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text-to-image

google/imagen3-fast

Google's highest quality text-to-image model, capable of generating images with detail, rich lighting and beauty

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Idle

A couple folding laundry together in a sunlit bedroom, casual clothes, sense of routine

Your request will cost $0.02 per run.

For $1 you can run this model approximately 50 times.

ExamplesView all

A cat sitting on a windowsill during a rainy afternoon, water droplets on glass, peaceful atmosphere
Busy Tokyo street at night, realistic pedestrians, cars, and signage, wet pavement reflections
Old European street with stone buildings and people dining outdoors, natural lighting, tourist snapshot vibe
Construction workers on a high-rise building at dawn, safety gear and realistic dust/light atmosphere
A couple grocery shopping together, smiling, in a brightly lit supermarket, candid realism
A young man tying his shoelaces on a city sidewalk in the morning, coffee in hand, realistic urban background
A woman brushing her teeth in a messy but cozy bathroom, foggy mirror, early morning light
A couple folding laundry together in a sunlit bedroom, casual clothes, sense of routine

README

Imagen 3

Imagen 3 is DeepMind’s latest text-to-image generative model, focusing on high-quality image generation with improved detail, lighting, and reduced artifacts.

Core Capabilities

  • Enhanced prompt understanding for complex image generation tasks

  • Improved text rendering for applications like presentations and typography

  • Support for diverse artistic styles from photorealism to animation

  • Better handling of lighting, textures, and fine details

  • Natural language prompt processing without requiring complex prompt engineering

Technical Improvements

Image Quality

  • Enhanced color balance and vibrancy

  • Improved texture rendering

  • Better detail preservation in complex scenes

  • Reduced artifact generation

  • More accurate style reproduction across different artistic genres

Prompt Processing

  • Support for longer, more detailed prompts

  • Better understanding of camera angles and composition requirements

  • Improved handling of specific style requests

  • Enhanced text rendering capabilities

Benchmarks

Performance metrics based on human evaluation using GenAI-Bench:

  • Highest score for visual quality among compared models

  • High accuracy in prompt response adherence

  • Strong performance in overall preference benchmarks

Detailed benchmark methodology and results are available in Appendix D of the technical report.

Security Features

  • Built-in content filtering system

  • Dataset filtering to minimize harmful content

  • SynthID watermarking integration for image identification

  • Extensive red teaming and evaluations for: Fairness, Bias, Content safety

Technical Documentation

For detailed technical specifications and methodology, refer to the full technical report.