nvidia/cosmos-3-super/text-to-image

Texto para Imagem

Nvidia Cosmos 3 Super Text-to-Image API

nvidia/cosmos-3-super/text-to-image

Text-to-image

Cosmos3 is a collection of Omnimodal world models capable of generating dynamic, high-quality video, image, audio, and action commands from combinations of text, image, video, and action trajectory inputs.

Entrada

Prompt *

Prompt Negativo

Num inference steps

Guidance scale

Output format

Semente

Saída

Inativo

As imagens geradas serão exibidas aqui

Configure os parâmetros e clique em executar para começar a gerar

Cada execução custará $0.044. Com $10 você pode executar aproximadamente 227 vezes.

Você pode continuar com:

Imagem para Vídeo Imagem para Imagem

Parâmetros

Exemplo de código
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "nvidia/cosmos-3-super/text-to-image",  # Required. model name
    "prompt": "A beautiful landscape with mountains and lake",  # Required. The text prompt describing the image to generate
    "negative_prompt": "",  # Text describing content to exclude from the generated image
    "image_size": "landscape_16_9",  # Output image resolution
    "num_inference_steps": 28,  # Number of denoising steps. (min: 1, max: 50)
    "guidance_scale": 4,  # Classifier-free guidance scale. (min: 1, max: 20)
    "output_format": "jpeg",  # Output image format. options: jpeg | png
    "seed": 0,  # Random seed for reproducibility. (min: 0)
    "enable_safety_checker": False,  # Enable or disable the safety checker
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

Instalar

Instale o pacote necessário para a sua linguagem de programação.

pip install requests

Autenticação

Todas as solicitações de API requerem autenticação por meio de uma chave de API. Você pode obter sua chave de API no painel do Atlas Cloud.

export ATLASCLOUD_API_KEY="your-api-key-here"

Cabeçalhos HTTP

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Mantenha sua chave de API segura

Nunca exponha sua chave de API em código do lado do cliente ou repositórios públicos. Use variáveis de ambiente ou um proxy de backend.

Enviar uma solicitação

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Enviar uma solicitação

Envie uma solicitação de geração assíncrona. A API retorna um ID de predição que você pode usar para verificar o status e obter o resultado.

POST/api/v1/model/generateImage

Corpo da solicitação

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "nvidia/cosmos-3-super/text-to-image",
    "prompt": "A beautiful landscape with mountains and lake"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

Resposta

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Verificar status

Consulte o endpoint de predição para verificar o status atual da sua solicitação.

GET/api/v1/model/prediction/{prediction_id}

Exemplo de polling

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Valores de status

processingA solicitação ainda está sendo processada.

completedA geração está completa. As saídas estão disponíveis.

succeededA geração foi bem-sucedida. As saídas estão disponíveis.

failedA geração falhou. Verifique o campo de erro.

Resposta concluída

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Enviar arquivos

Envie arquivos para o armazenamento do Atlas Cloud e obtenha uma URL que pode ser usada nas suas solicitações de API. Use multipart/form-data para enviar.

POST/api/v1/model/uploadMedia

Exemplo de upload

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Resposta

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Schema de entrada

Os seguintes parâmetros são aceitos no corpo da solicitação.

Total: 9Obrigatório: 2Opcional: 7

modelstringrequired

model name

Default: "nvidia/cosmos-3-super/text-to-image"

promptstringrequired

The text prompt describing the image to generate. Maximum 2,500 characters.

negative_promptstring

Text describing content to exclude from the generated image.

Default: ""

image_sizeunknown

Output image resolution. Use a preset size or specify custom width and height via an ImageSize object.

Default: "landscape_16_9"

num_inference_stepsinteger

Number of denoising steps. Higher values improve quality but increase generation time.

Default: 28Min: 1Max: 50

guidance_scalenumber

Classifier-free guidance scale. Higher values make the output follow the prompt more closely.

Default: 4Min: 1Max: 20

output_formatstring

Output image format.

Default: "jpeg"

jpegpng

seedinteger

Random seed for reproducibility. Use the same seed and prompt to reproduce results.

