# LongCat-Video i2v

> LongCat-Video turns a single still image into minutes-long, smooth 480p, 30fps video with stable style, lighting, and identity — fast, consistent, production-ready animation from one frame.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/meituan-longcat/longcat-video-i2v-480p`
- **Model ID**: `meituan-longcat/longcat-video-i2v-480p`
- **Category**: image-to-video
- **Kind**: inference
- **Tags**: image-to-video

## Pricing

- **Price**: $0.02 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/meituan-longcat/longcat-video-i2v-480p` 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/meituan-longcat/longcat-video-i2v-480p/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/meituan-longcat/longcat-video-i2v-480p/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/meituan-longcat/longcat-video-i2v-480p/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

- **`fps`** (`integer`, _optional_):
  Target playback frame rate (frames per second).
  - Default: `15`
  - Range: `1` to `60`

- **`seed`** (`integer`, _optional_):
  Random seed for reproducibility.
  - Default: `0`

- **`prompt`** (`string`, _optional_):
  Optional natural language guidance for motion, style, subject behavior, camera feel, etc.

- **`image_url`** (`string`, _required_):
  The URL of the image to generate a video from.

- **`num_frames`** (`integer`, _optional_):
  Total frame count of the generated video.
  - Default: `150`
  - Range: `17` to `961`

- **`video_quality`** (`video_quality`, _optional_):
  Overall visual fidelity / bitrate preset.
  - Default: `"high"`
  - Options: `"low"`, `"medium"`, `"high"`, `"maximum"`

- **`video_write_mode`** (`video_write_mode`, _optional_):
  Encoding mode: faster generation vs smaller output size.
  - Default: `"balanced"`
  - Options: `"fast"`, `"balanced"`, `"small"`

- **`video_output_type`** (`video_output_type`, _optional_):
  Container + codec for the final rendered video.
  - Default: `"X264 (.mp4)"`
  - Options: `"X264 (.mp4)"`, `"VP9 (.webm)"`, `"PRORES4444 (.mov)"`, `"GIF (.gif)"`

- **`num_inference_steps`** (`integer`, _optional_):
  Number of denoising / refinement steps per frame.
  - Default: `12`
  - Range: `2` to `16`

- **`enable_safety_checker`** (`boolean`, _optional_):
  If true, run safety / compliance filtering on the generated content. Can't be disabled in web UI.
  - Default: `true`

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "fps": 15,
  "seed": 0,
  "prompt": "First-person view from the cockpit of a Formula 1 car. The driver's gloved hands firmly grip the intricate, carbon-fiber steering wheel adorned with numerous colorful buttons and a vibrant digital display showing race data. Beyond the windshield, a sun-drenched racetrack stretches ahead, lined with cheering spectators in the grandstands. Several rival cars are visible in the distance, creating a dynamic sense of competition. The sky above is a clear, brilliant blue, reflecting the exhilarating atmosphere of a high-speed race. high resolution 4k",
  "image_url": "https://media.modelrunner.ai/jFlVHjGejLWLMBV8",
  "num_frames": 150,
  "video_quality": "maximum",
  "video_write_mode": "balanced",
  "video_output_type": "X264 (.mp4)",
  "num_inference_steps": 14,
  "enable_safety_checker": false
}
```

**Output**

```json
"https://media.modelrunner.ai/NulwrKQ7Xj70YdRJm86AU.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/meituan-longcat/longcat-video-i2v-480p \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "fps": 15,
  "seed": 0,
  "prompt": "First-person view from the cockpit of a Formula 1 car. The driver'\''s gloved hands firmly grip the intricate, carbon-fiber steering wheel adorned with numerous colorful buttons and a vibrant digital display showing race data. Beyond the windshield, a sun-drenched racetrack stretches ahead, lined with cheering spectators in the grandstands. Several rival cars are visible in the distance, creating a dynamic sense of competition. The sky above is a clear, brilliant blue, reflecting the exhilarating atmosphere of a high-speed race. high resolution 4k",
  "image_url": "https://media.modelrunner.ai/jFlVHjGejLWLMBV8",
  "num_frames": 150,
  "video_quality": "maximum",
  "video_write_mode": "balanced",
  "video_output_type": "X264 (.mp4)",
  "num_inference_steps": 14,
  "enable_safety_checker": false
}')

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("meituan-longcat/longcat-video-i2v-480p", {
  input: {
  "fps": 15,
  "seed": 0,
  "prompt": "First-person view from the cockpit of a Formula 1 car. The driver's gloved hands firmly grip the intricate, carbon-fiber steering wheel adorned with numerous colorful buttons and a vibrant digital display showing race data. Beyond the windshield, a sun-drenched racetrack stretches ahead, lined with cheering spectators in the grandstands. Several rival cars are visible in the distance, creating a dynamic sense of competition. The sky above is a clear, brilliant blue, reflecting the exhilarating atmosphere of a high-speed race. high resolution 4k",
  "image_url": "https://media.modelrunner.ai/jFlVHjGejLWLMBV8",
  "num_frames": 150,
  "video_quality": "maximum",
  "video_write_mode": "balanced",
  "video_output_type": "X264 (.mp4)",
  "num_inference_steps": 14,
  "enable_safety_checker": false
}
});

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

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "meituan-longcat/longcat-video-i2v-480p",
        arguments={
  "fps": 15,
  "seed": 0,
  "prompt": "First-person view from the cockpit of a Formula 1 car. The driver's gloved hands firmly grip the intricate, carbon-fiber steering wheel adorned with numerous colorful buttons and a vibrant digital display showing race data. Beyond the windshield, a sun-drenched racetrack stretches ahead, lined with cheering spectators in the grandstands. Several rival cars are visible in the distance, creating a dynamic sense of competition. The sky above is a clear, brilliant blue, reflecting the exhilarating atmosphere of a high-speed race. high resolution 4k",
  "image_url": "https://media.modelrunner.ai/jFlVHjGejLWLMBV8",
  "num_frames": 150,
  "video_quality": "maximum",
  "video_write_mode": "balanced",
  "video_output_type": "X264 (.mp4)",
  "num_inference_steps": 14,
  "enable_safety_checker": false
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/models/meituan-longcat/longcat-video-i2v-480p)
- [OpenAPI Schema](https://modelrunner.ai/models/meituan-longcat/longcat-video-i2v-480p/openapi.json)
- [LLM Instructions](https://modelrunner.ai/models/meituan-longcat/longcat-video-i2v-480p/llms.txt)
- [GitHub](https://github.com/meituan-longcat/LongCat-Video)
- [License](https://github.com/meituan-longcat/LongCat-Video/blob/main/LICENSE)
- [Paper](https://arxiv.org/abs/2510.22200)