# Qwen Wan 2.2 Plus — Image To Video

> Use wan 2.2 plus video for native 4K synthesis and 20s clips. Our API offers wan 2.2 plus video tools for motion control and consistency. Try GPTProto now.

## Overview

- **Endpoint**: `POST https://gptproto.com/api/v3/alibaba/wan-2.2-plus/image-to-video`
- **Result URL**: `GET https://gptproto.com/api/v3/predictions/{result_id}/result` — the submit response also returns the authoritative URL in `data.urls.get`
- **Model ID**: `wan-2.2-plus`
- **Vendor**: Qwen
- **Scene**: `image-to-video`
- **Category**: image-to-video
- **Modalities**: input image → output video
- **Playground**: https://gptproto.com/model/qwen/wan-2.2-plus/image-to-video
- **API documentation**: https://docs.gptproto.com
- **Other scenes of this model**: `text-to-video` — same auth, different endpoint path and input schema

## Authentication

Every request needs a GPTProto API key in the `Authorization` header. Create one at https://gptproto.com/dashboard/api-key, then export it:

```bash
export GPTPROTO_API_KEY="your-api-key"
```

Header: `Authorization: Bearer $GPTPROTO_API_KEY` (plus `Content-Type: application/json` on POST).

## Pricing

Platform price by tier (USD, already includes the GPTProto discount):

- **480p** — $0.09 per run
- **1080p** — $0.45 per run

Price range: $0.09 – $0.45 per generation.

Prices may change. The model page always shows the live price: https://gptproto.com/model/qwen/wan-2.2-plus/image-to-video

## API Information

The API is asynchronous: POST the endpoint to create a prediction, then poll its result URL until `status` is `completed` or `failed`.

### Input Schema

The endpoint accepts the following JSON body parameters:

- **`image`** (`string`, _required_):
  The image for generating the output.

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation.

- **`resolution`** (`enum`, _required_):
  - Default: `480p`
  - Options: 480p, 1080p

- **`duration`** (`enum`, _optional_):
  The duration of the generated media in seconds.
  - Default: `5`
  - Options: 5

- **`seed`** (`range`, _optional_):
  The random seed to use for the generation. -1 means a random seed will be used.
  - Default: `-1`
  - Range: -1–2147483647

- **`enable_prompt_expansion`** (`boolean`, _optional_):
  If set to true, the prompt optimizer will be enabled.
  - Options: true, false

- **`negative_prompt`** (`string`, _optional_):
  The negative prompt for the generation.

**Required Parameters Example**:

```json
{
  "image": "",
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
  "resolution": "480p"
}
```

**Full Example**:

```json
{
  "image": "",
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
  "resolution": "480p",
  "duration": 5,
  "seed": -1,
  "enable_prompt_expansion": false,
  "negative_prompt": ""
}
```

### Output Schema

Both submit and poll return the same envelope:

- **`data.id`** (`string`): Prediction id. Use it as `result_id` when polling for the result.
- **`data.status`** (`string`): One of `created`, `running`, `completed`, `failed`. See Status Values below.
- **`data.outputs`** (`array of string`): Generated files. Empty until `status` is `completed`; then it holds the output URLs (or base64 strings when the model exposes a base64 option).
- **`data.urls.get`** (`string`): Authoritative result URL for this prediction. Prefer it over building the poll URL yourself.
- **`data.error`** (`string | null`): Failure reason when `status` is `failed`, otherwise `null`.
- **`data.executionTime`** (`integer`): Total processing time in milliseconds.
- **`data.timings.inference`** (`integer`): Model inference time in milliseconds.
- **`data.hasNsfwContents`** (`array of boolean`): Per-output moderation flags.
- **`message`** (`string`): `success` on a normal response, otherwise the error message.
- **`code`** (`integer`): Business status code. `200` means the request was accepted.

**Example Response — submit (task accepted)**:

```json
{
  "data": {
    "id": "pred_example_01",
    "model": "wan-2.2-plus",
    "outputs": [],
    "urls": {
      "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result"
    },
    "hasNsfwContents": [],
    "status": "created",
    "createdAt": "2026-01-01T12:00:00Z",
    "executionTime": 0,
    "timings": {
      "inference": 0
    }
  },
  "message": "success",
  "code": 200
}
```

**Example Response — poll (completed)**:

```json
{
  "data": {
    "id": "pred_example_01",
    "model": "wan-2.2-plus",
    "outputs": [
      "https://oss-us.gptproto.com/example/output.mp4"
    ],
    "urls": {
      "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result"
    },
    "status": "completed",
    "error": null,
    "executionTime": 12345,
    "timings": {
      "inference": 12000
    },
    "has_nsfw_contents": [],
    "created_at": "2026-01-01T12:00:00Z"
  },
  "message": "success",
  "code": 200
}
```

### Status Values

- `created` — Task accepted. Use `data.id` as `result_id` for polling.
- `running` — Generation is in progress. Keep polling.
- `completed` — Finished successfully. Generated files are in `data.outputs`.
- `failed` — Generation failed. Read `data.error` for the reason.

