# LTX Video-0.9.7 13B Distilled · Multiconditioning API

> Video-til-video med bilde- og videokondisjonering, LoRA-støtte og to-passers forbedring med valgfri detaljrunde

Genererer en video fra en obligatorisk `prompt`, styrt av kondisjoneringsinndata i `images` og `videos`. Egendefinerte LoRA-er kan sendes i `loras`. Resultatet er i 480p eller 720p, med `num_frames` fra 9 til 1441 og `frame_rate` fra 1 til 60. Separate stegtall for første og andre passering, en valgfri detaljrunde og fargeinnstillinger som `temporal_adain_factor` gjør det mulig å finjustere resultatet.

- 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/no/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 |  |  | Tekstinstruksjoner som veileder genereringen. |
| `negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | Negative tekstinstruksjoner for generering. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | LoRA-vekter brukt under genereringen. |
| `loras[].path` |  | string | yes |  |  | Plassering for LoRA-vektene, oppgitt som en URL eller bane. |
| `loras[].weight_name` |  | string \| null | no |  |  | Navn på LoRA-vekten for valg mellom flere vekter i et HuggingFace-repositorium; kreves bare for repositorier med flere vekter. Denne innstillingen har ingen effekt med mindre `path` identifiserer et HuggingFace-repositorium. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Multiplikator som skalerer LoRA-vekten når den lastes inn. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | Oppløsning for videoen i utdataene. |
| `aspect_ratio` |  | enum (string) | no | `auto` | `9:16`, `1:1`, `16:9`, `auto` | Videoens størrelsesforhold. |
| `seed` |  | integer \| null | no |  |  | Startverdi som styrer tilfeldigheten under generering. |
| `num_frames` |  | integer | no | `121` | 9 – 1,441 | Totalt antall bilder i videoen. |
| `first_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Antall inferenstrinn for første gjennomgang. |
| `second_pass_num_inference_steps` |  | integer | no | `8` | 2 – 12 | Antall inferenstrinn for andre gjennomgang. |
| `second_pass_skip_initial_steps` |  | integer | no | `5` | 1 – 11 | Opprinnelig antall inferenstrinn som utelates under andre gjennomgang, slik at denne gjennomgangen fokuserer mer på fine detaljer enn på omfattende endringer. |
| `frame_rate` |  | integer | no | `24` | 1 – 60 | Bildehastighet for videoen. |
| `expand_prompt` |  | boolean | no | `false` |  | Promptutvidelse gjennom en språkmodell. |
| `reverse_video` |  | boolean | no | `false` |  | Reversering av videoens avspillingsrekkefølge. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Bryter for sikkerhetskontroll der av-innstillingen bare respekteres for autoriserte kontoer. Alle forespørsler uten denne autoriseringen gjennomgår sikkerhetskontroller. |
| `enable_detail_pass` |  | boolean | no | `false` |  | Valgfri ekstra forbedringsgjennomgang som forbedrer videodetaljer når den aktiveres. |
| `temporal_adain_factor` |  | number | no | `0.5` | 0 – 1 | Styrke for adaptiv instansnormalisering (AdaIN), som balanserer fargekonsistens ved høyere innstillinger mot større fargevariasjon ved lavere innstillinger. Den brukes på genererte segmenter unntatt det første og normaliserer fargefordelingen gjennom hele videoen for å motvirke en gradvis økning i metning eller kontrast. |
| `tone_map_compression_ratio` |  | number | no | `0` | 0 – 1 | Nivå for tonekartleggingskomprimering, fra ingen komprimering ved 0.0 til maksimal komprimering ved 1.0. Slik komprimering av videoens dynamikkområde forbedrer den visuelle kvaliteten. |
| `constant_rate_factor` |  | integer | no | `29` | 0 – 51 | Konstant rate-faktor (CRF) brukt for inndatakomprimering, som kan forbedre bevegelseskvaliteten ved å bringe det leverte mediet nærmere modellens treningsdata. |
| `images` |  | array of object {image_url, start_frame_num, strength} | no | `[]` |  | Betingelsesbilder levert via URL. |
| `images[].image_url` |  | string (image URL) | yes |  |  | Betingelsesbilde levert via URL. |
| `images[].start_frame_num` |  | integer | no | `0` | 0 – 1,440 | Startposisjon for bilde-betingelsen, angitt med et bildenummer delelig med 8. |
| `images[].strength` |  | number | no | `1` | 0 – 1 | Betingelsesintensitet: 0.0 deaktiverer betingelsen, mens 1.0 bruker den fullt ut. |
| `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 | `[]` |  | Videoer levert for betingelse. |
| `videos[].video_url` |  | string (video URL) | yes |  |  | Betingelsesvideo levert via URL. |
| `videos[].conditioning_type` |  | enum (string) \| null | no | `rgb` | `rgb`, `depth`, `pose`, `canny` | Kategori for videobetingelse, brukt til å velge forbehandlingsrørledningen når forbehandling er aktivert, og til å bruke LoRA-vekter i kontekst riktig. |
| `videos[].preprocess` |  | boolean | no | `false` |  | Aktiverer forbehandling for å samsvare med videoens betingelsestype. For RGB-betingelse gjør aktivering ingen endringer. |
| `videos[].start_frame_num` |  | integer | no | `0` | 0 – 1,440 | Startposisjon for betingelsen i videoen, angitt som et bilde nummerert delelig med 8. |
| `videos[].strength` |  | number | no | `1` | 0 – 1 | Betingelsesintensitet: 0.0 deaktiverer betingelsen, mens 1.0 bruker den fullt ut. |
| `videos[].limit_num_frames` |  | boolean | no | `false` |  | Bryter for videobildegrense: når den aktiveres, blir `max_num_frames` grensen for bilder hentet fra videoen. |
| `videos[].max_num_frames` |  | integer | no | `1441` | 1 – 1,441 | Grense for antall videobilder som brukes, der None velger hele videoen i stedet for et begrenset antall bilder. |
| `videos[].resample_fps` |  | boolean | no | `false` |  | Bryter for konvertering av videobildehastighet: når den aktiveres, prøves videoen på nytt med hastigheten angitt av `target_fps`. |
| `videos[].target_fps` |  | integer | no | `24` | 1 – 60 | Bildehastighet for omprøving i FPS, bare relevant når `resample_fps` er aktivert. |
| `videos[].reverse_video` |  | boolean | no | `false` |  | Reversering av videorekkefølgen for oppgaver som krever at betingelsen følger bildene baklengs. |

## 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} | Videofil produsert av genereringen. |
| `prompt` | string | Prompten som ble brukt til å generere utdataene. |
| `seed` | integer | Seed-verdi brukt under genereringen. |

## 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