# Nemotron Diffusion Vlm API

> مدل بینایی-زبان که با رمزگشایی متنی مبتنی بر انتشار، به پرامپت‌های مربوط به تصویر پاسخ می‌دهد

تصویر را در `image_url` و پرسش را در `prompt` می‌گیرد و پاسخ متنی برمی‌گرداند. رمزگشایی از طریق `max_tokens` (1 تا 8192)، `num_inference_steps` (1 تا 1024)، `block_length` (8 تا 128) و `threshold` اطمینان از 0 تا 1 قابل تنظیم است. خروجی همچنین جزئیات زمان‌بندی و مصرف را شامل می‌شود.

- Model id: `nemotron-diffusion-vlm`
- Made by: NVIDIA
- Category: Vision
- Output: text
- Estimated price per run: $0.005 / run (cheapest run $0.005 (5 API credits))
- Run: `POST https://api.doitong.com/v1/run/nemotron-diffusion-vlm`
- Quote: `POST https://api.doitong.com/v1/quote/nemotron-diffusion-vlm`
- Docs page: https://doitong.com/fa/developers/models/nemotron-diffusion-vlm

## Pricing

Price: **$0.005 / run**. Estimated from the typical cost of one run. The quote is exactly what the run charges.

The full example input below costs $0.005 = 5 API credits (1 request × 5 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.com/v1/quote/nemotron-diffusion-vlm` 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 |  |  | URL تصویر مورد پردازش. |
| `prompt` |  | string | yes |  |  | پرامپتی که مشخص می‌کند درباره تصویر چه پاسخی داده شود. |
| `max_tokens` |  | integer | no | `512` | 1 – 8,192 | حد بالای توکن‌های تولیدشده. |
| `num_inference_steps` |  | integer \| null | no | `256` | 1 – 1,024 | تعداد گام‌های رمزگشایی diffusion را هنگام تعیین صریح، مضربی از max_tokens / block_length انتخاب کنید؛ این تعداد نباید از این خارج‌قسمت کمتر باشد. |
| `block_length` |  | integer | no | `32` | 8 – 128 | طول هر بلوک رمزگشایی diffusion. |
| `threshold` |  | number | no | `0.9` | 0 – 1 | حد آستانه اطمینان برای رمزگشایی diffusion. |
| `enable_safety_checker` |  | boolean | no | `true` |  | با تنظیم false، در صورت مجاز بودن فراخواننده، می‌توان بررسی را آسان‌گیرانه‌تر کرد. |

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

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "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.com/v1/run/nemotron-diffusion-vlm?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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.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/nemotron-diffusion-vlm?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/nemotron-diffusion-vlm", 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": "nemotron-diffusion-vlm",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "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": "nemotron-diffusion-vlm",
  "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": 5,
    "usd": "0.005",
    "charged": 5,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "output": "The image shows a dog sitting outdoors.",
    "usage": {
      "prompt_tokens": 1,
      "completion_tokens": 1,
      "num_function_evals": 1
    },
    "timings": {
      "total_time": 1.0,
      "image_validation_time": 1.0,
      "preprocessing_time": 1.0,
      "gpu_transfer_time": 1.0,
      "generation_time": 1.0,
      "decode_time": 1.0
    }
  },
  "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `output` | string | پاسخ تولیدشده توسط مدل. |
| `usage` | object {prompt_tokens, completion_tokens, num_function_evals} | جزئیات مصرف توکن و رمزگشایی diffusion. |
| `timings` | object {total_time, image_validation_time, preprocessing_time, gpu_transfer_time, generation_time, decode_time} | جزئیات زمان پردازش درخواست، برحسب ثانیه. |

## Related models

- [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 Video](https://doitong.com/developers/models/nvidia/nemotron-3-5-super/video.md) (`nvidia/nemotron-3-5-super/video`): $0.01 / 1000 tokens
- [NVIDIA Nemotron 3.5 Super Vision](https://doitong.com/developers/models/nvidia/nemotron-3-5-super/vision.md) (`nvidia/nemotron-3-5-super/vision`): $0.01 / run
- [Bagel · Understand](https://doitong.com/developers/models/bagel/understand.md) (`bagel/understand`): $0.05 / request
- [Bria Ad Delayer](https://doitong.com/developers/models/bria/ad-delayer.md) (`bria/ad-delayer`): $0.30 / request
- [Florence 2 Large Caption](https://doitong.com/developers/models/florence-2-large/caption.md) (`florence-2-large/caption`): $0.003 / run
- [Florence 2 Large Detailed Caption](https://doitong.com/developers/models/florence-2-large/detailed-caption.md) (`florence-2-large/detailed-caption`): $0.004 / run

## Links

- HTML page: https://doitong.com/developers/models/nemotron-diffusion-vlm
- 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=nemotron-diffusion-vlm
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/nemotron-diffusion-vlm