# LongCat Video Distilled · Text to Video · 720p API

> 720p 蒸馏文生视频，支持细化步数，默认 30 fps

使用蒸馏模型在 720p 下根据文本生成视频。`num_inference_steps` 和 `num_refine_inference_steps` 均接受 2 到 16（默认 12）。`aspect_ratio` 为 16:9、9:16 或 1:1，`num_frames` 为 17 到 961（默认 162），默认 fps 为 30。输出可以是 mp4、webm、ProRes mov 或 GIF。

- Model id: `longcat-video/distilled/text-to-video/720p`
- Made by: Meituan
- Category: Text to Video
- Output: video
- Price per second of your output video: $0.01 / second of output video (cheapest run $0.01 (10 API credits))
- Run: `POST https://api.doitong.ru/v1/run/longcat-video/distilled/text-to-video/720p`
- Quote: `POST https://api.doitong.ru/v1/quote/longcat-video/distilled/text-to-video/720p`
- Docs page: https://doitong.com/zh/developers/models/longcat-video/distilled/text-to-video/720p

## Pricing

Price: **$0.01 / second of output video**. Price per second of your output video: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.054 = 54 API credits (5.4 s output video × $0.01).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.ru/v1/quote/longcat-video/distilled/text-to-video/720p` 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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | 指导视频生成的提示词。 |
| `num_frames` |  | integer | no | `162` | 17 – 961 | 生成输出的帧数。 |
| `num_inference_steps` |  | integer | no | `12` | 2 – 16 | 执行的推理步数。 |
| `num_refine_inference_steps` |  | integer | no | `12` | 2 – 16 | 优化期间执行的推理步数。 |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | 输出视频的宽高比。 |
| `fps` |  | integer | no | `30` | 1 – 60 | 输出视频的帧率。 |
| `seed` |  | integer \| null | no |  |  | 用于初始化随机数生成的种子值。 |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | 控制是否启用提示词扩展。 |
| `enable_safety_checker` |  | boolean | no | `true` |  | 受账户权限限制的安全检查开关：未授权请求必须进行检查，禁用检查需要授权。 |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | 结果视频的输出类型。 |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | 结果视频的质量级别。 |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | 结果视频的写入模式。 |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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.ru/v1/run/longcat-video/distilled/text-to-video/720p?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"
  }'

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

### JavaScript

```javascript
const API = "https://api.doitong.ru/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/longcat-video/distilled/text-to-video/720p?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"
  }),
});
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.ru/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",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/longcat-video/distilled/text-to-video/720p", 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.ru/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": "longcat-video/distilled/text-to-video/720p",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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": "longcat-video/distilled/text-to-video/720p",
  "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": 54,
    "usd": "0.054",
    "charged": 54,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "prompt": "realistic filming style, a person wearing a dark helmet, a deep-colored jacket, blue jeans, and bright yellow shoes rides a skateboard along a winding mountain road. The skateboarder starts in a standing position, then gradually lowers into a crouch, extending one hand to touch the road surface while maintaining a low center of gravity to navigate a sharp curve. After completing the turn, the skateboarder rises back to a standing position and continues gliding forward. The background features lush green hills flanking both sides of the road, with distant snow-capped mountain peaks rising against a clear, bright blue sky. The camera follows closely from behind, smoothly tracking the skateboarder’s movements and capturing the dynamic scenery along the route. The scene is shot in natural daylight, highlighting the vivid outdoor environment and the skateboarder’s fluid actions.",
    "seed": 42,
    "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
    }
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `prompt` | string | 用于生成输出的提示词。 |
| `seed` | integer | 生成期间应用的种子值。 |
| `video` | object {url, content_type, file_name, file_size} | 生成得到的视频文件。 |

## Related models

- [LongCat Video Distilled · Text to Video · 480p](https://doitong.com/developers/models/longcat-video/distilled/text-to-video/480p.md) (`longcat-video/distilled/text-to-video/480p`): $0.005 / second of output video
- [LongCat Video Distilled · Image to Video · 480p](https://doitong.com/developers/models/longcat-video/distilled/image-to-video/480p.md) (`longcat-video/distilled/image-to-video/480p`): $0.005 / second of output video
- [LongCat Video Distilled · Image to Video · 720p](https://doitong.com/developers/models/longcat-video/distilled/image-to-video/720p.md) (`longcat-video/distilled/image-to-video/720p`): $0.01 / second of output video
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second

## Links

- HTML page: https://doitong.com/developers/models/longcat-video/distilled/text-to-video/720p
- 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=longcat-video/distilled/text-to-video/720p
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/longcat-video/distilled/text-to-video/720p