# Kling 2.6 Pro Image-to-Video

> Animate a still photo into a short, cinematic video with fluid motion driven by a text prompt, plus optional native audio.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/kuaishou/kling-video/v2.6/image-to-video`
- **Model ID**: `kuaishou/kling-video/v2.6/image-to-video`
- **Category**: image-to-video
- **Kind**: inference
- **Tags**: kling, kling-video, kuaishou, image-to-video, video-generation

## Pricing

- **false**: $0.07 per output second
- **true**: $0.14 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/kuaishou/kling-video/v2.6/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/kuaishou/kling-video/v2.6/image-to-video/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/kuaishou/kling-video/v2.6/image-to-video/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/kuaishou/kling-video/v2.6/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

- **`prompt`** (`string`, _required_):
  Text description of the motion/action to animate in the video.

- **`duration`** (`duration`, _optional_):
  Length of the generated video in seconds.
  - Default: `"5"`
  - Options: `"5"`, `"10"`

- **`end_image_url`** (`string`, _optional_):
  Optional end/tail frame to interpolate toward.

- **`generate_audio`** (`boolean`, _optional_):
  Whether to generate native audio for the video. Enabling audio raises the per-second rate.
  - Default: `true`

- **`negative_prompt`** (`string`, _optional_):
  Describe content to avoid in the generated video.
  - Default: `"blur, distort, and low quality"`

- **`start_image_url`** (`string`, _required_):
  The start frame the video animates from. Use a JPEG image (min 300x300px, aspect ratio roughly 0.4-2.5).

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "prompt": "The golden eagle spreads its wings fully and lifts off from the cliff, soaring out over the misty mountain peaks as dawn light breaks, slow cinematic tracking shot.",
  "duration": "5",
  "generate_audio": false,
  "negative_prompt": "blur, distort, and low quality",
  "start_image_url": "https://media.modelrunner.ai/slgQXB62f0FAVIboJxvlb.jpeg"
}
```

**Output**

```json
"https://media.modelrunner.ai/AqQkXkjai3UZ95RSJW4h7.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/kuaishou/kling-video/v2.6/image-to-video \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "prompt": "The golden eagle spreads its wings fully and lifts off from the cliff, soaring out over the misty mountain peaks as dawn light breaks, slow cinematic tracking shot.",
  "duration": "5",
  "generate_audio": false,
  "negative_prompt": "blur, distort, and low quality",
  "start_image_url": "https://media.modelrunner.ai/slgQXB62f0FAVIboJxvlb.jpeg"
}')

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("kuaishou/kling-video/v2.6/image-to-video", {
  input: {
  "prompt": "The golden eagle spreads its wings fully and lifts off from the cliff, soaring out over the misty mountain peaks as dawn light breaks, slow cinematic tracking shot.",
  "duration": "5",
  "generate_audio": false,
  "negative_prompt": "blur, distort, and low quality",
  "start_image_url": "https://media.modelrunner.ai/slgQXB62f0FAVIboJxvlb.jpeg"
}
});

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

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "kuaishou/kling-video/v2.6/image-to-video",
        arguments={
  "prompt": "The golden eagle spreads its wings fully and lifts off from the cliff, soaring out over the misty mountain peaks as dawn light breaks, slow cinematic tracking shot.",
  "duration": "5",
  "generate_audio": false,
  "negative_prompt": "blur, distort, and low quality",
  "start_image_url": "https://media.modelrunner.ai/slgQXB62f0FAVIboJxvlb.jpeg"
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/models/kuaishou/kling-video/v2.6/image-to-video)
- [OpenAPI Schema](https://modelrunner.ai/models/kuaishou/kling-video/v2.6/image-to-video/openapi.json)
- [LLM Instructions](https://modelrunner.ai/models/kuaishou/kling-video/v2.6/image-to-video/llms.txt)