# Wan-2.1 Image-to-Video API

> Wan 2.1 image-to-video, animuojantis vieną pradinį vaizdą pagal tekstinį raginį

Animuoja vieną įvesties vaizdą (`image_url`) pagal `prompt`. Išvestis yra 480p arba 720p, formato santykis – auto, 16:9, 9:16 arba 1:1, o neatitinkantys vaizdai apkerpami iš centro. `num_frames` yra 81–100, dažnis – 5–24 kadrai per sekundę. Valdikliai apima `negative_prompt`, `seed`, `guide_scale`, `shift` ir `acceleration` nustatymą.

- Model id: `wan-i2v`
- Made by: Alibaba
- Category: Image to Video
- Output: video
- Price: from $0.20 / video (cheapest run $0.20 (200 API credits))
- Run: `POST https://api.doitong.com/v1/run/wan-i2v`
- Quote: `POST https://api.doitong.com/v1/quote/wan-i2v`
- Docs page: https://doitong.com/lt/developers/models/wan-i2v

## Pricing

Price: **from $0.20 / video** (the lowest tier; the quote prices your exact input). Billed once per generated video.

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` = 720p: $0.50 (500 API credits) / video
- When `resolution` = 720p: $0.40 (400 API credits) / video
- When `num_frames` > 81: $0.25 (250 API credits) / video

The full example input below costs $0.40 = 400 API credits (1 video × 400 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.com/v1/quote/wan-i2v` 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

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Tekstinės instrukcijos, valdančios vaizdo įrašo generavimą. |
| `negative_prompt` |  | string | no | `bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards` |  | Generuojant vaizdo įrašą taikomas neigiamas raginys. |
| `image_url` | `image` | string (image URL) | yes |  |  | Šaltinio vaizdo URL; pasirinktas kraštinių santykis lemia, ar reikia išankstinio apdorojimo: neatitikimas sukelia dydžio keitimą, po kurio atliekamas centrinis apkirpimas. |
| `num_frames` |  | integer \| null | no | `81` | 81 – 100 | Generavimo kadrų skaičius nuo 81 iki 100 imtinai. |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 24 | Sugeneruoto vaizdo įrašo kadrų dažnis kadrais per sekundę nuo 5 iki 24. |
| `seed` |  | integer \| null | no |  |  | Generavimą atkurianti pradinė reikšmė. Nustačius None, ji parenkama atsitiktinai. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | Išvesties vaizdo įrašo raiška: 480p arba 720p. |
| `num_inference_steps` |  | integer | no | `30` | 2 – 40 | Diskretizavimo žingsnių skaičius: didėjant skaičiui, ilgesnis apdorojimas suteikia geresnę kokybę. |
| `guide_scale` |  | number | no | `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 | Generuojant vaizdo įrašą taikomas poslinkio nustatymas. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Saugos tikrinimo jungiklis, kurio išjungimo nustatymui reikia paskyros autorizacijos. Be šios autorizacijos tikrinama kiekviena užklausa, nepaisant nustatymo; true įjungia tikrintuvą. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Valdo, ar įjungtas raginio išplėtimas. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular` | Spartinimo nustatymas; rekomenduojama reikšmė yra 'regular'. Didesnis spartinimas mažina kokybę, kad sutrumpintų generavimo laiką. |
| `aspect_ratio` |  | enum (string) | no | `auto` | `auto`, `16:9`, `9:16`, `1:1` | Generuojamo vaizdo įrašo proporcijos, automatiškai parenkamos pagal įvesties vaizdą, kai nustatyta 'auto'. |

File parameters (`image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## 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.com/v1/run/wan-i2v?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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/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-i2v?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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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.com/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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/wan-i2v", 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.com/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-i2v",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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-i2v",
  "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": 400,
    "usd": "0.40",
    "charged": 400,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "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
    },
    "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/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. |
| `seed` | integer | Generuojant taikoma pradinė reikšmė. |

## Related models

- [Wan-2.1 Pro Text-to-Video](https://doitong.com/developers/models/wan-pro/text-to-video.md) (`wan-pro/text-to-video`): $0.80 / run
- [Wan-2.1 Text-to-Video](https://doitong.com/developers/models/wan-t2v.md) (`wan-t2v`): from $0.20 / video
- [Wan Effects](https://doitong.com/developers/models/wan-effects.md) (`wan-effects`): $0.35 / video
- [Wan-2.1 First-Last-Frame-to-Video](https://doitong.com/developers/models/wan-flf2v.md) (`wan-flf2v`): from $0.20 / video
- [Wan-2.1 Pro Image-to-Video](https://doitong.com/developers/models/wan-pro/image-to-video.md) (`wan-pro/image-to-video`): $0.80 / video
- [Wan 3.0 Image to Video](https://doitong.com/developers/models/alibaba/wan-3.0/image-to-video.md) (`alibaba/wan-3.0/image-to-video`): from $0.05 / second
- [FLUX 3 Max Image to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/image-to-video.md) (`blackforestlabs/flux-3-max/image-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Image to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/image-to-video.md) (`xai/grok-imagine-video/v1.5/image-to-video`): from $0.082 / second

## Links

- HTML page: https://doitong.com/developers/models/wan-i2v
- 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-i2v
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/wan-i2v