# Topaz Upscale Video Generative API

> Mise à l'échelle vidéo générative avec choix de modèles Starlight, destinée aux séquences compressées ou d'archives

Améliore et augmente la résolution d'une vidéo avec les modèles Starlight fondés sur la diffusion, sélectionnés via `model` : Precise 2.6, HQ, Mini, Sharp ou Fast 2. `upscale_factor` va de 1 à 4, et `target_fps` (16-60) active l'interpolation d'images lorsqu'il diffère de la source. `softness` (1-5) s'applique uniquement à Starlight Precise 2.6. Le codec de sortie est H265, ou H264 sur demande.

- Model id: `topaz/upscale/video/generative`
- Made by: Topaz Labs
- Category: Upscale
- Output: video
- Price per second of your input video: from $0.06 / second of input video (cheapest run $0.10 (100 API credits))
- Run: `POST https://api.doitong.com/v1/run/topaz/upscale/video/generative`
- Quote: `POST https://api.doitong.com/v1/quote/topaz/upscale/video/generative`
- Docs page: https://doitong.com/fr-FR/developers/models/topaz/upscale/video/generative

## Pricing

Price: **from $0.06 / 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:

- Starlight Fast 2, up to 1080p: $0.06 / second of input video
- up to 1080p: $0.12 / second of input video
- Starlight Fast 2, up to 1080p, frame rate: $0.12 / second of input video
- Starlight Fast 2, 4K: $0.13 / second of input video
- Starlight Fast 2, above 4K: $0.2311 / second of input video
- up to 1080p, frame rate: $0.24 / second of input video
- 4K: $0.255 / second of input video
- Starlight Fast 2, 4K, frame rate: $0.26 / second of input video
- above 4K: $0.4533 / second of input video
- Starlight Fast 2, above 4K, frame rate: $0.4622 / second of input video
- 4K, frame rate: $0.51 / second of input video
- above 4K, frame rate: $0.9067 / second of input video

The full example input below costs $2.60 = 2600 API credits (10 s input video × $0.255 (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/generative` 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 de la vidéo source pour la mise à l’échelle. |
| `model` |  | enum (string) | no | `Starlight Precise 2.6` | `Starlight Precise 2.6`, `Starlight HQ`, `Starlight Mini`, `Starlight Sharp`, `Starlight Fast 2` | Sélection du modèle de diffusion génératif pour l’amélioration vidéo. Pour la restauration d’archives, utilisez Starlight Mini ; pour une restauration rapide aux détails nets, Starlight Sharp ; pour une qualité maximale à partir de séquences haute résolution, Starlight HQ ; et pour des vidéos générées par IA plus réalistes, Starlight Precise 2.6. Parmi les modèles de mise à l’échelle par diffusion, Starlight Fast 2 est à la fois le plus rapide et le moins cher. |
| `upscale_factor` |  | number | no | `2` | 1 – 4 | Multiplicateur de mise à l’échelle vidéo ; une valeur de 2.0 double les deux dimensions des images. |
| `target_fps` |  | integer \| null | no |  | 16 – 60 | Fréquence d’images cible de sortie ; une fréquence identique à celle de la source désactive l’interpolation, et seule une fréquence différente l’active. |
| `softness` |  | number \| null | no |  | 1 – 5 | Paramètre de douceur disponible uniquement pour Starlight Precise 2.6, avec la valeur par défaut utilisée en cas d’omission. Sélectionnez 1 pour la sortie la plus nette ou 5 pour la plus douce. |
| `H264_output` |  | boolean | no | `false` |  | Indique si la vidéo de sortie utilise l’encodage H264 au lieu du H265 par défaut. |

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/upscale/video/generative?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/upscale/video/generative?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/upscale/video/generative", 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/generative",
      "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/upscale/video/generative",
  "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": 2600,
    "usd": "2.60",
    "charged": 2600,
    "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} | Fichier vidéo produit par la mise à l’échelle. |

## 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 Video Upscale](https://doitong.com/developers/models/topaz/upscale/video/precision.md) (`topaz/upscale/video/precision`): from $0.00667 / 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/generative
- 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/generative
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/topaz/upscale/video/generative