Min: 0

enable_safety_checkerboolean

Enable or disable the safety checker. Disabling the safety checker may result in NSFW content.

Default: false

Exemplo de corpo da solicitação

{
  "model": "nvidia/cosmos-3-super/text-to-image",
  "prompt": "A beautiful landscape",
  "negative_prompt": "",
  "image_size": "landscape_16_9",
  "num_inference_steps": 28,
  "guidance_scale": 4,
  "output_format": "jpeg",
  "enable_safety_checker": false
}

Schema de saída

A API retorna uma resposta de predição com as URLs de saída geradas.

modelstring

model name

Default: "nvidia/cosmos-3-super/text-to-image"

created_atstring

ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

idstring

Unique identifier for the prediction.

outputsarray

Array of URLs to the generated images. Null when status is not completed.

statusstring

Status of the task: created, processing, completed, or failed.

Exemplo de resposta

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

O Atlas Cloud Skills integra mais de 400 modelos de IA diretamente no seu assistente de codificação com IA. Um comando para instalar e depois use linguagem natural para gerar imagens, vídeos e conversar com LLM.

Clientes compatíveis

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ clientes compatíveis

Instalar

npx skills add AtlasCloudAI/atlas-cloud-skills

Configurar chave de API

Obtenha sua chave de API no painel do Atlas Cloud e defina-a como variável de ambiente.

export ATLASCLOUD_API_KEY="your-api-key-here"

Funcionalidades

Após a instalação, você pode usar linguagem natural no seu assistente de IA para acessar todos os modelos do Atlas Cloud.

Geração de imagensGere imagens com modelos como Nano Banana 2, Z-Image e mais.

Criação de vídeosCrie vídeos a partir de texto ou imagens com Kling, Vidu, Veo, etc.

Chat com LLMConverse com Qwen, DeepSeek e outros grandes modelos de linguagem.

Upload de mídiaEnvie arquivos locais para fluxos de trabalho de edição de imagens e imagem para vídeo.

Saiba mais

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

O Atlas Cloud MCP Server conecta seu IDE com mais de 400 modelos de IA através do Model Context Protocol. Funciona com qualquer cliente compatível com MCP.

Clientes compatíveis

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ clientes compatíveis

Instalar

npx -y atlascloud-mcp

Configuração

Adicione a seguinte configuração ao arquivo de configuração de MCP do seu IDE.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Ferramentas disponíveis

atlas_generate_imageGere imagens a partir de prompts de texto.

atlas_generate_videoCrie vídeos a partir de texto ou imagens.

atlas_chatConverse com grandes modelos de linguagem.

atlas_list_modelsExplore mais de 400 modelos de IA disponíveis.

atlas_quick_generateCriação de conteúdo em uma etapa com seleção automática de modelo.

atlas_upload_mediaEnvie arquivos locais para fluxos de trabalho de API.

