# Wan v2.2 5B · Text to Video API

> Text-to-video su 5B modeliu: 580p arba 720p, 16:9, 9:16 arba 1:1 ir pasirenkama kadrų interpolacija

Sukuria vaizdo klipą iš tekstinio `prompt`. Trukmę nustato `num_frames` (nuo 17 iki 161) ir `frames_per_second` (nuo 4 iki 60), naudojant `resolution` 580p arba 720p ir 16:9, 9:16 arba 1:1 kraštinių santykius. Galima įjungti film arba rife kadrų interpolaciją, taip pat reguliuoti išvesties kokybę ir failo rašymo režimą. Tai standartinio valdymo variantas su iki 50 išvesties žingsnių.

- Model id: `wan/v2.2-5b/text-to-video`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Price: $0.15 / video (cheapest run $0.15 (150 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-5b/text-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-5b/text-to-video`
- Docs page: https://doitong.com/lt/developers/models/wan/v2.2-5b/text-to-video

## Pricing

Price: **$0.15 / video**. Billed once per generated video.

The full example input below costs $0.15 = 150 API credits (1 video × 150 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/v2.2-5b/text-to-video` 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 |  |  | Tekstinės instrukcijos, valdančios vaizdo įrašo generavimą. |
| `negative_prompt` |  | string | no | `` |  | Generuojant vaizdo įrašą taikomas neigiamas raginys. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Generavimo kadrų skaičius nuo 17 iki 161 imtinai. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | Sugeneruoto vaizdo įrašo kadrų dažnis nuo 4 iki 60; nustačius `adjust_fps_for_interpolation` į false, šis dažnis išlaikomas nepakitęs. Naudojant interpoliaciją ir `adjust_fps_for_interpolation` esant true (numatytoji reikšmė), šį dažnį padauginus iš vieneto ir interpoliuotų kadrų skaičiaus sumos gaunamas galutinis FPS. Pavyzdžiui, 16 FPS ir 1 interpoliuotas kadras tampa 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Generavimą atkurianti pradinė reikšmė. Nustačius None, ji parenkama atsitiktinai. |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | Išvesties vaizdo įrašo raiška: 580p arba 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Išvesties vaizdo įrašo kraštinių santykis: 16:9 arba 9:16. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Diskretizavimo žingsnių skaičius: didėjant skaičiui, ilgesnis apdorojimas suteikia geresnę kokybę. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Įvesties saugos tikrinimas prieš apdorojimą, kurį išjungti gali tik įgaliotos paskyros. Neįgaliotos užklausos visada tikrinamos; kitu atveju true įjungia tikrinimą. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Valdo sugeneruoto vaizdo įrašo saugos tikrinimą; true įjungia patikrą po generavimo. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Leidžia dideliam kalbos modeliui papildyti raginį detalėmis. Įjungus šį išplėtimą raginio reikšmė nesikeičia. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Klasifikatoriaus nenaudojančio valdymo stiprumas; didėjant masteliui galima kokybės praradimo rizika keičiama į glaudesnį atitikimą ragin iui. |
| `shift` |  | number | no | `5` | 1 – 10 | Vaizdo įrašo poslinkio nustatymas, leidžiamas intervalas 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Kadrų interpoliacijos nustatymas: pasirinkite None, kad interpoliacija nebūtų atliekama, arba nurodykite ją atliekantį modelį. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Į kiekvieną tarpą tarp dviejų sugeneruotų kadrų įterpkite nuo 0 iki 4 interpoliuotų kadrų. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Kadrų dažnio koregavimo jungiklis: false išlaiko pateiktą FPS, o true padaugina jį iš vieneto ir interpoliuotų kadrų skaičiaus sumos. Taigi, interpoliavus 1 kadrą, 16 FPS tampa 32 FPS, jei koregavimas įjungtas. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Išvesties vaizdo įrašo kokybės nustatymas: didesnė reikšmė sukuria didesnius failus, bet pagerina vaizdą. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Vaizdo įrašo rašymo režimas: balanced suderina spartą ir kokybę. Pasirinkite small mažiausiems failams ir lėčiausiam rašymui; spartesnis rašymas rezultatus pateikia anksčiau, bet sukuria didesnius failus. |

## 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/v2.2-5b/text-to-video?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/v2.2-5b/text-to-video?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/v2.2-5b/text-to-video", 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/v2.2-5b/text-to-video",
      "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/v2.2-5b/text-to-video",
  "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": 150,
    "usd": "0.15",
    "charged": 150,
    "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 medium shot establishes a modern, minimalist office setting: clean lines, muted grey walls, and polished wood surfaces. The focus shifts to a close-up on a woman in sharp, navy blue business attire. Her crisp white blouse contrasts with the deep blue of her tailored suit jacket. The subtle texture of the fabric is visible—a fine weave with a slight sheen. Her expression is serious, yet engaging, as she speaks to someone unseen just beyond the frame. Close-up on her eyes, showing the intensity of her gaze and the fine lines around them that hint at experience and focus. Her lips are slightly parted, as if mid-sentence. The light catches the subtle highlights in her auburn hair, meticulously styled. Note the slight catch of light on the silver band of her watch. High resolution 4k",
    "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} | Generuojant sukurtas vaizdo įrašo failas. |
| `prompt` | string | Vaizdo įrašui generuoti naudotas tekstinis raginys. |
| `seed` | integer | Generuojant taikoma pradinė reikšmė. |

## Related models

- [Wan · v2.2 5b · Text to Image](https://doitong.com/developers/models/wan/v2.2-5b/text-to-image.md) (`wan/v2.2-5b/text-to-image`): $0.016 / image
- [Wan · v2.2 5b · Text to Video · Distill](https://doitong.com/developers/models/wan/v2.2-5b/text-to-video/distill.md) (`wan/v2.2-5b/text-to-video/distill`): $0.08 / video
- [Wan v2.2 5B · Image to Video](https://doitong.com/developers/models/wan/v2.2-5b/image-to-video.md) (`wan/v2.2-5b/image-to-video`): $0.15 / video
- [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

## Links

- HTML page: https://doitong.com/developers/models/wan/v2.2-5b/text-to-video
- 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/v2.2-5b/text-to-video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan/v2.2-5b/text-to-video