# Nemotron Asr Multilingual API

> تفريغ كلام متعدد اللغات مع اكتشاف تلقائي للغة وأربعة مستويات للسرعة والدقة

يفرّغ ملفًا صوتيًا من `audio_url` إلى نص. تكون قيمة `language` الافتراضية `auto` للاكتشاف، أو يمكنك اختيار locale مثل en-US أو de-DE أو ja-JP من القائمة. توازن `acceleration` بين الدقة والسرعة: تكون `none` الأدق، و`regular` متوازنة، و`high` أسرع، و`full` الأسرع.

- Model id: `nvidia/nemotron-asr-multilingual/asr`
- Made by: NVIDIA
- Category: Speech to Text
- Output: text
- Price per minute of your input audio: $0.008 / minute of input audio (cheapest run $0.008 (8 API credits))
- Run: `POST https://api.doitong.ru/v1/run/nvidia/nemotron-asr-multilingual/asr`
- Quote: `POST https://api.doitong.ru/v1/quote/nvidia/nemotron-asr-multilingual/asr`
- Docs page: https://doitong.com/ar/developers/models/nvidia/nemotron-asr-multilingual/asr

## Pricing

Price: **$0.008 / minute of input audio**. Price per minute of your input audio: 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 $0.002 = 2 API credits (0.1667 min input audio × $0.008).

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/nvidia/nemotron-asr-multilingual/asr` 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 |
|---|---|---|---|---|---|---|
| `audio_url` | `audio` | string (audio URL) | yes |  |  | عنوان URL لملف الصوت المستخدم في التفريغ النصي. |
| `language` |  | enum (string) | no | `auto` | `auto`, `en-US`, `en-GB`, `es-US`, `es-ES`, `de-DE`, `fr-FR`, `fr-CA`, `it-IT`, `ar-AR`, `ja-JP`, `ko-KR`, `pt-BR`, `pt-PT`, `ru-RU`, `hi-IN`, `zh-CN`, `vi-VN`, `he-IL`, `nl-NL`, `cs-CZ`, `da-DK`, `pl-PL`, `nn-NO`, `nb-NO`, `sv-SE`, `th-TH`, `tr-TR`, `bg-BG`, `el-GR`, `et-EE`, `fi-FI`, `hr-HR`, `hu-HU`, `lt-LT`, `lv-LV`, `ro-RO`, `sk-SK`, `uk-UA`, `mt-MT`, `sl-SI` | موجّه لتعريف اللغة في التفريغ النصي، يقبل لغة مستهدفة أو 'auto' للكشف المعتمد على النموذج. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high`, `full` | إعداد السرعة/الدقة المستند إلى طول المقطع: يحقق 1.12s مع 'none' أفضل دقة؛ ويوازن 0.56s مع 'regular' بين السرعة والدقة؛ ويكون 0.32s مع 'high' أسرع؛ بينما 0.08s مع 'full' هو الأسرع. |

File parameters (`audio`) 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
{
  "audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
```

A fuller example:

```json
{
  "audio_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
```

## 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/nvidia/nemotron-asr-multilingual/asr?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "audio_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
  }'

# 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/nvidia/nemotron-asr-multilingual/asr?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "audio_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
  }),
});
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 = {
    "audio_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/nvidia/nemotron-asr-multilingual/asr", 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": "nvidia/nemotron-asr-multilingual/asr",
      "input": {
        "audio_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
      },
      "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": "nvidia/nemotron-asr-multilingual/asr",
  "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": 2,
    "usd": "0.002",
    "charged": 2,
    "refunded": 0
  },
  "input": {
    "audio_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
  },
  "output": {
    "output": "Actually, I'm second guessing myself a single coherent passage might be cleaner and more representative of real world speech performance, which is what benchmarking typically uses. I'll write an engaging flowing piece on something like a journey or a day in a tech forward city. That weaves in all the varied elements naturally, rather than splitting it into sections. I'm deciding to keep the targeted tricky sentences section after all. It'll directly test homophones and number heavy lines that are most prone to errors, so I'll include it as a concise, clearly marked addition at the end now. I'm drafting the full passage, starting with a detailed travel narrative that weaves in dates, times, currency, and specific details by the time we pulled into Waverley Station, my phone had buzzed forty seven times, mostly from doctor Amara Akon Reyes at Neurosynt Technologies fretting over our board presentation. We'd spent three weeks refining a transformer model with one point three billion parameters, and the improvements were stunning. Our word error rate plummeted from fourteen point two percent down to three point eight percent. There's something surreal about watching those number shift like that. They're not just metrics they're the payoff from countless late nights and too much coffee.",
    "partial": false
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "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 |
|---|---|---|
| `output` | string | النص المستخرج من تفريغ الصوت. |
| `partial` | boolean | يكون True عندما تكون نتيجة البث مؤقتة. |

## Related models

- [Nemotron 3 Nano Omni · Audio](https://doitong.com/developers/models/nvidia/nemotron-3-nano-omni/audio.md) (`nvidia/nemotron-3-nano-omni/audio`): $0.01 / 1000 tokens
- [Cohere Transcribe](https://doitong.com/developers/models/cohere-transcribe.md) (`cohere-transcribe`): $0.0000694 / second of input audio
- [Elevenlabs - Forced Alignment](https://doitong.com/developers/models/elevenlabs/forced-alignment.md) (`elevenlabs/forced-alignment`): $0.22 / hour of input audio
- [ElevenLabs Speech to Text](https://doitong.com/developers/models/elevenlabs/speech-to-text.md) (`elevenlabs/speech-to-text`): $0.03 / minute of input audio
- [ElevenLabs Speech to Text - Scribe V2](https://doitong.com/developers/models/elevenlabs/speech-to-text/scribe-v2.md) (`elevenlabs/speech-to-text/scribe-v2`): $0.008 / minute of input audio
- [Kotoba Speech-to-Text](https://doitong.com/developers/models/kotoba-technologies/kotoba-stt/v1/speech-to-text.md) (`kotoba-technologies/kotoba-stt/v1/speech-to-text`): $0.0000694 / second of input audio
- [Pipecat's Smart Turn model](https://doitong.com/developers/models/smart-turn.md) (`smart-turn`): $0.00111 / second of processing time
- [Silero VAD](https://doitong.com/developers/models/silero-vad.md) (`silero-vad`): $0.00001 / second of input audio

## Links

- HTML page: https://doitong.com/developers/models/nvidia/nemotron-asr-multilingual/asr
- 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=nvidia/nemotron-asr-multilingual/asr
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/nvidia/nemotron-asr-multilingual/asr