Saiba mais

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        },
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        },
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "schema": {
              "type": "string",
              "description": "Request ID"
            },
            "required": true
          }
        ]
      },
      "x-api-name": "model_result"
    }
  },
  "openapi": "3.0.0",
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "nvidia/cosmos-3-super/text-to-image"
          },
          "prompt": {
            "description": "The text prompt describing the image to generate. Maximum 2,500 characters.",
            "type": "string",
            "minLength": 1,
            "maxLength": 2500
          },
          "negative_prompt": {
            "description": "Text describing content to exclude from the generated image.",
            "type": "string",
            "default": ""
          },
          "image_size": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/ImageSize"
              },
              {
                "type": "string",
                "enum": [
                  "square_hd",
                  "square",
                  "portrait_4_3",
                  "portrait_16_9",
                  "landscape_4_3",
                  "landscape_16_9"
                ]
              }
            ],
            "description": "Output image resolution. Use a preset size or specify custom width and height via an ImageSize object.",
            "title": "Resolution",
            "default": "landscape_16_9",
            "x-ui-component": "select",
            "x-enum-labels": {
              "square_hd": "Square HD (1024×1024)",
              "square": "Square (512×512)",
              "portrait_4_3": "Portrait 4:3",
              "portrait_16_9": "Portrait 16:9",
              "landscape_4_3": "Landscape 4:3",
              "landscape_16_9": "Landscape 16:9"
            }
          },
          "num_inference_steps": {
            "description": "Number of denoising steps. Higher values improve quality but increase generation time.",
            "type": "integer",
            "default": 28,
            "minimum": 1,
            "maximum": 50
          },
          "guidance_scale": {
            "description": "Classifier-free guidance scale. Higher values make the output follow the prompt more closely.",
            "type": "number",
            "default": 4,
            "minimum": 1,
            "maximum": 20
          },
          "output_format": {
            "description": "Output image format.",
            "type": "string",
            "default": "jpeg",
            "enum": [
              "jpeg",
              "png"
            ],
            "x-ui-component": "select"
          },
          "seed": {
            "description": "Random seed for reproducibility. Use the same seed and prompt to reproduce results.",
            "type": "integer",
            "minimum": 0
          },
          "enable_safety_checker": {
            "description": "Enable or disable the safety checker. Disabling the safety checker may result in NSFW content.",
            "type": "boolean",
            "default": false
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "negative_prompt",
          "image_size",
          "num_inference_steps",
          "guidance_scale",
          "output_format",
          "seed"
        ]
      },
      "ImageSize": {
        "properties": {
          "width": {
            "type": "integer",
            "title": "Width",
            "description": "The width of the generated image.",
            "exclusiveMinimum": 0,
            "maximum": 14142,
            "default": 512
          },
          "height": {
            "type": "integer",
            "title": "Height",
            "description": "The height of the generated image.",
            "exclusiveMinimum": 0,
            "maximum": 14142,
            "default": 512
          }
        },
        "title": "ImageSize",
        "type": "object",
        "x-order-properties": [
          "width",
          "height"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "nvidia/cosmos-3-super/text-to-image"
          },
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., \"2023-04-01T12:34:56.789Z\").",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated images. Null when status is not completed.",
            "items": {
              "type": "string"
            },
            "nullable": true,
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  }
}

Template de Prompt Compatível com LLM

# nvidia/cosmos-3-super/text-to-image

> Cosmos3 is a collection of Omnimodal world models capable of generating dynamic, high-quality video, image, audio, and action commands from combinations of text, image, video, and action trajectory inputs.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `nvidia/cosmos-3-super/text-to-image`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"nvidia/cosmos-3-super/text-to-image"`

- **`prompt`** (`string`, _required_):
  The text prompt describing the image to generate. Maximum 2,500 characters.

- **`negative_prompt`** (`string`, _optional_):
  Text describing content to exclude from the generated image.
  - Default: `""`

- **`image_size`** (`string`, _optional_):
  Output image resolution. Use a preset size or specify custom width and height via an ImageSize object.
  - Default: `"landscape_16_9"`

- **`num_inference_steps`** (`integer`, _optional_):
  Number of denoising steps. Higher values improve quality but increase generation time.
  - Default: `28`
  - Min: 1
  - Max: 50

- **`guidance_scale`** (`number`, _optional_):
  Classifier-free guidance scale. Higher values make the output follow the prompt more closely.
  - Default: `4`
  - Min: 1
  - Max: 20

- **`output_format`** (`string`, _optional_):
  Output image format.
  - Default: `"jpeg"`
  - Options: "jpeg", "png"

- **`seed`** (`integer`, _optional_):
  Random seed for reproducibility. Use the same seed and prompt to reproduce results.
  - Min: 0



**Required Parameters Example**:

```json
{
  "model": "nvidia/cosmos-3-super/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "nvidia/cosmos-3-super/text-to-image",
  "prompt": "",
  "negative_prompt": "",
  "image_size": "landscape_16_9",
  "num_inference_steps": 28,
  "guidance_scale": 4,
  "output_format": "jpeg",
  "seed": 0
}
```


### Output Schema

The API returns the following output format:


