# Wan-2.2 Text-to-Video A14B with LoRAs API

> A14B text-to-video med LoRA-understøttelse og valgfri omvendt afspilning

Opretter en video fra en tekst-`prompt` og anvender LoRA-vægte angivet i `loras`. `reverse_video` afspiller klippet baglæns. `num_frames` går fra 17 til 161, `resolution` er 480p, 580p eller 720p, og billedformatet er 16:9, 9:16 eller 1:1. Film- eller rife-interpolation og to guidance-skalaer er tilgængelige.

- Model id: `wan/v2.2-a14b/text-to-video/lora`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Estimated price per run: from $0.507 / run (cheapest run $0.507 (507 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-a14b/text-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-a14b/text-to-video/lora`
- Docs page: https://doitong.com/da/developers/models/wan/v2.2-a14b/text-to-video/lora

## Pricing

Price: **from $0.507 / run** (the lowest tier; the quote prices your exact input). Estimated from the typical cost of one run. The quote is exactly what the run charges.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `num_frames` > 81 and `resolution` = 480p: base price × 2
- When `num_frames` > 81 and `resolution` = 580p: base price × 2
- When `num_frames` > 81 and `resolution` = 720p: base price × 2

The full example input below costs $0.507 = 507 API credits (1 request × 507 API credits).

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/wan/v2.2-a14b/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 |  |  | Tekstinstruktioner, der styrer videogenerering. |
| `negative_prompt` |  | string | no | `` |  | Negativ prompt anvendt ved generering af en video. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Antal frames til generering med et inklusivt interval på 17–161. |
| `frames_per_second` |  | integer \| null | no | `16` | 4 – 60 | Den genererede videos billedhastighed, der accepterer værdier fra 4 til 60; indstilling af `adjust_fps_for_interpolation` til false bevarer denne hastighed uændret. Ved interpolation og `adjust_fps_for_interpolation` sat til true (standardværdien) ganges denne hastighed med én plus antallet af interpolerede frames for at beregne den endelige FPS. 16 FPS med 1 interpoleret frame bliver f.eks. til 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Seed, der gør genereringen reproducerbar. Indstilling til None vælger en seed tilfældigt. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | Outputvideoens opløsning: 480p, 580p eller 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Outputvideoens størrelsesforhold, enten 16:9 eller 9:16. |
| `num_inference_steps` |  | integer | no | `27` | 2 – 40 | Antal samplingstrin, hvor længere behandlingstid byttes for bedre kvalitet, når antallet øges. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Sikkerhedskontrol af input før behandling, som kun autoriserede konti kan deaktivere. Anmodninger uden autorisation kontrolleres altid; ellers aktiverer true kontrollen. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Styrer sikkerhedskontrollen af den genererede video; true aktiverer en kontrol efter genereringen. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Tillad en stor sprogmodel at berige prompten med detaljer. Denne udvidelse ændrer ikke promptens betydning. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular` | Accelerationsindstilling, hvor 'regular' anbefales. Højere acceleration reducerer kvaliteten for at forkorte genereringstiden. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Styrke for classifier-free guidance, hvor muligt kvalitetstab byttes for tættere promptmatch, når skalaen øges. |
| `guidance_scale_2` |  | number | no | `4` | 1 – 10 | Guidance-skala, der styrer, hvor tæt modellen følger prompten under dens andet trin. |
| `shift` |  | number | no | `5` | 1 – 10 | Indstilling for videoskift med et tilladt interval på 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Indstilling for frame-interpolation: vælg None for at springe interpolation over, eller angiv modellen, der skal udføre den. |
| `num_interpolated_frames` |  | integer | no | `1` | 0 – 4 | Indsæt 0–4 interpolerede frames i hvert mellemrum mellem to genererede frames. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Kontakt for justering af billedhastighed: false bevarer den angivne FPS, mens true skalerer den med én plus antallet af interpolerede frames. Derfor bliver 16 FPS til 32 FPS, når 1 frame interpoleres, og justering er aktiveret. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Indstilling for outputvideoens kvalitet, der bytter større filer for bedre visuel kvalitet, når værdien øges. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Vide skrivefunktion, hvor balanced er et kompromis mellem hastighed og kvalitet. Vælg small for de mindste filer og langsomste skrivning; hurtigere skrivning returnerer resultater tidligere, men opretter større filer. |
| `loras` |  | array of object {path, weight_name, scale, transformer} | no | `[]` |  | LoRA-vægte, der anvendes under inferens. |
| `loras[].path` |  | string | yes |  |  | Placering af LoRA-vægtene, angivet som en URL eller sti. |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA-vægtnavn, kun påkrævet, når et Hugging Face-arkiv indeholder mere end 1 safetensors-fil. Navnet bruges kun, når `path` identificerer et sådant arkiv. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Multiplikator anvendt på LoRA-vægten, før den flettes ind i basismodellen. |
| `loras[].transformer` |  | enum (string) | no | `high` | `high`, `low`, `both` | Transformer-destination for LoRA-vægten. Vælg 'high' til transformeren med høj støj, 'low' til transformeren med lav støj eller 'both' for at indlæse vægten i begge transformere. |
| `reverse_video` |  | boolean | no | `false` |  | Kontakt for omvendt videoafspilning; true vender afspilningen om. |

## 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/wan/v2.2-a14b/text-to-video/lora?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/wan/v2.2-a14b/text-to-video/lora?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/wan/v2.2-a14b/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": "wan/v2.2-a14b/text-to-video/lora",
      "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": "wan/v2.2-a14b/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": 507,
    "usd": "0.507",
    "charged": 507,
    "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 close-up of a young woman smiling gently in the rain, raindrops glistening on her face and eyelashes. The video captures the delicate details of her expression and the water droplets, with soft light reflecting off her skin in the rainy atmosphere.",
    "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 produceret ved generering. |
| `prompt` | string | Tekstprompt, der bruges til at generere videoen. |
| `seed` | integer | Seed-værdi anvendt under generering. |

## Related models

- [Wan v2.2 A14B Text-to-Image A14B with LoRAs](https://doitong.com/developers/models/wan/v2.2-a14b/text-to-image/lora.md) (`wan/v2.2-a14b/text-to-image/lora`): $0.05 / image
- [Wan v2.2 A14B Image-to-Video A14B with LoRAs](https://doitong.com/developers/models/wan/v2.2-a14b/image-to-video/lora.md) (`wan/v2.2-a14b/image-to-video/lora`): from $1.006 / run
- [Wan 3.0 Text to Video](https://doitong.com/developers/models/alibaba/wan-3.0/text-to-video.md) (`alibaba/wan-3.0/text-to-video`): from $0.05 / second
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second

## Links

- HTML page: https://doitong.com/developers/models/wan/v2.2-a14b/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=wan/v2.2-a14b/text-to-video/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan/v2.2-a14b/text-to-video/lora