# Wan v2.2 5B · Text to Video API

> Text-to-video gamit ang 5B modelo: 580p o 720p, 16:9, 9:16 o 1:1, at opsyonal na frame interpolation

Gumagawa ng video clip mula sa teksto `prompt`. Itinatakda ang haba ng `num_frames` (17 hanggang 161) at `frames_per_second` (4 hanggang 60), na may `resolution` na 580p o 720p at aspect ratio na 16:9, 9:16 o 1:1. Maaaring i-enable ang frame interpolation gamit ang film o rife, at maaaring ayusin ang output quality at file write mode. Ito ang standard-guidance variant na may hanggang 50 inference hakbang.

- 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/fil/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 |  |  | Mga text instruction na gumagabay sa pagbuo ng video. |
| `negative_prompt` |  | string | no | `` |  | Negative prompt na inilalapat sa pagbuo ng video. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Bilang ng frame para sa pagbuo, na may inclusive range na 17–161. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | Frame rate ng nabuong video, tumatanggap ng mga value mula 4 hanggang 60; kapag itinakda ang `adjust_fps_for_interpolation` sa false, pinapanatili ang rate na ito nang walang pagbabago. Kapag ginagamit ang interpolation at true ang `adjust_fps_for_interpolation` (ang default nito), i-multiply ang rate na ito sa isa dagdag ang bilang ng interpolated frame upang makuha ang final FPS. Halimbawa, ang 16 FPS na may 1 interpolated frame ay nagiging 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Seed na ginagawang reproducible ang pagbuo. Ang pagtatakda nito sa None ay random na pumipili ng seed. |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | Resolution ng output video, alinman sa 580p o 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Aspect ratio ng output video, alinman sa 16:9 o 9:16. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Bilang ng sampling step, kung saan ipinagpapalit ang mas mahabang oras ng pagproseso para sa mas magandang kalidad habang tumataas ang bilang. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Safety screening ng input bago ang pagproseso, na mga awtorisadong account lamang ang maaaring mag-off. Palaging sini-screen ang mga kahilingang walang authorization; kung hindi, ini-enable ng true ang screening. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Kinokontrol ang safety screening ng nabuong video; ini-enable ng true ang pagsusuri pagkatapos ng pagbuo. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Pahintulutan ang isang large language modelo na pagyamanin ang prompt gamit ang mga detalye. Hindi binabago ng pagpapalawak na ito ang kahulugan ng prompt. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Lakas ng classifier-free guidance, kung saan ipinagpapalit ang posibleng pagbaba ng kalidad para sa mas malapit na pagtutugma sa prompt habang tumataas ang scale. |
| `shift` |  | number | no | `5` | 1 – 10 | Setting ng video shift, na may pinapahintulutang saklaw na 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Setting ng frame interpolation: pumili ng None upang laktawan ang interpolation, o tumukoy ng modelong magsasagawa nito. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Magpasok ng 0–4 interpolated frame sa bawat pagitan ng dalawang nabuong frame. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Toggle para sa adjustment ng frame rate: pinapanatili ng false ang ibinigay na FPS, samantalang mina-multiply ito ng true sa isa dagdag ang bilang ng interpolated frame. Kaya nagiging 32 FPS ang 16 FPS kapag ini-interpolate ang 1 frame at naka-enable ang adjustment. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Setting ng kalidad ng output video na ipinagpapalit ang mas malalaking file para sa mas magandang visual habang itinataas ang setting. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Mode ng pagsusulat ng video, kung saan nagbibigay ang balanced ng kompromiso sa pagitan ng bilis at kalidad. Pumili ng small para sa pinakamaliliit na file at pinakamabagal na pagsusulat; mas mabilis na pagsusulat ang mas maagang nagbabalik ng resulta ngunit lumilikha ng mas malalaking file. |

## 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} | Video file na ginawa sa pagbuo. |
| `prompt` | string | Text prompt na ginamit upang buuin ang video. |
| `seed` | integer | Seed value na inilapat sa pagbuo. |

## 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