# Cosmos 3 Super Image to Video API

> Janimà immaġni tal-ewwel frejm f'vidjo, b'espansjoni fakultattiva tal-prompt u loop ta' rfinar agentiku

Juża `image_url` bħala l-frejm tal-ftuħ u `prompt` sa 4096 karattru. `num_frames` jitla' sa 189 u `frames_per_second` minn 4 sa 60. L-espansjoni tal-prompt hija attivata prestabbilitament, u `enable_agentic_generation` iħaddem kandidati iterattivi bi kritika. Joffri wkoll `negative_prompt`, `guidance_scale` u `num_inference_steps` sa 50.

- Model id: `nvidia/cosmos-3-super/image-to-video`
- Made by: NVIDIA
- Category: Image to Video
- Output: video
- Price per second of your output video: from $0.05 / second of output video (cheapest run $0.05 (50 API credits))
- Run: `POST https://api.doitong.ru/v1/run/nvidia/cosmos-3-super/image-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/nvidia/cosmos-3-super/image-to-video`
- Docs page: https://doitong.com/mt/developers/models/nvidia/cosmos-3-super/image-to-video

## Pricing

Price: **from $0.05 / second of output video** (the lowest tier; the quote prices your exact input). Price per second of your output 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.

The full example input below costs $0.40 = 400 API credits (8 s output video × $0.05).

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/image-to-video` 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 | Istruzzjonijiet testwali għall-ġenerazzjoni tal-vidjo: speċifika x’fih ix-xenarju u l-moviment li għandu juri. |
| `image_url` | `image` | string (image URL) | yes |  |  | URL tal-immaġni użata biex tikkundizzjona l-ewwel frejm tal-vidjo. |
| `negative_prompt` |  | string | no | `The video captures a series of frames showing macroblocking artifacts, chromatic aberration, high-frequency noise, and rolling shutter distortion. It includes static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, bit-depth compression artifacts, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, hard cut, visual noise, and flickering. It features moiré patterns, edge halos, and temporal aliasing. Furthermore, the content defies common sense, generating illogical scenarios, nonsensical entities, absurd character behaviors, and conceptual paradoxes that violate basic human reasoning and everyday reality. The video looks like a surreal or glitchy hallucination. Overall, the video is of poor quality.` | ≤ 2048 characters | Prompt negattiv biex jiskoraġġixxi kontenut bħal moviment jew artefatti mhux mixtieqa. Jekk jitħalla barra, jintuża l-prompt negattiv rakkomandat minn NVIDIA għal i2v, filwaqt li string vojta tiddiżattiva l-gwida negattiva. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Espansjoni tal-prompt li, meta tkun true, tuża Cosmos3-Nano Reasoner biex tipproduċi l-format ta’ deskrizzjoni densa użat għat-taħriġ ta’ Cosmos3; dan il-VLM jeżamina l-ewwel frejm. COSMOS_PROMPT_UPSAMPLER_BASE_URL jagħżel servizz Reasoner ikkonfigurat; inkella, l-app tniedi wieħed lokalment. Jekk l-espansjoni tfalli, jintuża l-prompt mhux modifikat. |
| `enable_agentic_generation` |  | boolean | no | `false` |  | Ġenerazzjoni iterattiva aġentika ta’ Cosmos, ferm aktar bil-mod u għalja mill-ġenerazzjoni darba waħda għax kull kandidat jeħtieġ render sħiħ. Iċ-ċiklu jespandi l-prompt, jiġġenera kandidati tal-vidjo, juża VLM biex jikkritika frejms kampjunati, u jikteb mill-ġdid il-prompt. |
| `agentic_max_iterations` |  | integer | no | `2` | 1 – 3 | Limitu massimu tal-istadji tal-prompt meta l-ġenerazzjoni aġentika tkun attivata. |
| `agentic_samples_per_iteration` |  | integer | no | `2` | 1 – 3 | Għadd ta’ kandidati tal-vidjo għal kull iterazzjoni taċ-ċiklu aġentiku, li jiddetermina kemm-il vidjo jikkompeti fl-evalwazzjoni qabel ma l-aħjar jgħaddi għall-kitba mill-ġdid tal-prompt. |
| `agentic_early_stop` |  | boolean | no | `true` |  | Kontroll tal-waqfien bikri li jqis punteġġ ta’ kritiku ogħla mil-limitu strett tal-kwalità bħala biżżejjed biex jintemm iċ-ċiklu aġentiku. |
| `image_size` |  | object {width, height} \| enum (string) | no | `{"height":480,"width":832}` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Dimensjonijiet tal-vidjo mitluba qabel l-aġġustament awtomatiku. Biex tikseb daqs appoġġjat, is-sistema tillimita t-talba u tagħżel l-eqreb livell ta’ NVIDIA—256p, 480p jew 720p—u proporzjon tal-aspett appoġġjat. |
| `num_frames` |  | integer | no | `189` | 5 – 189 | Għadd ta’ frejms għall-ġenerazzjoni; żiedu jipproduċi vidjo itwal. |
| `frames_per_second` |  | integer | no | `24` | 4 – 60 | Rata tal-frejms tal-vidjo output, imkejla f'frejms kull sekonda. |
| `num_inference_steps` |  | integer | no | `28` | 1 – 50 | Għadd tal-passi tat-tneħħija tal-istorbju, fejn proċessar itwal jipprovdi kwalità aħjar hekk kif jiżdied l-għadd. |
| `guidance_scale` |  | number | no | `6` | 0 – 20 | Saħħa tal-gwida mingħajr klassifikatur. |
| `seed` |  | integer \| null | no |  |  | Żerriegħa li tikkontrolla r-ripetibbiltà: prompt u żerriegħa identiċi jipproduċu vidjo identiku meta l-verżjoni tal-mudell ma tinbidilx. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Kontroll tal-moderazzjoni għall-immaġni u l-prompt ipprovduti, b’diżattivazzjoni permessa biss għal kontijiet awtorizzati. Talbiet mingħajr awtorizzazzjoni jgħaddu mill-kontrolli irrispettivament mill-issettjar. |

