# Topaz Video Upscale API

> Topaz Labs videoförstorare och restaureringsverktyg, upp till 4x med valfri bildfrekvenskonvertering.

Skalar upp och återställer video med Topaz modeller Proteus, Iris, Dione, Artemis, Gaia, Rhea och Theia, från äldre DV- och TV-material till animering. Kontroller för detaljåterställning, brus, glorior, komprimering och kornighet samt en valfri målbilderate från 16 till 60 fps.

- Model id: `topaz/upscale/video/precision`
- Made by: Topaz Labs
- Category: Upscale
- Output: video
- Price per second of your input video: from $0.00667 / second of input video (cheapest run $0.10 (100 API credits))
- Run: `POST https://api.doitong.com/v1/run/topaz/upscale/video/precision`
- Quote: `POST https://api.doitong.com/v1/quote/topaz/upscale/video/precision`
- Docs page: https://doitong.com/sv/developers/models/topaz/upscale/video/precision

## Pricing

Price: **from $0.00667 / 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:

- 720p: $0.00667 / second of input video
- 1080p: $0.0133 / second of input video
- 720p, frame rate: $0.0133 / second of input video
- 1080p, frame rate: $0.0267 / second of input video
- 4K: $0.0517 / second of input video
- above 4K: $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 $0.60 = 600 API credits (10 s input video × $0.051667 (4K), 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/upscale/video/precision` 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 till källvideo för uppskalning. |
| `model` |  | enum (string) | no | `Proteus` | `Proteus`, `Proteus Natural`, `Iris`, `Iris Low Quality`, `Dione DV`, `Dione TV`, `Dione Robust`, `Dione Dehalo`, `Dione Robust Dehalo`, `Artemis High Quality`, `Artemis Medium Quality`, `Artemis Low Quality`, `Artemis Strong Halo`, `Artemis Medium Halo`, `Artemis Aliasing & Moire`, `Gaia HQ`, `Gaia CG`, `Gaia 2`, `Rhea`, `Theia Fine Tune Detail`, `Theia Fine Tune Fidelity` | Icke-generativ modell för precisionsförbättring, där Theia ger manuell kontroll över återgivningstrogenhet och detaljrikedom och Rhea maximerar fina detaljer genom en intern 4x-bearbetning. För restaurering kan du använda Artemis för att skärpa och brusreducera försämrat videomaterial, Dione för att avfläta äldre eller sammanflätat material eller Iris för att återställa ansikten. Proteus passar de flesta verkliga videomaterial och Proteus Natural ger ett mjukare alternativ. Gaia förbättrar högkvalitativt videomaterial och datorgrafik, medan Gaia 2 erbjuder 2x-uppskalning för animation. |
| `upscale_factor` |  | number | no | `2` | 1 – 4 | Videoskalningsmultiplikator; värdet 2.0 fördubblar båda bildrutornas dimensioner. |
| `target_fps` |  | integer \| null | no |  | 16 – 60 | Målbildfrekvens för utdata; om källans FPS matchas förblir interpolering inaktiverad, och endast en annan FPS aktiverar den. |
| `compression` |  | number \| null | no |  | 0 – 1 | Styrka för borttagning av komprimeringsartefakter, från 0.0 till 1.0. Modellen bestämmer standardvärdet. |
| `noise` |  | number \| null | no |  | 0 – 1 | Brusreduceringens styrka, från 0.0 till 1.0. Modellen bestämmer standardvärdet. |
| `halo` |  | number \| null | no |  | 0 – 1 | Styrka för halo-reducering, från 0.0 till 1.0. Modellen bestämmer standardvärdet. |
| `grain` |  | number \| null | no |  | 0 – 0.1 | Mängd filmkorn, från 0.0 till 0.1. Standardvärdet beror på modellen. |
| `recover_detail` |  | number \| null | no |  | 0 – 1 | Styrka för återskapning av originaldetaljer, från 0.0 till 1.0. Ett högre värde bevarar mer källdetaljer. |
| `H264_output` |  | boolean | no | `false` |  | Styr om utgående video använder H264-kodning i stället för standardkodningen H265. |

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": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
  "upscale_factor": 2
}
```

## 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/upscale/video/precision?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "upscale_factor": 2
  }'

# 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/upscale/video/precision?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "upscale_factor": 2
  }),
});
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": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "upscale_factor": 2,
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/topaz/upscale/video/precision", 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/upscale/video/precision",
      "input": {
        "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
        "upscale_factor": 2
      },
      "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/upscale/video/precision",
  "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": 600,
    "usd": "0.60",
    "charged": 600,
    "refunded": 0
  },
  "input": {
    "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "upscale_factor": 2
  },
  "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} | Videofil som skapats genom uppskalning. |

## Related models

- [Topaz Upscale Video Creative](https://doitong.com/developers/models/topaz/upscale/video/creative.md) (`topaz/upscale/video/creative`): from $0.30 / second of input video
- [Topaz Upscale Video Generative](https://doitong.com/developers/models/topaz/upscale/video/generative.md) (`topaz/upscale/video/generative`): from $0.06 / second of input 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 Upscale Image Creative](https://doitong.com/developers/models/topaz/upscale/image/creative.md) (`topaz/upscale/image/creative`): $0.08 / 2 megapixels of output image
- [Topaz Upscale Image Generative](https://doitong.com/developers/models/topaz/upscale/image/generative.md) (`topaz/upscale/image/generative`): from $0.01 / megapixel of output image
- [Topaz Upscale Image Transparent](https://doitong.com/developers/models/topaz/upscale/image/transparent.md) (`topaz/upscale/image/transparent`): $0.08 / 24 megapixels of output image
- [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

## Links

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