OmniGen is a unified image generation model that can generate a wide range of images from multi-modal prompts. It can be used for various tasks such as Image Editing, Personalized Image Generation, Virtual Try-On, Multi Person Generation and more!

fal-ai/omnigen-v2

Inference

Commercial use

Schema

LLMs

Playground API

SandboxOpen in Sandbox

Input

Prompt*

Additional Settings

Customize your input with more control.

Result

Idle

What would you like to do next?

fal-ai/omnigen-v2

Schema

LLMs

Input

Prompt*

Additional Settings

Customize your input with more control.

Result

Idle

What would you like to do next?

Input

Prompt*

Input Image Urls

Hint: Drag and drop files from your computer, images from web pages, paste from clipboard (Ctrl/Cmd+V), or provide a URL.

1 image added

Additional Settings

Customize your input with more control.

Your request will cost $0.15 per megapixel.

or try similar models free in Sandbox

Result

Idle

What would you like to do next?

Your request will cost $0.15 per megapixel.

Readme

OmniGen V2: Advanced AI Image Generation

Transform your creative vision into stunning images with OmniGen V2, a unified image generation model that handles multiple tasks within a single framework, from text-to-image generation to complex image editing.

Overview

OmniGen V2 delivers exceptional image generation capabilities through an intuitive API. Whether you're building a creative application, generating marketing assets, or exploring AI art, OmniGen V2 provides a unified approach that eliminates the need for additional modules like ControlNet or IP-Adapter.

Key Features

Transform text descriptions into high-quality images with advanced capabilities:

Unified Framework

Text-to-image generation, image editing, and personalized generation in one model
No need for additional modules or preprocessing steps
Supports multi-modal prompts with text and image inputs

Versatile Applications

Image editing with natural language instructions
Personalized image generation using reference images
Virtual try-on capabilities
Multi-person generation
Subject-driven generation

Developer Experience

Simple REST API with comprehensive SDKs
Support for up to 3 input images
Extensive documentation and examples

Getting Started

Getting up and running with OmniGen V2 takes just a few minutes. Here's how:

Install the SDK for your platform:

JavaScript/TypeScript:

bash
npm install --save @fal-ai/client

Python:

bash
pip install fal-client

Configure your credentials:

JavaScript:

javascript
import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Python:

python
import fal_client
import os

os.environ["FAL_KEY"] = "YOUR_FAL_KEY"

Generate your first image:

JavaScript:

javascript
const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "A serene mountain landscape at sunset, photorealistic style"
  }
});

Python:

python
result = fal_client.subscribe("fal-ai/omnigen-v2", {
    "prompt": "A serene mountain landscape at sunset, photorealistic style"
})

Advanced Usage

Image Editing with Reference Images

javascript
const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "Make the dress blue",
    input_image_urls: ["https://your-image-url.jpg"]
  }
});

Multi-Image Generation

javascript
const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "Add the bird from image 1 to the desk in image 2",
    input_image_urls: [
      "https://bird-image.jpg",
      "https://desk-image.jpg"
    ]
  }
});

API Parameters

Input Parameters:

prompt (required): Text description for generation or editing
input_image_urls: Array of up to 3 image URLs for editing/reference
image_size: Output size (default: "square_hd")
- Options: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
num_inference_steps: Number of denoising steps (default: 50)
text_guidance_scale: Controls prompt adherence (default: 5)
image_guidance_scale: Controls reference image influence (default: 2)
negative_prompt: Elements to avoid in generation
scheduler: Sampling method (default: "euler")
num_images: Number of images to generate (default: 1)
enable_safety_checker: Enable content filtering (default: true)
output_format: Image format (default: "jpeg")

Queue-Based Processing

For asynchronous generation:

javascript
// Submit request
const { request_id } = await fal.queue.submit("fal-ai/omnigen-v2", {
  input: {
    prompt: "Your prompt here"
  },
  webhookUrl: "https://optional.webhook.url/for/results"
});

// Check status
const status = await fal.queue.status("fal-ai/omnigen-v2", {
  requestId: request_id,
  logs: true
});

// Get result
const result = await fal.queue.result("fal-ai/omnigen-v2", {
  requestId: request_id
});

Best Practices

Maximize the quality of your generations with these proven approaches:

Write Effective Prompts

Use specific language for multi-image tasks (e.g., "Add the X from image 1 to Y in image 2")
Be descriptive about style, mood, and technical details
Include negative prompts to avoid unwanted elements

Optimize Parameters

Adjust text_guidance_scale (1-20) for prompt adherence
Use image_guidance_scale (1-10) to control reference image influence
Higher inference steps (50-100) generally improve quality

Handle Results Properly

Implement proper error handling for API responses
Use the file storage API for uploading local images
Monitor usage through the fal.ai dashboard

File Upload Support

Upload local images for editing or reference:

javascript
import { fal } from "@fal-ai/client";

const file = new File([imageData], "image.jpg", { type: "image/jpeg" });
const url = await fal.storage.upload(file);

const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "Edit this image",
    input_image_urls: [url]
  }
});

Technical Specifications

Model Architecture

Based on unified diffusion technology
Simplified architecture without additional text encoders
Supports arbitrarily interleaved text and image inputs

Performance

Fast inference times
Supports various output resolutions and aspect ratios
Automatic safety checking

Integration Options

Native SDKs for JavaScript and Python
Direct HTTP API access
Webhook support for async processing

Pricing and Usage

Cost: $0.15 per megapixel
Transparent, usage-based pricing
No subscription necessary
No hidden fees or minimum commitments

View detailed pricing or contact sales for enterprise solutions.

