# Kandinsky 6.0 VSR API

> 선명하고 깜박임 없는 프레임에 중점을 두고 클립을 2x, 2.25x 또는 4x로 업스케일하는 동영상 초해상도

`upscale_factor`에서 선택한 2, 2.25(기본값) 또는 4 배율로 `video_url`의 클립을 업스케일합니다. 입력은 24 fps로 리샘플링되고 121프레임, 약 5초로 제한됩니다. 2x 및 4x에서는 너비와 높이가 16의 배수여야 합니다. `num_inference_steps`는 2~50(기본값 5)이며, 재현성을 위한 `seed`를 지원합니다.

- Model id: `kandinsky6-vsr`
- Made by: Sber AI
- Category: Upscale
- Output: video
- Price per megapixel of your output video: from $0.00036 / megapixel of output video (cheapest run $0.001 (1 API credit))
- Run: `POST https://api.doitong.ru/v1/run/kandinsky6-vsr`
- Quote: `POST https://api.doitong.ru/v1/quote/kandinsky6-vsr`
- Docs page: https://doitong.com/ko/developers/models/kandinsky6-vsr

## Pricing

Price: **from $0.00036 / megapixel of output video** (the lowest tier; the quote prices your exact input). Price per megapixel 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.

Price by tier:

- base rate: $0.00036 / megapixel of output video
- steps: $0.0036 / megapixel of output video

The full example input below costs $0.204 = 204 API credits (564.5376 MP output video × $0.00036).

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/kandinsky6-vsr` 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

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `video_url` | `video` | string (video URL) | yes |  |  | 업스케일할 동영상입니다. 2 및 4 배율에서는 너비와 높이가 16으로 나누어떨어져야 합니다. 처리 시 클립을 24fps로 리샘플링하고 121 프레임(약 5초)으로 제한합니다. |
| `upscale_factor` |  | enum (number) | no | `2.25` | `2`, `2.25`, `4` | 원본 해상도에 적용하는 전체 배율입니다. 2, 2.25 또는 4입니다. |
| `num_inference_steps` |  | integer | no | `5` | 2 – 50 | 타일별로 적용하는 디노이징 단계 수입니다. |
| `seed` |  | integer \| null | no |  |  | 생성에 사용된 무작위 시드입니다. |
| `enable_safety_checker` |  | boolean | no | `true` |  | 호출자에게 권한이 있으면 false로 설정해 검사를 완화할 수 있습니다. |

File parameters (`video`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

A fuller example:

```json
{
  "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

## 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/kandinsky6-vsr?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }'

# 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/kandinsky6-vsr?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }),
});
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 = {
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/kandinsky6-vsr", 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": "kandinsky6-vsr",
      "input": {
        "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
      },
      "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": "kandinsky6-vsr",
  "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": 204,
    "usd": "0.204",
    "charged": 204,
    "refunded": 0
  },
  "input": {
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  },
  "output": {
    "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
    },
    "seed": 42
  },
  "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 |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | 업스케일링으로 생성된 동영상 파일입니다. |
| `seed` | integer | 생성에 사용된 무작위 시드입니다. |

## Related models

- [Kandinsky 6.0 VSR · Lite](https://doitong.com/developers/models/kandinsky6-vsr/lite.md) (`kandinsky6-vsr/lite`): from $0.00036 / megapixel of output video
- [Topaz Image Upscale](https://doitong.com/developers/models/topaz/upscale/image/precision.md) (`topaz/upscale/image/precision`): $0.08 / 24 megapixels of output image
- [Topaz Video Upscale](https://doitong.com/developers/models/topaz/upscale/video/precision.md) (`topaz/upscale/video/precision`): from $0.00667 / second of input video
- [AuraSR](https://doitong.com/developers/models/aura-sr.md) (`aura-sr`): $0.001111 / second of processing time
- [Bria Increase Resolution](https://doitong.com/developers/models/bria/increase-resolution.md) (`bria/increase-resolution`): $0.04 / image
- [Bytedance Upscaler Upscale Video](https://doitong.com/developers/models/bytedance-upscaler/upscale/video.md) (`bytedance-upscaler/upscale/video`): from $0.0072 / second of input video
- [Chrono Edit Lora Gallery · Upscaler](https://doitong.com/developers/models/chrono-edit-lora-gallery/upscaler.md) (`chrono-edit-lora-gallery/upscaler`): $0.03 / image
- [Clarity Upscaler](https://doitong.com/developers/models/clarity-upscaler.md) (`clarity-upscaler`): $0.03 / megapixel of output image

## Links

- HTML page: https://doitong.com/developers/models/kandinsky6-vsr
- 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=kandinsky6-vsr
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/kandinsky6-vsr