# Topaz Denoise Video API

> Denoiser video dengan empat model Nyx, level noise, kompresi, dan halo yang dapat diatur, serta upscale opsional

Membersihkan noise dari video di `video_url`. `model` dapat berupa Nyx, Nyx Fast, Nyx XL, atau Nyx HF. Nilai `noise`, `compression`, dan `halo` opsional (0 hingga 1) menyempurnakan pengurangan noise, sementara `upscale_factor` (1 hingga 4) dapat memperbesar output; 1 mempertahankan resolusi sumber. `H264_output` mengganti kodek H265 bawaan.

- Model id: `topaz/denoise/video`
- Made by: Topaz Labs
- Category: Video to Video
- Output: video
- Price per second of your input video: from $0.00333 / second of input video (cheapest run $0.10 (100 API credits))
- Run: `POST https://api.doitong.com/v1/run/topaz/denoise/video`
- Quote: `POST https://api.doitong.com/v1/quote/topaz/denoise/video`
- Docs page: https://doitong.com/id/developers/models/topaz/denoise/video

## Pricing

Price: **from $0.00333 / second of input video** (the lowest tier; the quote prices your exact input). Price per second of your input 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:

- Nyx Fast, 720p: $0.00333 / second of input video
- 720p: $0.00667 / second of input video
- Nyx Fast, 720p, frame rate: $0.00667 / second of input video
- Nyx Fast, 1080p: $0.00667 / second of input video
- 720p, frame rate: $0.0133 / second of input video
- 1080p: $0.0133 / second of input video
- Nyx Fast, 1080p, frame rate: $0.0133 / second of input video
- Nyx Fast, 4K: $0.0258 / second of input video
- 1080p, frame rate: $0.0267 / second of input video
- Nyx Fast, above 4K: $0.0459 / second of input video
- 4K: $0.0517 / second of input video
- Nyx Fast, 4K, frame rate: $0.0517 / second of input video
- above 4K: $0.0919 / second of input video
- Nyx Fast, above 4K, frame rate: $0.0919 / second of input video
- 4K, frame rate: $0.1033 / second of input video
- above 4K, frame rate: $0.1837 / second of input video

The full example input below costs $0.10 = 100 API credits (10 s input video × $0.006667 (720p), rounded up to the next $0.10).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/topaz/denoise/video` 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 |  |  | URL video sumber untuk penghapusan noise. |
| `model` |  | enum (string) | no | `Nyx` | `Nyx`, `Nyx Fast`, `Nyx XL`, `Nyx HF` | Pemilihan model pengurangan noise: untuk noise ekstrem, gunakan Nyx XL; untuk pengurangan noise presisi yang siap digunakan dalam pipeline tanpa peningkatan resolusi, gunakan Nyx HF. Nyx memprioritaskan kualitas dan retensi tekstur, sedangkan Nyx Fast mengutamakan kecepatan dibanding kualitas untuk pemrosesan volume tinggi. |
| `upscale_factor` |  | number | no | `1` | 1 – 4 | Pengali resolusi opsional bersama pengurangan noise, dengan 1.0 mempertahankan dimensi sumber, bukan meningkatkan resolusi. |
| `noise` |  | number \| null | no |  | 0 – 1 | Kekuatan pengurangan noise, dari 0.0 hingga 1.0. Bawaannya ditentukan oleh model. |
| `compression` |  | number \| null | no |  | 0 – 1 | Kekuatan penghapusan artefak kompresi, dari 0.0 hingga 1.0. Bawaannya ditentukan oleh model. |
| `halo` |  | number \| null | no |  | 0 – 1 | Kekuatan pengurangan halo, dari 0.0 hingga 1.0. Bawaannya ditentukan oleh model. |
| `H264_output` |  | boolean | no | `false` |  | Mengontrol apakah video output menggunakan encoding H264, bukan H265 bawaan. |

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.com/v1/run/topaz/denoise/video?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.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/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/topaz/denoise/video?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.com/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/topaz/denoise/video", 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.com/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": "topaz/denoise/video",
      "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": "topaz/denoise/video",
  "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": 100,
    "usd": "0.10",
    "charged": 100,
    "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
    }
  },
  "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | file video yang dihasilkan melalui peningkatan resolusi. |

## Related models

- [Topaz Denoise Image](https://doitong.com/developers/models/topaz/denoise/image.md) (`topaz/denoise/image`): $0.08 / run of output image
- [Topaz Deblur Video](https://doitong.com/developers/models/topaz/deblur/video.md) (`topaz/deblur/video`): from $0.00667 / second of input video
- [Topaz Interpolate Video](https://doitong.com/developers/models/topaz/interpolate/video.md) (`topaz/interpolate/video`): from $0.001 / frame of output video
- [Topaz Sdr To Hdr Video](https://doitong.com/developers/models/topaz/sdr-to-hdr/video.md) (`topaz/sdr-to-hdr/video`): from $0.2317 / second of input video
- [AMT Interpolation](https://doitong.com/developers/models/amt-interpolation.md) (`amt-interpolation`): $0.000575 / second of processing time
- [AnimateDiff Turbo · Video to Video](https://doitong.com/developers/models/fast-animatediff/turbo/video-to-video.md) (`fast-animatediff/turbo/video-to-video`): $0.00125 / second of processing time
- [AnimateDiff · Video to Video](https://doitong.com/developers/models/fast-animatediff/video-to-video.md) (`fast-animatediff/video-to-video`): $0.00125 / second of processing time
- [Auto-Captioner](https://doitong.com/developers/models/auto-caption.md) (`auto-caption`): $0.10 / video

## Links

- HTML page: https://doitong.com/developers/models/topaz/denoise/video
- 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=topaz/denoise/video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/topaz/denoise/video