# LTX Video-0.9.7 13B Distilled · Multiconditioning API

> Video u video s uvjetovanjem slikom i videom, podrškom za LoRA modele i dvoprolaznim poboljšanjem s neobaveznim prolazom detalja

Generira video iz obaveznog `prompt`, vođen uvjetujućim ulazima u `images` i `videos`. Prilagođeni LoRA modeli mogu se proslijediti u `loras`. Izlaz je 480p ili 720p, s `num_frames` od 9 do 1441 i `frame_rate` od 1 do 60. Odvojeni brojevi koraka za prvi i drugi prolaz, neobavezni prolaz detalja i kontrole boja poput `temporal_adain_factor` omogućuju podešavanje rezultata.

- Model id: `ltx-video-13b-distilled/multiconditioning`
- Made by: Lightricks
- Category: Video 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.ru/v1/run/ltx-video-13b-distilled/multiconditioning`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-video-13b-distilled/multiconditioning`
- Docs page: https://doitong.com/hr/developers/models/ltx-video-13b-distilled/multiconditioning

## 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.ru/v1/quote/ltx-video-13b-distilled/multiconditioning` 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 |  |  | Tekstualne upute koje usmjeravaju generiranje. |
| `negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | Negativne tekstualne upute za generiranje. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | LoRA težine primijenjene tijekom generiranja. |
| `loras[].path` |  | string | yes |  |  | Lokacija LoRA težina, navedena kao URL ili putanja. |
| `loras[].weight_name` |  | string \| null | no |  |  | Naziv težine LoRA-e za odabir među višestrukim težinama u repozitoriju HuggingFace; potreban je samo za repozitorije s više težina. Ova postavka nema učinka osim ako `path` označava repozitorij HuggingFace. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Množitelj koji skalira LoRA težinu pri učitavanju. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | Razlučivost izlaznog videozapisa. |
| `aspect_ratio` |  | enum (string) | no | `auto` | `9:16`, `1:1`, `16:9`, `auto` | Omjer slike videozapisa. |
| `seed` |  | integer \| null | no |  |  | Početna vrijednost koja kontrolira slučajnost tijekom generiranja. |
| `num_frames` |  | integer | no | `121` | 9 – 1,441 | Ukupan broj sličica za video. |
| `first_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Broj koraka zaključivanja za prvi prolaz. |
| `second_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Broj koraka zaključivanja za drugi prolaz. |
| `second_pass_skip_initial_steps` |  | integer | no | `5` | 1 – 11 | Početni broj koraka zaključivanja koji se izostavljaju tijekom drugog prolaza, čime se taj prolaz usmjerava na fine detalje umjesto na opsežne promjene. |
| `frame_rate` |  | integer | no | `24` | 1 – 60 | Brzina sličica za video. |
| `expand_prompt` |  | boolean | no | `false` |  | Proširivanje prompta putem jezičnog modela. |
| `reverse_video` |  | boolean | no | `false` |  | Obrnuti redoslijed reprodukcije videa. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Prekidač sigurnosne provjere čija se isključena postavka poštuje samo za ovlaštene račune. Svi zahtjevi bez tog ovlaštenja prolaze sigurnosne provjere. |
| `enable_detail_pass` |  | boolean | no | `false` |  | Neobavezni drugi prolaz poboljšanja koji poboljšava detalje videa kada je omogućen. |
| `temporal_adain_factor` |  | number | no | `0.5` | 0 – 1 | Jačina prilagodljive normalizacije instance (AdaIN), koja pri višim postavkama uravnotežuje dosljednost boja, a pri nižima veću varijaciju boja. Djeluje na generiranim blokovima osim prvog, normalizirajući distribucije boja kroz video kako bi pomogla suzbiti postupno povećanje zasićenosti ili kontrasta. |
| `tone_map_compression_ratio` |  | number | no | `0` | 0 – 1 | Razina kompresije mapiranja tonova, od bez kompresije pri 0.0 do najveće kompresije pri 1.0. Komprimiranje dinamičkog raspona videa na ovaj način poboljšava vizualnu kvalitetu. |
| `constant_rate_factor` |  | integer | no | `29` | 0 – 51 | Faktor konstantne brzine (CRF) koji se upotrebljava za kompresiju ulaza i može poboljšati kvalitetu kretanja približavanjem dostavljenog medija podacima za obuku modela. |
| `images` |  | array of object {image_url, start_frame_num, strength} | no | `[]` |  | Slike za uvjetovanje dostavljene putem URL-a. |
| `images[].image_url` |  | string (image URL) | yes |  |  | Slika za uvjetovanje dostavljena putem URL-a. |
| `images[].start_frame_num` |  | integer | no | `0` | 0 – 1,440 | Početni položaj uvjetovanja slike, naveden pomoću broja sličice djeljivog s 8. |
| `images[].strength` |  | number | no | `1` | 0 – 1 | Intenzitet uvjetovanja: 0.0 onemogućuje uvjetovanje, dok ga 1.0 u potpunosti primjenjuje. |
| `videos` |  | array of object {video_url, conditioning_type, preprocess, start_frame_num, strength, limit_num_frames, max_num_frames, resample_fps, target_fps, reverse_video} | no | `[]` |  | Videozapisi dostavljeni za uvjetovanje. |
| `videos[].video_url` |  | string (video URL) | yes |  |  | Video za uvjetovanje dostavljen putem URL-a. |
| `videos[].conditioning_type` |  | enum (string) \| null | no | `rgb` | `rgb`, `depth`, `pose`, `canny` | Kategorija uvjetovanja videa koja se upotrebljava za odabir cjevovoda pretprocesiranja kada je pretprocesiranje omogućeno i za ispravnu primjenu LoRA težina u kontekstu. |
| `videos[].preprocess` |  | boolean | no | `false` |  | Omogućuje pretprocesiranje radi podudaranja s vrstom uvjetovanja videa. Za RGB uvjetovanje njegovo omogućivanje ne donosi promjene. |
| `videos[].start_frame_num` |  | integer | no | `0` | 0 – 1,440 | Početni položaj uvjetovanja u videu, naveden kao broj sličice djeljiv s 8. |
| `videos[].strength` |  | number | no | `1` | 0 – 1 | Intenzitet uvjetovanja: 0.0 onemogućuje uvjetovanje, dok ga 1.0 u potpunosti primjenjuje. |
| `videos[].limit_num_frames` |  | boolean | no | `false` |  | Prekidač ograničenja sličica videa: njegovim omogućivanjem `max_num_frames` postaje gornja granica broja sličica preuzetih iz videa. |
| `videos[].max_num_frames` |  | integer | no | `1441` | 1 – 1,441 | Ograničenje broja sličica videa za upotrebu, pri čemu None odabire cijeli video umjesto ograničenog broja sličica. |
| `videos[].resample_fps` |  | boolean | no | `false` |  | Prekidač pretvorbe brzine sličica videa: njegovim omogućivanjem video se ponovno uzorkuje brzinom navedenom u `target_fps`. |
| `videos[].target_fps` |  | integer | no | `24` | 1 – 60 | Brzina sličica za ponovno uzorkovanje u FPS-u, primjenjiva samo kada je omogućeno `resample_fps`. |
| `videos[].reverse_video` |  | boolean | no | `false` |  | Obrnuti redoslijed videa za zadatke koji zahtijevaju da uvjetovanje prati sličice unatrag. |