Support and Resources

We're here to help you succeed with OmniGen V2:

Documentation

API Documentation
General fal.ai Documentation
Code examples in multiple languages

Community and Support

Active developer community
Direct email support
Regular model updates

Get started with OmniGen V2 today and experience the power of unified image generation. Create your API key at fal.ai to begin generating amazing images with our API.

Readme

OmniGen V2: Advanced AI Image Generation

Overview

Key Features

Transform text descriptions into high-quality images with advanced capabilities:

Unified Framework

Text-to-image generation, image editing, and personalized generation in one model
No need for additional modules or preprocessing steps
Supports multi-modal prompts with text and image inputs

Versatile Applications

Image editing with natural language instructions
Personalized image generation using reference images
Virtual try-on capabilities
Multi-person generation
Subject-driven generation

Developer Experience

Simple REST API with comprehensive SDKs
Support for up to 3 input images
Extensive documentation and examples

Getting Started

Getting up and running with OmniGen V2 takes just a few minutes. Here's how:

Install the SDK for your platform:

JavaScript/TypeScript:

bash
npm install --save @fal-ai/client

Python:

bash
pip install fal-client

Configure your credentials:

JavaScript:

javascript
import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Python:

python
import fal_client
import os

os.environ["FAL_KEY"] = "YOUR_FAL_KEY"

Generate your first image:

JavaScript:

javascript
const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "A serene mountain landscape at sunset, photorealistic style"
  }
});

Python:

python
result = fal_client.subscribe("fal-ai/omnigen-v2", {
    "prompt": "A serene mountain landscape at sunset, photorealistic style"
})

Advanced Usage

Image Editing with Reference Images

javascript
const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "Make the dress blue",
    input_image_urls: ["https://your-image-url.jpg"]
  }
});

Multi-Image Generation

javascript
const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "Add the bird from image 1 to the desk in image 2",
    input_image_urls: [
      "https://bird-image.jpg",
      "https://desk-image.jpg"
    ]
  }
});

API Parameters

Input Parameters:

prompt (required): Text description for generation or editing
input_image_urls: Array of up to 3 image URLs for editing/reference
image_size: Output size (default: "square_hd")
- Options: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
num_inference_steps: Number of denoising steps (default: 50)
text_guidance_scale: Controls prompt adherence (default: 5)
image_guidance_scale: Controls reference image influence (default: 2)
negative_prompt: Elements to avoid in generation
scheduler: Sampling method (default: "euler")
num_images: Number of images to generate (default: 1)
enable_safety_checker: Enable content filtering (default: true)
output_format: Image format (default: "jpeg")

Queue-Based Processing

For asynchronous generation:

javascript
// Submit request
const { request_id } = await fal.queue.submit("fal-ai/omnigen-v2", {
  input: {
    prompt: "Your prompt here"
  },
  webhookUrl: "https://optional.webhook.url/for/results"
});

// Check status
const status = await fal.queue.status("fal-ai/omnigen-v2", {
  requestId: request_id,
  logs: true
});

// Get result
const result = await fal.queue.result("fal-ai/omnigen-v2", {
  requestId: request_id
});

Best Practices

Maximize the quality of your generations with these proven approaches:

Write Effective Prompts

Use specific language for multi-image tasks (e.g., "Add the X from image 1 to Y in image 2")
Be descriptive about style, mood, and technical details
Include negative prompts to avoid unwanted elements

Optimize Parameters

Adjust text_guidance_scale (1-20) for prompt adherence
Use image_guidance_scale (1-10) to control reference image influence
Higher inference steps (50-100) generally improve quality

Handle Results Properly

Implement proper error handling for API responses
Use the file storage API for uploading local images
Monitor usage through the fal.ai dashboard

File Upload Support

Upload local images for editing or reference:

javascript
import { fal } from "@fal-ai/client";

const file = new File([imageData], "image.jpg", { type: "image/jpeg" });
const url = await fal.storage.upload(file);

const result = await fal.subscribe("fal-ai/omnigen-v2", {
  input: {
    prompt: "Edit this image",
    input_image_urls: [url]
  }
});

Technical Specifications

Model Architecture

Based on unified diffusion technology
Simplified architecture without additional text encoders
Supports arbitrarily interleaved text and image inputs

Performance

Fast inference times
Supports various output resolutions and aspect ratios
Automatic safety checking

Integration Options

Native SDKs for JavaScript and Python
Direct HTTP API access
Webhook support for async processing

Pricing and Usage

Cost: $0.15 per megapixel
Transparent, usage-based pricing
No subscription necessary
No hidden fees or minimum commitments

View detailed pricing or contact sales for enterprise solutions.

Support and Resources

We're here to help you succeed with OmniGen V2:

Documentation

API Documentation
General fal.ai Documentation
Code examples in multiple languages

Community and Support

Active developer community
Direct email support
Regular model updates

Get started with OmniGen V2 today and experience the power of unified image generation. Create your API key at fal.ai to begin generating amazing images with our API.