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

text-to-image

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.

Compare models

Nvidia Cosmos 3 Super Text-to-Image is developed by NVIDIA. Atlas Cloud (operated by Atlas Cloud AI LLC) provides access to it and does not own it. All trademarks belong to their respective owners.

INPUT

Prompt *

Negative Prompt

Num inference steps

Guidance scale

Output format

Seed

OUTPUT

Idle

Your generated images will appear here

Configure your settings and click Run to get started

Your request will cost $0.044 per run. For $10 you can run this model approximately 227 times.

Here's what you can do next:

Image-to-Video Image-to-Image

Parameters

Code Example
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()

Install

Install the required package for your language.

pip install requests

Authentication

All API requests require authentication via an API key. You can get your API key from the Atlas Cloud dashboard.

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

HTTP Headers

import os

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

Keep your API key secure

Never expose your API key in client-side code or public repositories. Use environment variables or a backend proxy instead.

Submit a request

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())

Submit a Request

Submit an asynchronous generation request. The API returns a prediction ID that you can use to check the status and retrieve the result.

POST/api/v1/model/generateImage

Request Body

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']}")

Response

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

Check Status

Poll the prediction endpoint to check the current status of your request.

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

Polling Example

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)

Status Values

processingThe request is still being processed.

completedGeneration is complete. Outputs are available.

succeededGeneration succeeded. Outputs are available.

failedGeneration failed. Check the error field.

Completed Response

{
  "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"
  }
}

Upload Files

Upload files to Atlas Cloud storage and get a URL you can use in your API requests. Use multipart/form-data to upload.

POST/api/v1/model/uploadMedia

Upload Example

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}")

Response

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

Input Schema

The following parameters are accepted in the request body.

Total: 9Required: 2Optional: 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

Example Request Body

{
  "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
}

Output Schema

The API returns a prediction response with the generated output URLs.

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.

Example Response

{
  "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

Atlas Cloud Skills integrates 400+ AI models directly into your AI coding assistant. One command to install, then use natural language to generate images, videos, and chat with LLMs.

Supported Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ supported clients

Install

npx skills add AtlasCloudAI/atlas-cloud-skills

Setup API Key

Get your API key from the Atlas Cloud dashboard and set it as an environment variable.

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

Capabilities

Once installed, you can use natural language in your AI assistant to access all Atlas Cloud models.

Image GenerationGenerate images with models like Nano Banana 2, Z-Image, and more.

Video CreationCreate videos from text or images with Kling, Vidu, Veo, etc.

LLM ChatChat with Qwen, DeepSeek, and other large language models.

Media UploadUpload local files for image editing and image-to-video workflows.

Learn more

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server connects your IDE with 400+ AI models via the Model Context Protocol. Works with any MCP-compatible client.

Supported Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ supported clients

Install

npx -y atlascloud-mcp

Configuration

Add the following configuration to your IDE's MCP settings file.

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

Available Tools

atlas_generate_imageGenerate images from text prompts.

atlas_generate_videoCreate videos from text or images.

atlas_chatChat with large language models.

atlas_list_modelsBrowse 400+ available AI models.

atlas_quick_generateOne-step content creation with auto model selection.

atlas_upload_mediaUpload local files for API workflows.

Learn more

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"
      }
    }
  }
}

LLM-Friendly Prompt Template

# 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.

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.

Explore Similar Models

NEW

text-to-image

Openai GPT Image 2 Text-to-Image

GPT Image 2 text to image is OpenAI's fast, cost-efficient text-to-image generator powered by GPT-5 guidance. Create photorealistic shots, product renders, concept art, and stylized graphics from natural-language prompts (optionally conditioned with an image). Supports custom aspect ratios, seeds, negative prompts, hex color hints, and style presets. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Openai GPT Image 2 Edit

GPT Image 2 Edit is OpenAI's image model for precise, natural-language edits. Add/remove objects, swap backgrounds, retouch faces, adjust colors/lighting, edit text/graphics, crop/resize, and apply hex color control. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

GPT Image 2 Developer Edit

GPT Image 2 Developer Edit applies natural-language instructions to one or more reference images, with common aspect ratios and 1k, 2k, or supported 4k output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

GPT Image 2 Developer Text-to-Image

GPT Image 2 Developer Text-to-Image generates polished visuals from natural-language prompts, with common aspect ratios and 1k, 2k, or supported 4k output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Seedream v5.0 Pro Layer Decomposition

ByteDance flagship image layer decomposition. Splits a single input image into an editable stack: one base image plus up to 16 transparent PNG layers, each returned with stacking order (z_index), bounding box coordinates, name, and description for downstream drag/scale/recompose editing.

