# Nemotron 3 Nano Omni API

> صرف متنی چیٹ LLM، قابلِ تبدیـل استدلالی ٹریس اور زیادہ سے زیادہ 20,000 تیار کردہ ٹوکن کے ساتھ

ایک زبان ماڈل جو متنی پرامپٹس کے جواب دیتا ہے، رویے کی سمت متعین کرنے کے لیے اختیاری `system_prompt` کے ساتھ۔ جواب سے پہلے استدلالی ٹریس حاصل کرنے کے لیے `reasoning_mode` کو `think`، یا براہِ راست جواب کے لیے `no_think` پر سیٹ کریں۔ `max_tokens` 20,000 تک جا سکتا ہے، جبکہ `temperature` اور `top_p` قابلِ تنظیم ہیں۔ پرامپٹس انگریزی میں ہونے چاہییں۔

- Model id: `nvidia/nemotron-3-nano-omni`
- Made by: NVIDIA
- Category: LLM
- Output: text
- Estimated price per run: $0.01 / run (cheapest run $0.01 (10 API credits))
- Run: `POST https://api.doitong.ru/v1/run/nvidia/nemotron-3-nano-omni`
- Quote: `POST https://api.doitong.ru/v1/quote/nvidia/nemotron-3-nano-omni`
- Docs page: https://doitong.com/ur/developers/models/nvidia/nemotron-3-nano-omni

## Pricing

Price: **$0.01 / run**. Estimated from the typical cost of one run. The quote is exactly what the run charges.

The full example input below costs $0.01 = 10 API credits (1 request × 10 API credits).

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-3-nano-omni` 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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  | ≥ 1 characters | ماڈل کے پرامپٹ کے طور پر فراہم کیا گیا متن؛ English میں ہونا ضروری ہے۔ |
| `system_prompt` |  | string \| null | no |  |  | سسٹم پرامپٹ کے طور پر فراہم کردہ ماڈل کے لیے اختیاری رہنمائی، جس کے کنٹرولز میں استدلال شامل نہیں؛ اس کے لیے `reasoning_mode` استعمال کریں۔ |
| `reasoning_mode` |  | enum (string) | no | `no_think` | `think`, `no_think` | جواب کا format: `think` حتمی جواب سے پہلے واضح chain-of-thought trace شامل کرتا ہے۔ اس trace کے بغیر براہِ راست جواب کے لیے `no_think` استعمال کریں۔ |
| `max_tokens` |  | integer | no | `1024` | 1 – 20,000 | تخلیق کردہ ٹوکن کی بالائی حد۔ |
| `temperature` |  | number | no | `0.7` | 0 – 2 | sampling کے لیے temperature؛ کم قدریں آؤٹ پٹ کو زیادہ deterministic بناتی ہیں۔ |
| `top_p` |  | number | no | `0.95` | 0 – 1 | nucleus sampling کے لیے استعمال ہونے والا probability mass۔ |
| `enable_safety_checker` |  | boolean | no | `true` |  | یہ کنٹرول کرتا ہے کہ حفاظتی جانچ فعال ہو یا نہیں۔ |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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-3-nano-omni?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# 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-3-nano-omni?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
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 = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/nvidia/nemotron-3-nano-omni", 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-3-nano-omni",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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-3-nano-omni",
  "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": 10,
    "usd": "0.01",
    "charged": 10,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "output": "The image shows a golden retriever puppy sitting on a wooden floor.",
    "finish_reason": "stop",
    "usage": {
      "input_tokens": 1,
      "output_tokens": 1
    }
  },
  "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 | جواب کے طور پر تیار کیا گیا متن۔ |
| `finish_reason` | string | تخلیق ختم ہونے کی وجہ۔ |
| `usage` | object {input_tokens, output_tokens} | درخواست سے متعلق ٹوکن کا استعمال۔ |

## 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
- [Nemotron 3 Nano Omni · Video](https://doitong.com/developers/models/nvidia/nemotron-3-nano-omni/video.md) (`nvidia/nemotron-3-nano-omni/video`): $0.006 / 1000 tokens
- [Nemotron 3 Nano Omni · Vision](https://doitong.com/developers/models/nvidia/nemotron-3-nano-omni/vision.md) (`nvidia/nemotron-3-nano-omni/vision`): $0.018 / run
- [NVIDIA Nemotron 3.5 Super Text](https://doitong.com/developers/models/nvidia/nemotron-3-5-super/text.md) (`nvidia/nemotron-3-5-super/text`): $0.01 / run
- [Bytedance Seed V2 Mini](https://doitong.com/developers/models/bytedance/seed/v2/mini.md) (`bytedance/seed/v2/mini`): $0.0001 / 1000 tokens
- [Fibo Edit \[Structured Instruction\]](https://doitong.com/developers/models/bria/fibo-edit/edit/structured_instruction.md) (`bria/fibo-edit/edit/structured_instruction`): $0.01 / request
- [Fibo Lite · Structured Prompt](https://doitong.com/developers/models/bria/fibo-lite/generate/structured_prompt.md) (`bria/fibo-lite/generate/structured_prompt`): $0.008 / request
- [Fibo · Structured Prompt](https://doitong.com/developers/models/bria/fibo/generate/structured_prompt.md) (`bria/fibo/generate/structured_prompt`): $0.01 / request

## Links

- HTML page: https://doitong.com/developers/models/nvidia/nemotron-3-nano-omni
- 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-3-nano-omni
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/nvidia/nemotron-3-nano-omni