## Usage Examples

### 1. Submit a request

```bash
curl --request POST "https://gptproto.com/api/v3/alibaba/wan-2.2-plus/image-to-video" \
  --header "Authorization: Bearer $GPTPROTO_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "image": "",
    "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
    "resolution": "480p",
    "duration": 5,
    "seed": -1,
    "enable_prompt_expansion": false,
    "negative_prompt": ""
  }'
```

```python
import os
import requests

url = "https://gptproto.com/api/v3/alibaba/wan-2.2-plus/image-to-video"
headers = {
  "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}",
  "Content-Type": "application/json"
}
payload = {
  "image": "",
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
  "resolution": "480p",
  "duration": 5,
  "seed": -1,
  "enable_prompt_expansion": False,
  "negative_prompt": ""
}

response = requests.request("POST", url, headers=headers, json=payload)
print(response.json())
```

```typescript
const response = await fetch("https://gptproto.com/api/v3/alibaba/wan-2.2-plus/image-to-video", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    image: "",
    prompt: "A tiny origami fox sailing a teacup across a moonlit puddle",
    resolution: "480p",
    duration: 5,
    seed: -1,
    enable_prompt_expansion: false,
    negative_prompt: "",
  }),
});

const data = await response.json();
console.log(data);
```

### 2. Poll until the task finishes

Replace `YOUR_RESULT_ID` with `data.id` from the submit response (or call `data.urls.get` directly), and keep polling every 1–3 seconds while `status` is `created` or `running`.

```bash
result_id="YOUR_RESULT_ID"

curl --request GET "https://gptproto.com/api/v3/predictions/$result_id/result" \
  --header "Authorization: Bearer $GPTPROTO_API_KEY"
```

```python
import os
import requests

result_id = "YOUR_RESULT_ID"
url = f"https://gptproto.com/api/v3/predictions/{result_id}/result"
headers = {
  "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}"
}
response = requests.request("GET", url, headers=headers)
print(response.json())
```

```typescript
const result_id = "YOUR_RESULT_ID";
const response = await fetch(`https://gptproto.com/api/v3/predictions/${result_id}/result`, {
  method: "GET",
  headers: {
    "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
  },
});

const data = await response.json();
console.log(data);
```

## Example Prompts

- A soldier sprints desperately through a destroyed urban battlefield, with flames and explosions erupting behind him, scattering debris in all directions. His expression is resolute, his eyes sharp and intense. In slow motion, chunks of rubble and shrapnel whip past him. The camer…
- A mountaineer reaches the summit of a snowy peak. They take a deep breath of the thin air, a look of awe and accomplishment washing over their face. Fierce winds whip at their jacket and nearby prayer flags, as clouds rush past below. Arc shot moving from behind to a close-up on…
- A person is deeply engrossed in a book in a cozy study. The wall behind them begins to ripple like water, slowly transforming into a swirling galaxy of stars and nebulae that reflects the fantasy world of the book. The light from the galaxy gently illuminates the side of their fa…

## HTTP Status Codes

- `400` — malformed body, a parameter or value this model does not accept, or input blocked by the provider's content moderation
- `401` — missing or invalid API key
- `403` — insufficient credits
- `413` — request body too large
- `429` — rate limited; retry with backoff
- `500` — An internal server error occurred
- `502` — An internal server error occurred
- `504` — Gateway timeout — upstream service did not respond in time; retry later

## Additional Resources

- [Model playground](https://gptproto.com/model/qwen/wan-2.2-plus/image-to-video)
- [API documentation](https://docs.gptproto.com)
- [All models](https://gptproto.com/model)
- [API keys](https://gptproto.com/dashboard/api-key)
- [Platform overview for LLMs](https://gptproto.com/llm-full.txt)
- Any other model: `https://gptproto.com/model/{vendor}/{model}/{scene}/llms.txt`