Interrupziun dal sampling da restart per eventualmain meglier qualitad dal video: l’activaziun agiunta in pau canun ad ogni pass da denoisaziun. |
| `scheduler` |  | enum (string) | no | `ltx2` | `ltx2`, `linear_quadratic`, `beta` | Selecziun dal scheduler. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high`, `full` | Nivel d'acceleraziun applitgà a l'elavuraziun. |
| `camera_lora` |  | enum (string) | no | `none` | `dolly_in`, `dolly_out`, `dolly_left`, `dolly_right`, `jib_up`, `jib_down`, `static`, `none` | Selecziun da Camera LoRA per controllar il moviment en il video generà pli precis che mo cun prompts da moviment da camera. |
| `camera_lora_scale` |  | number | no | `1` | 0 – 1 | Furza da Camera LoRA per controllar il moviment en il video generà pli precis che mo cun prompts da moviment da camera. |
| `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 negativ utilisà durant la generaziun dal video. |
| `seed` |  | integer \| null | no |  |  | Valur da seed che inizialisescha la generaziun da nums casuals. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Controlla sche l'expansiun dal prompt è activada. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Controllescha sche la verificaziun da segirezza è activada. |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | Tip d'output dal video resultà. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Nivel da qualitad dal video resultà. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Modus da scriver per il video resultà. |
| `loras` |  | array of object {path, weight_name, scale} | yes |  |  | Selecziun da LoRA per la generaziun. |
| `loras[].path` |  | string | yes |  |  | Lieu dals pais LoRA, inditgà sco URL u ID d’in repositori HuggingFace en il format owner/repo. |
| `loras[].weight_name` |  | string \| null | no |  |  | Num dal pais LoRA per tscherner tranter plirs pais en in repositori HuggingFace; necessari mo per repositoris cun plirs pais. Questa configuraziun n’ha nagin effect, sch’il `path` n’identifitgescha betg in repositori HuggingFace. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Factor da scalaziun applitgà a LoRA, da 0.0 fin 4.0. |
| `distill_lora_first_pass_scale` |  | number | no | `0.2` | 0 – 1 | Controllar la scala da distill LoRA dal prim pass; utilisar 0 per la deactivar. |
| `distill_lora_second_pass_scale` |  | number | no | `0.5` | 0 – 1 | Controllar la scala da distill LoRA per mintga pass suenter l’emprim. |
| `interpolation_direction` |  | enum (string) | no | `forward` | `forward`, `backward` | Direcziun d’interpolaziun per la sequenza da maletgs. 'Forward' va dal maletg inizial vers il maletg final; 'Backward' inverte l’urden. |
| `image_strength` |  | number | no | `1` | 0 – 1 | Furza da l’influenza dal maletg sin la generaziun dal video. |
| `end_image_strength` |  | number | no | `1` | 0 – 1 | Controllar quant che il maletg final influenzescha il video generà. |

File parameters (`image`, `end_image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## 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",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

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",
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## 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/image-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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# 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/image-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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# 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/image-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/image-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",
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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/image-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": 230,
    "usd": "0.23",
    "charged": 230,
    "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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "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": "Continue the scene naturally, maintaining the same style and motion."
  },
  "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 producì dal model. |
| `seed` | integer | Valur da seed utilisà per inizialisar la generaziun da nums casuals. |
| `prompt` | string | Prompt utilisà per dirigir la generaziun. |

## 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 · Text to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/text-to-video/lora.md) (`ltx-2.3-22b/text-to-video/lora`): $0.00181 / 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](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/image-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/image-to-video/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/ltx-2.3-22b/image-to-video/lora