Nano Banana Pro: Hands-on with the World’s Most Powerful Image Model

In this episode of Release Notes, Logan Kilpatrick and team members Robin, Elon, Abhishek, and Sherry from Google DeepMind's Nano Banana and Gemini image teams discuss the launch of Nano Banana Pro, built on Gemini 3 Pro. They highlight its advancements over the original Nano Banana model, particularly in text rendering, infographic generation, structured content creation, and visual reasoning. The team shares examples demonstrating the model's improved world knowledge, multi-turn capabilities, and character consistency. They also touch on the fusion of image understanding and generation, its potential applications in robotics, and the model's enhanced performance across multiple languages. The discussion covers the model's ability to generate infographics grounded with search and its potential integration with NotebookLM.

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Google AI: Release Notes

Introduction to Nano Banana Pro and its Enhanced Capabilities

Data, Training, and the Synergistic Relationship Between Image Generation and Understanding

Collaboration and Model Improvements: Visual Reasoning and Infographic Generation

Code Understanding and Visual Representation

Side-by-Side Comparison and Text Rendering Metrics

Infographics and Real-Time Data Integration

Accuracy and Multi-Modal Input Capabilities

Model Latency, Character Consistency, and Data Curation

Key Improvements and Style Transfer

Multi-Turn Generation and Conclusion

Nano Banana Pro: Hands-on with the World’s Most Powerful Image Model

Google AI: Release Notes

00:07Introduction to Nano Banana Pro and its Enhanced Capabilities

Introduction to Nano Banana Pro and its Enhanced Capabilities

04:07Data, Training, and the Synergistic Relationship Between Image Generation and Understanding

Data, Training, and the Synergistic Relationship Between Image Generation and Understanding

07:40Collaboration and Model Improvements: Visual Reasoning and Infographic Generation

Collaboration and Model Improvements: Visual Reasoning and Infographic Generation

11:13Code Understanding and Visual Representation

Code Understanding and Visual Representation

14:27Side-by-Side Comparison and Text Rendering Metrics

Side-by-Side Comparison and Text Rendering Metrics

17:44Infographics and Real-Time Data Integration

Infographics and Real-Time Data Integration

21:33Accuracy and Multi-Modal Input Capabilities

Accuracy and Multi-Modal Input Capabilities

25:08Model Latency, Character Consistency, and Data Curation

Model Latency, Character Consistency, and Data Curation

29:24Key Improvements and Style Transfer

Key Improvements and Style Transfer

32:14Multi-Turn Generation and Conclusion

Multi-Turn Generation and Conclusion