# Topaz Image Upscale API

> Topaz Labs' בילד־ופּסקיילער מיט פּנים־רעקאָווערי, נויז־רעדוקציע און שאַרפּענינג, ביז 4x.

פֿאַרגרעסערט אַ פֿאָטאָ אָדער רענדער ביז פֿיר מאָל מיט Topaz מאָדעלן צוגעפּאַסט פֿאַר פֿאַרשידענע מקורים: נאָרמאַלע פֿאָטאָס, הויכע פֿידעליטעט, נידעריק־רעזאָלוציע־מקורים, CGI, טעקסט און פּנימער. אָפּציאָנאַלע פּנים־פֿאַרבעסערונג, דענאָיזינג, שאַרפֿונג און קאָמפּרעסיע־פֿאַרריכטונג; JPEG אָדער PNG רעזולטאַט.

- Model id: `topaz/upscale/image/precision`
- Made by: Topaz Labs
- Category: Upscale
- Output: image
- Price per 24 megapixels of your output image: $0.08 / 24 megapixels of output image (cheapest run $0.08 (80 API credits))
- Run: `POST https://api.doitong.ru/v1/run/topaz/upscale/image/precision`
- Quote: `POST https://api.doitong.ru/v1/quote/topaz/upscale/image/precision`
- Docs page: https://doitong.com/yi/developers/models/topaz/upscale/image/precision

## Pricing

Price: **$0.08 / 24 megapixels of output image**. Price per 24 megapixels of your output image: 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 $0.08 = 80 API credits (1 × 24 MP output image × $0.08).

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/topaz/upscale/image/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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  | ≥ 1 characters | URL פֿון דעם מקור־בילד פֿאַר אַפּסקעילינג. |
| `model` |  | enum (string) | no | `Standard V2` | `Standard V2`, `High Fidelity V3`, `High Fidelity V2`, `Low Resolution V2`, `CGI`, `Text Refine`, `Faces` | אויסקלײַב פֿון גענויעם אַפּסקעילינג־מאָדעל: Faces ניצט Face Recovery 3 פֿאַר פּנים־רעקאָנסטרוקציע, Text Refine האַלט שאַרפֿן טעקסט און פֿאָרמען, און CGI פּאַסט פֿאַר קונסטווערק און רענדערירטע גראַפֿיק. פֿאַר פֿאָטאָגראַפֿיעס דעקט Standard V2 רובֿ באַניצונגען; High Fidelity V3 און High Fidelity V2 האַלטן פּראָפֿעסיאָנעל געפֿילמטן דעטאַל, און Low Resolution V2 בויט איבער קאָמפּרימירטע קוואַלן. |
| `upscale_factor` |  | number | no | `2` | 1 – 4 | מולטיפּליקאַטאָר פֿאַר בילד־פֿאַרגרעסערונג; למשל, 2.0 מאַכט ביידע דימענסיעס טאָפּלט אַזוי גרויס. |
| `crop_to_fill` |  | boolean | no | `false` |  |  |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | פֿאָרמאַט גענוצט פֿאַר דעם אַפּסקעילטן בילד. |
| `subject_detection` |  | enum (string) | no | `All` | `All`, `Foreground`, `Background` | טעמע־דערקענונג־באַשטעטיק גענוצט בעת בילד־פֿאַרבעסערונג. |
| `face_enhancement` |  | boolean | no | `true` |  | פֿאַרבעסערונג־שאַלטער פֿאַרן פּנים אין בילד. |
| `face_enhancement_creativity` |  | number | no | `0` | 0 – 1 | קרעאַטיוויטעט־קאָנטראָל פֿאַר פּנים־פֿאַרבעסערונג, אַקטיוו נאָר ווען פּנים־פֿאַרבעסערונג איז אַקטיוו: שטעל 1.0 פֿאַר מאַקסימום קרעאַטיוויטעט אָדער 0.0 פֿאַר קיין שום. |
| `face_enhancement_strength` |  | number | no | `0.8` | 0 – 1 | שטאַרקייט־קאָנטראָל פֿאַר פּנים־פֿאַרבעסערונג, אַקטיוו נאָר ווען פּנים־פֿאַרבעסערונג איז אַקטיוו: שטעל 1.0 פֿאַר מאַקסימום פֿאַרבעסערונג אָדער 0.0 פֿאַר קיין שום. |
| `sharpen` |  | number \| null | no |  | 0 – 1 | שאַרפּענינג־אינטענסיטעט פֿון 0.0 ביז 1.0, מיט אַ מאָדעל־אָפּהענגיקן סטאַנדאַרט. |
| `denoise` |  | number \| null | no |  | 0 – 1 | דע־נויזינג־אינטענסיטעט פֿון 0.0 ביז 1.0, מיט אַ מאָדעל־אָפּהענגיקן סטאַנדאַרט. |
| `fix_compression` |  | number \| null | no |  | 0 – 1 | אינטענסיטעט פֿון קאָמפּרעסיע־אַרטיפאַקט־באַזײַטיקונג פֿון 0.0 ביז 1.0; נישט בנימצא מיט CGI. |
| `strength` |  | number \| null | no |  | 0.01 – 1 | פֿאַרבעסערונג־אינטענסיטעט פֿון 0.01 ביז 1.0, געשטיצט נאָר דורך Text Refine. |

File parameters (`image`) 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
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "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.ru/v1/run/topaz/upscale/image/precision?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "upscale_factor": 2
  }'

# 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/topaz/upscale/image/precision?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/image/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.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": "topaz/upscale/image/precision",
      "input": {
        "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "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/image/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": 80,
    "usd": "0.08",
    "charged": 80,
    "refunded": 0
  },
  "input": {
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "upscale_factor": 2
  },
  "output": {
    "image": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "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 |
|---|---|---|
| `image` | object {url, content_type, file_name, file_size} | בילד געשאַפֿן דורך פֿאַרגרעסערונג. |

## Related models

- [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
- [Topaz Video Upscale](https://doitong.com/developers/models/topaz/upscale/video/precision.md) (`topaz/upscale/video/precision`): from $0.00667 / second of input video
- [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
- [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/image/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/image/precision
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/topaz/upscale/image/precision