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
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## 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/image-to-video?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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# 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/image-to-video?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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# 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/image-to-video", 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/image-to-video",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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/image-to-video",
  "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": 400,
    "usd": "0.40",
    "charged": 400,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "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,
      "width": 1024,
      "height": 768,
      "fps": 1.0,
      "duration": 5,
      "num_frames": 1
    },
    "seed": 42
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames} | Vidjo prodott mill-mudell. |
| `seed` | integer | Valur ta’ seed applikat waqt il-ġenerazzjoni. |

## Related models

- [Cosmos 3 Super](https://doitong.com/developers/models/nvidia/cosmos-3-super/text-to-image.md) (`nvidia/cosmos-3-super/text-to-image`): from $0.04 / run of output image
- [FLUX 3 Max Image to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/image-to-video.md) (`blackforestlabs/flux-3-max/image-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Image to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/image-to-video.md) (`xai/grok-imagine-video/v1.5/image-to-video`): from $0.082 / second
- [Kling 3.0 Pro Image to Video](https://doitong.com/developers/models/kling-video/v3/pro/image-to-video.md) (`kling-video/v3/pro/image-to-video`): from $0.112 / second
- [LTX 2.5 Pro Image to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/image-to-video/pro.md) (`lightricks/ltx-2.5/image-to-video/pro`): from $0.12 / second
- [MiniMax H3 Image to Video](https://doitong.com/developers/models/minimax/h3/image-to-video.md) (`minimax/h3/image-to-video`): from $0.05 / second
- [Seedance 2.0 Fast Image to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/fast/image-to-video.md) (`bytedance/seedance-2.0/fast/image-to-video`): from $0.113 / second
- [Seedance 2.0 Image to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/image-to-video.md) (`bytedance/seedance-2.0/image-to-video`): from $0.141 / second

## Links

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