# Cosmos 3 Super API

> Tekstosar-kipo keripe prompto expansionosa thaj opcionalone agentic kandidatonge-komparacijake modosa

Kerel 1 dži 4 kipo andar `prompt` dži 4096 karaktera. `image_size` edges si limitime 512-1280 px. `enable_agentic_generation` kerel but kandidata thaj lačharel o prompto maškar rounds, dži 3 iteraciji. Vi si `negative_prompt`, `guidance_scale` dži 20, `num_inference_steps` dži 50, thaj jpeg vaj png rezultato.

- Model id: `nvidia/cosmos-3-super/text-to-image`
- Made by: NVIDIA
- Category: Text to Image
- Output: image
- Price per run: from $0.04 / run of output image (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.ru/v1/run/nvidia/cosmos-3-super/text-to-image`
- Quote: `POST https://api.doitong.ru/v1/quote/nvidia/cosmos-3-super/text-to-image`
- Docs page: https://doitong.com/rom/developers/models/nvidia/cosmos-3-super/text-to-image

## Pricing

Price: **from $0.04 / run of output image** (the lowest tier; the quote prices your exact input). Price per run: 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 $0.04 = 40 API credits (1 run × $0.04).

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/cosmos-3-super/text-to-image` 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 |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  | 1 – 4096 characters | Tekstosk-i deskripcija e mangljake rezultato kipeski. |
| `negative_prompt` |  | string | no | `` | ≤ 1024 characters | Negative guidance savo sikavel nakamime rangura, predmetura vaj artefakto vaš te na kerel len. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Promptoskoro lačharipen anglal keripe, OpenRouterça, savo kerel dense structured-JSON reprezentacij so labardilo Cosmos3 sikavipastar. Kana lačharipen na džal, kiposkoro keripe džal na-modifikime promptesa. |
| `enable_agentic_generation` |  | boolean | no | `false` |  | Automatikano promptoskoro lačharipaskoro loop vaš po paše džalipen originalno mangipnasa. Sako runda kerel but kipo-kere kandidat para thaj mukhel len te compete, promptoskere paruvipena mashkar runde. |
| `agentic_max_iterations` |  | integer | no | `2` | 1 – 3 | Lačharipaskeri rundakoro limitos vaš keripe agentic modesa. |
| `agentic_samples_per_iteration` |  | integer | no | `2` | 1 – 3 | Sa-iteracijakoro kiposkere kandidatonge gin and-o agentic loop; phenel keci kipo compete-il and-i evaluacij anglal o majlačho džal ko promptoskoro palal-lilavipe. |
| `agentic_early_stop` |  | boolean | no | `true` |  | Early-stop kontrola savi lel zoralo kipo-to-prompt match sar dosta te agoril bi majbut iteracijengo. |
| `image_size` |  | object {width, height} \| enum (string) | no | `square_hd` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Thov o rezultatoskoro kiposkere dimenzije; clamping ačhavel sako agor mashkar 512 thaj 1280px, thaj agora musaj te aven multiples 16-eskere. |
| `num_inference_steps` |  | integer | no | `28` | 1 – 50 | Gendo e denoising stepengo, kaj maj lengo procesipen del maj lačhi kvaliteta kana o gendo barol. |
| `guidance_scale` |  | number | no | `4` | 0 – 20 | Zor e classifier-free guidance-ki. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Manglo kipoqo gin vaš generiripe. |
| `seed` |  | integer \| null | no |  |  | Seed vaš povtorime kiposkoro keripe. O rezultatoskoro kipo na paruvvel pes mashkar runura, te na paruvvel pes seed, prompto vaj modeloskoro versija. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Content moderacijakoro switch savo ačhavel prompto inputo thaj kipo rezultato. Accountura musaj te aven autorizime vaš bypass; averčhane kontrolura si obavezime. Kipo savo dikhel pes unsafe, zamenel pes kale kipesa. |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | Fajlo-formato e rezultato kipoqo. |

## 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/cosmos-3-super/text-to-image?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/cosmos-3-super/text-to-image?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/cosmos-3-super/text-to-image", 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/cosmos-3-super/text-to-image",
      "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/cosmos-3-super/text-to-image",
  "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": 40,
    "usd": "0.04",
    "charged": 40,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "images": [
      {
        "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,
        "width": 1024,
        "height": 768
      }
    ],
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ]
  },
  "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 |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Kipo kerdine e modeloça. |
| `seed` | integer | Seed-valoro aplikovano ko generiripe. |
| `has_nsfw_concepts` | array of boolean | Status e safety-checkerosko pala sako kerdo kipo. |

## Related models

- [Cosmos 3 Super Image to Video](https://doitong.com/developers/models/nvidia/cosmos-3-super/image-to-video.md) (`nvidia/cosmos-3-super/image-to-video`): from $0.05 / second of output video
- [FLUX.1 \[dev\]](https://doitong.com/developers/models/flux/dev.md) (`flux/dev`): $0.025 / megapixel
- [FLUX.1 \[schnell\]](https://doitong.com/developers/models/flux/schnell.md) (`flux/schnell`): $0.003 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [GPT Image 2.5 Text to Image](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/text-to-image.md) (`openai/gpt-image-2.5/flare/text-to-image`): from $0.008 / image
- [Ideogram V4.5](https://doitong.com/developers/models/ideogram/v4.5.md) (`ideogram/v4.5`): from $0.03 / image
- [Nano Banana 2](https://doitong.com/developers/models/nano-banana-2.md) (`nano-banana-2`): from $0.06 / image

## Links

- HTML page: https://doitong.com/developers/models/nvidia/cosmos-3-super/text-to-image
- 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/cosmos-3-super/text-to-image
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/nvidia/cosmos-3-super/text-to-image