# Seedance 2.5 Image to Video

> Animate a still photo into a video with synchronized audio — single takes up to 30 seconds long that keep your image's exact shape.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/bytedance/seedance-v2.5/image-to-video`
- **Model ID**: `bytedance/seedance-v2.5/image-to-video`
- **Category**: image-to-video
- **Kind**: inference
- **Tags**: video, image-to-video, video generation, audio, bytedance, seedance, seedance 2.5, 30-second-video

## Pricing

- **Price**: $0.347 per output second

## Request Lifecycle

This model runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps:

1. **Submit** — `POST https://queue.modelrunner.run/bytedance/seedance-v2.5/image-to-video` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the model; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>` (exact key=value matches, AND-ed). The response carries request handles only (no output yet):

```json
{
  "status": "IN_QUEUE",
  "request_id": "<21-char id>",
  "status_url": "https://queue.modelrunner.run/bytedance/seedance-v2.5/image-to-video/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/bytedance/seedance-v2.5/image-to-video/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/bytedance/seedance-v2.5/image-to-video/requests/<request_id>/cancel"
}
```

2. **Poll status** — `GET <status_url>` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field.

3. **Read result** — `GET <response_url>`. Returns the finished request, including the generated `output`:

```json
{ "id": "<request_id>", "status": "COMPLETED", "output": ..., "input": ... }
```

The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow.

### Input Schema

- **`image`** (`string`, _required_):
  Still image used as the first frame of the clip. 300-6000 px on a side, under 30 MB, aspect ratio between 1:2.5 and 2.5:1. JPEG, PNG, WebP, BMP, TIFF, GIF, HEIC and HEIF are accepted. The finished clip keeps this image's shape.

- **`prompt`** (`string`, _required_):
  Describe what should happen from the first frame onwards: the action, the camera move, and the sound you want.

- **`duration`** (`integer`, _optional_):
  Clip length in seconds, from 4 to 30. Leave at -1 (the default) to let the model choose an appropriate whole-second length inside that range. Billing is per second of finished video, so -1 makes the cost of a run variable.
  - Default: `-1`

- **`resolution`** (`resolution`, _optional_):
  Output resolution of the clip. 720p costs more per second of video than 480p.
  - Default: `"720p"`
  - Options: `"480p"`, `"720p"`

- **`aspect_ratio`** (`aspect_ratio`, _optional_):
  Frame shape of the clip. adaptive is the only value this model accepts: the clip always inherits the aspect ratio of the supplied image, so a vertical still produces a vertical clip. Crop the image before you send it if you need a different shape.
  - Default: `"adaptive"`
  - Options: `"adaptive"`

- **`generate_audio`** (`boolean`, _optional_):
  Generate a synchronized soundtrack (dialogue, ambience and sound effects) together with the picture. Set false for a silent clip; the price is the same either way.
  - Default: `true`

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "image": "https://media.modelrunner.ai/W5jjfbTQ6BahmlesNVWhr.jpeg",
  "prompt": "The paper lantern sways on its bamboo pole, its warm reflection rocking across the wet cobbles below, fine rain drifting through the light, mist rolling slowly between the timber eaves, and the small brass chime turning and ringing beside it",
  "duration": 5,
  "resolution": "720p",
  "aspect_ratio": "adaptive",
  "generate_audio": true
}
```

**Output**

```json
"https://media.modelrunner.ai/6m0I6xs8DL2oaJhQoD8x9.mp4"
```
## Usage Examples

### cURL

The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`.

```bash
# 1. Submit the request (returns request handles, not the output)
SUBMIT=$(curl --silent --request POST \
  --url https://queue.modelrunner.run/bytedance/seedance-v2.5/image-to-video \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "image": "https://media.modelrunner.ai/W5jjfbTQ6BahmlesNVWhr.jpeg",
  "prompt": "The paper lantern sways on its bamboo pole, its warm reflection rocking across the wet cobbles below, fine rain drifting through the light, mist rolling slowly between the timber eaves, and the small brass chime turning and ringing beside it",
  "duration": 5,
  "resolution": "720p",
  "aspect_ratio": "adaptive",
  "generate_audio": true
}')

STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url')
RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url')

# 2. Poll until the request leaves the queue / in-progress state
while true; do
  STATUS=$(curl --silent --url "$STATUS_URL" \
    --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status')
  echo "Status: $STATUS"
  case "$STATUS" in
    COMPLETED) break ;;
    FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;;
  esac
  sleep 1
done

# 3. Read the finished request, including the generated output
curl --silent --url "$RESPONSE_URL" \
  --header "Authorization: Key $MODEL_RUNNER_KEY"
```

### JavaScript

```javascript
import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("bytedance/seedance-v2.5/image-to-video", {
  input: {
  "image": "https://media.modelrunner.ai/W5jjfbTQ6BahmlesNVWhr.jpeg",
  "prompt": "The paper lantern sways on its bamboo pole, its warm reflection rocking across the wet cobbles below, fine rain drifting through the light, mist rolling slowly between the timber eaves, and the small brass chime turning and ringing beside it",
  "duration": 5,
  "resolution": "720p",
  "aspect_ratio": "adaptive",
  "generate_audio": true
}
});

console.log(result.data);
```

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "bytedance/seedance-v2.5/image-to-video",
        arguments={
  "image": "https://media.modelrunner.ai/W5jjfbTQ6BahmlesNVWhr.jpeg",
  "prompt": "The paper lantern sways on its bamboo pole, its warm reflection rocking across the wet cobbles below, fine rain drifting through the light, mist rolling slowly between the timber eaves, and the small brass chime turning and ringing beside it",
  "duration": 5,
  "resolution": "720p",
  "aspect_ratio": "adaptive",
  "generate_audio": true
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/models/bytedance/seedance-v2.5/image-to-video)
- [OpenAPI Schema](https://modelrunner.ai/models/bytedance/seedance-v2.5/image-to-video/openapi.json)
- [LLM Instructions](https://modelrunner.ai/models/bytedance/seedance-v2.5/image-to-video/llms.txt)