- **`model`** (`string`, _optional_):
  model name
  - Default: `"nvidia/cosmos-3-super/text-to-image"`

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated images. Null when status is not completed.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "model": "nvidia/cosmos-3-super/text-to-image",
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "nvidia/cosmos-3-super/text-to-image",
  "prompt": "",
  "negative_prompt": "",
  "image_size": "landscape_16_9",
  "num_inference_steps": 28,
  "guidance_scale": 4,
  "output_format": "jpeg",
  "seed": 0
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/nvidia/cosmos-3-super/text-to-image)

A symphony orchestra performing inside a grand European train station after the last train has departed. Empty platforms stretch into darkness while warm lantern light illuminates the musicians. Steam drifts through the air, creating a dreamlike cinematic atmosphere. Emotional storytelling, movie still, ultra realistic.

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NVIDIA Cosmos 3 Super Text-to-Image

NVIDIA Cosmos 3 Super Text-to-Image is NVIDIA's flagship text-to-image model built on the Cosmos 3 architecture. Designed for high-fidelity physical world simulation, it delivers photorealistic images with strong prompt adherence, precise spatial reasoning, and support for negative prompting — making it well suited for both creative and technical generation tasks.

🌟 Key Features

🎨 Photorealistic Generation

Produces high-quality images grounded in physical realism, excelling at scenes with natural lighting, accurate materials, and spatial coherence.

📝 Strong Prompt Fidelity

Understands complex, multi-element prompts and accurately reflects subject, environment, style, and compositional instructions in the output.

🚫 Negative Prompting

Accepts a negative_prompt to explicitly exclude unwanted content, artifacts, or styles from the generated image.

📐 Flexible Output Sizes

Choose from six standard presets covering square, portrait, and landscape orientations to match any platform or use case.

🔁 Reproducible Results

Pin a seed value to reproduce or iterate on a specific generation, enabling systematic prompt refinement workflows.

⚙️ Parameters

Parameter	Required	Description
`prompt`	✅	Text description of the image to generate. Maximum 2,500 characters.
`negative_prompt`	❌	Content to exclude from the output (default: empty).
`image_size`	❌	Output size preset: `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` (default).
`num_inference_steps`	❌	Denoising steps (1–100, default: 28). Higher values improve quality but increase time.
`guidance_scale`	❌	Prompt adherence strength (1.0–20.0, default: 4.0). Higher values follow the prompt more strictly.
`output_format`	❌	Output format: `jpeg` (default) or `png`.
`seed`	❌	Random seed for reproducibility. Omit for random results.

💲 Pricing

Billing Standard	Price
Per image	$0.044

Billing is based on the number of images generated.

💡 Prompt Tips

A photorealistic close-up of hands shaping clay on a pottery wheel, warm studio lighting, shallow depth of field, 8K resolution.

Describe subject, environment, lighting, and camera perspective in a single coherent prompt.
Use negative_prompt to remove common artifacts: blurry, low quality, distorted, watermark, cartoon.
Keep guidance_scale between 3–5 for natural-looking outputs; increase to 7–10 for strict prompt adherence.
Use landscape_16_9 for cinematic or widescreen compositions.
Fix seed when iterating on prompt wording to isolate the effect of each change.

🎯 Use Cases

Creative Illustration — Generate concept art, characters, and environments from descriptive text prompts.
Product Visualization — Produce photorealistic product renders and lifestyle imagery from written descriptions.
Scene Prototyping — Rapidly visualize environment and set designs before committing to production.
Social Media Content — Create scroll-stopping visuals in any aspect ratio for any platform.
Research & Simulation — Leverage Cosmos's physical world grounding for technically accurate scene generation.
Rapid Iteration — Generate multiple candidates with varied seeds and prompts to explore creative directions quickly.

📝 Notes

prompt is the only required field (besides model).
output_format supports jpeg (smaller file size) and png (lossless).
Task status values: created, processing, completed, failed.
Generated image URLs are returned in outputs once status is completed.

NVIDIA Cosmos 3 Super Image-to-Video — Animate a reference image into a video clip with a text prompt.

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