## 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.ru/v1/run/ltx-video-13b-distilled/multiconditioning?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.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-video-13b-distilled/multiconditioning?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.ru/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/multiconditioning", 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-video-13b-distilled/multiconditioning",
      "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/multiconditioning",
  "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 vibrant, abstract composition featuring a person with outstretched arms, rendered in a kaleidoscope of colors against a deep, dark background. The figure is composed of intricate, swirling patterns reminiscent of a mosaic, with hues of orange, yellow, blue, and green that evoke the style of artists such as Wassily Kandinsky or Bridget Riley. The camera zooms into the face striking portrait of a man, reimagined through the lens of old-school video-game graphics. The subject's face is rendered in a kaleidoscope of colors, with bold blues and reds set against a vibrant yellow backdrop. His dark hair is pulled back, framing his profile in a dramatic pose.",
    "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.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} | Video datoteka proizvedena generiranjem. |
| `prompt` | string | Prompt koji je korišten za generiranje izlaza. |
| `seed` | integer | Vrijednost seeda primijenjena tijekom generiranja. |

## Related models

- [LTX Video-0.9.7 13B Distilled](https://doitong.com/developers/models/ltx-video-13b-distilled.md) (`ltx-video-13b-distilled`): from $0.04 / second of output video
- [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 2.3](https://doitong.com/developers/models/ltx-2.3/reframe.md) (`ltx-2.3/reframe`): from $0.10 / second of input 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 Quality · Clean Plate](https://doitong.com/developers/models/ltx-2.3-quality/clean-plate.md) (`ltx-2.3-quality/clean-plate`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Colorization](https://doitong.com/developers/models/ltx-2.3-quality/colorization.md) (`ltx-2.3-quality/colorization`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Cross Eyed](https://doitong.com/developers/models/ltx-2.3-quality/cross-eyed.md) (`ltx-2.3-quality/cross-eyed`): $0.00241 / megapixel of output video

## Links

- HTML page: https://doitong.com/developers/models/ltx-video-13b-distilled/multiconditioning
- 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/multiconditioning
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/ltx-video-13b-distilled/multiconditioning