# Wan v2.2 5B · Text to Video API

> Teksta pārvēršana video ar 5B modeli: 580p vai 720p, 16:9, 9:16 vai 1:1, pēc izvēles kadru interpolācija

Izveido video klipu no teksta `prompt`. Garumu nosaka `num_frames` (17 līdz 161) un `frames_per_second` (4 līdz 60), bet `resolution` ir 580p vai 720p ar malu attiecību 16:9, 9:16 vai 1:1. Var ieslēgt kadru interpolāciju ar film vai rife, kā arī pielāgot izvades kvalitāti un faila rakstīšanas režīmu. Šis ir standarta vadības variants ar līdz 50 inferenču soļiem.

- 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/lv/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 |  |  | Teksta norādes video ģenerēšanai. |
| `negative_prompt` |  | string | no | `` |  | Negatīvā uzvedne, kas tiek lietota video ģenerēšanas laikā. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Kadru skaits ģenerēšanai ar diapazonu 17–161 ieskaitot. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | Ģenerētā video kadru nomaiņas ātrums, pieņemot vērtības no 4 līdz 60; iestatot `adjust_fps_for_interpolation` uz false, šis ātrums tiek saglabāts nemainīgs. Izmantojot interpolāciju un iestatot `adjust_fps_for_interpolation` uz true (noklusējums), reiziniet šo ātrumu ar viens plus interpolēto kadru skaits, lai iegūtu galīgo FPS. Piemēram, 16 FPS ar 1 interpolētu kadru kļūst par 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Sēkla, kas padara ģenerēšanu atkārtojamu. Iestatot None, sēkla tiek izvēlēta nejauši. |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | Izvades video izšķirtspēja: 580p vai 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Izvades video malu attiecība: 16:9 vai 9:16. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Semplešanas soļu skaits; lielāks skaits nodrošina labāku kvalitāti, bet paildzina apstrādi. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Ievades drošības pārbaude pirms apstrādes, ko drīkst atspējot tikai autorizēti konti. Pieprasījumi bez autorizācijas vienmēr tiek pārbaudīti; pretējā gadījumā true iespējo pārbaudi. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Nosaka ģenerētā video drošības pārbaudi; true iespējo pārbaudi pēc ģenerēšanas. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Ļauj lielajam valodas modelim papildināt uzvedni ar detalizētu informāciju. Šī paplašināšana nemaina uzvednes nozīmi. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Klasifikatora brīvās vadības stiprums; palielinoties mērogam, iespējams kvalitātes zudums tiek mainīts pret precīzāku atbilstību uzvednei. |
| `shift` |  | number | no | `5` | 1 – 10 | Video nobīdes iestatījums ar pieļaujamo diapazonu 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Kadru interpolācijas iestatījums: izvēlieties None, lai izlaistu interpolāciju, vai norādiet modeli tās veikšanai. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Ievietojiet 0–4 interpolētus kadrus katrā spraugā starp diviem ģenerētiem kadriem. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Kadru nomaiņas ātruma pielāgošanas slēdzis: false saglabā norādīto FPS, bet true to reizina ar viens plus interpolēto kadru skaitu. Tādējādi 16 FPS kļūst par 32 FPS, ja tiek interpolēts 1 kadrs un pielāgošana ir iespējota. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Izvades video kvalitātes iestatījums, kas, palielinoties vērtībai, maina lielākus failus pret labāku attēlu. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Video rakstīšanas režīms; balanced nodrošina kompromisu starp ātrumu un kvalitāti. Izvēlieties small mazākajiem failiem un lēnākajai rakstīšanai; ātrāka rakstīšana rezultātus atgriež ātrāk, bet izveido lielākus 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} | Ģenerēšanas rezultātā iegūtais video fails. |
| `prompt` | string | Teksta uzvedne, kas izmantota video ģenerēšanai. |
| `seed` | integer | Ģenerēšanas laikā lietotā sēklas vērtība. |

## 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