Reve 2.1 Remix

Reve 2.1 Remix composes one to six reference images with a natural-language prompt into a single coherent image at native 4K, blending subject, style, and background while keeping references consistent.

Reve 2.1 Edit

Reve 2.1 Edit applies precise, instruction-driven, element-level edits to a single input image at native 4K, changing targeted regions while preserving the rest of the scene.

Reve 2.1 Text-to-Image

Reve 2.1 is a layout-first text-to-image model that turns natural-language prompts into sharp, production-ready images at native 4K, with best-in-class typography and high prompt adherence.

Youchuan V8.2 Remove Background

Youchuan automatically removes the background from an input image, returning one transparent-background result.

Youchuan V8.2 Style Transfer

Youchuan retexture changes the artistic style of an input image while preserving its composition, returning four restyled results.

Youchuan V8.2 Blend

Youchuan V8.2 blends two to five input images into four fused results, with an optional guiding prompt and native 2K HD.

Youchuan V8.2 Image-to-Image

Youchuan V8.2 re-imagines an input image guided by a text prompt, returning four variations. Supports native 2K HD, style reference, and aspect-ratio / stylize / chaos / weird controls.

Youchuan V8.2 Text-to-Image

Youchuan V8.2 generates four images from a text prompt, with optional native 2K HD, a style reference, and aspect-ratio / stylize / chaos / weird controls.

Seedream v5.0 Pro Edit

ByteDance flagship next-generation image editing model. Supports up to 10 reference images while preserving identity, lighting, and color tones for professional-quality modifications.

Seedream v5.0 Pro Text-to-Image

ByteDance flagship next-generation image generation model with stronger prompt adherence, refined typography, and photorealistic detail. Single-image output at 1.5K and 2K tiers with JPEG and PNG support.

Nano Banana 2 Lite Edit Developer

Google's fastest and most cost-efficient Nano Banana image model for editing, applying natural-language edits and multi-image composition to up to 14 reference images with low latency.

From$0.04/PIC

$0.028/PIC

-30%

One API for All Media AI.

Explore all models

Nvidia Cosmos 3 Super Text-to-Image API

INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values

Completed Response

Upload Files

Upload Example

Response

Input Schema

Example Request Body

Output Schema

Example Response

Atlas Cloud Skills

Supported Clients

Install

Setup API Key

Capabilities

MCP Server

Supported Clients

Install

Configuration

Available Tools

API Schema

LLM-Friendly Prompt Template

NVIDIA Cosmos 3 Super Text-to-Image

🌟 Key Features

🎨 Photorealistic Generation

📝 Strong Prompt Fidelity

🚫 Negative Prompting

📐 Flexible Output Sizes

🔁 Reproducible Results

⚙️ Parameters

💲 Pricing

💡 Prompt Tips

🎯 Use Cases

📝 Notes

🔗 Related Models

Explore Similar Models

Openai GPT Image 2 Text-to-Image

Openai GPT Image 2 Edit

GPT Image 2 Developer Edit

GPT Image 2 Developer Text-to-Image

Seedream v5.0 Pro Layer Decomposition

Reve 2.1 Remix

Reve 2.1 Edit

Reve 2.1 Text-to-Image

Youchuan V8.2 Remove Background

Youchuan V8.2 Style Transfer

Youchuan V8.2 Blend

Youchuan V8.2 Image-to-Image

Youchuan V8.2 Text-to-Image

Seedream v5.0 Pro Edit

Seedream v5.0 Pro Text-to-Image

Nano Banana 2 Lite Edit Developer

One API for All Media AI.

INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values