Google recently launched their experimental AI Mode in Search, and as someone working on a BeeAI framework project with Flask as a front end, I wanted to compare how Google’s new offering stacks up against Perplexity when searching for Flask information.

Visual Comparison from the Screenshots

Google AI Mode Screenshot 1

Looking at the screenshots provided, both services offer information about Flask, but with notably different approaches:

Content Organization

Google AI Mode presents Flask information in a more traditional search-style format:

  • Clear section headers (Key Characteristics, Why Choose Flask?)
  • Paragraph-based explanations with contextual links
  • Wikipedia attribution clearly visible
  • A sequential reading experience similar to an article

Perplexity opts for a more structured presentation:

  • Bulleted lists for key features
  • Numbered lists for common use cases
  • More visual separation between concepts
  • A “Related” section at the bottom with additional Flask queries

Google AI Mode Screenshot 2

User Experience Differences

Google’s approach feels more like an enhanced search result, while Perplexity appears designed as a conversational AI tool from the ground up:

  • Google: Maintains its search DNA with a clean, information-focused layout
  • Perplexity: Embraces a chat-like interface with features like “Ask follow-up” and interactive buttons

Google’s New AI Mode: What We Now Know

Based on the pasted article, Google’s AI Mode:

  • Uses a custom version of Gemini 2.0
  • Employs “query fan-out” to issue multiple related searches concurrently
  • Combines AI capabilities with Google’s information systems
  • Targets complex, multi-part questions that previously required multiple searches
  • Is currently in Labs testing with Google One AI Premium subscribers

Comparative Strengths

Google AI Mode Strengths:

  • Integration with Google’s massive information systems
  • Real-time sources like Knowledge Graph
  • Familiar Google interface for longtime users
  • Potentially more comprehensive information breadth

Perplexity Strengths:

  • More interactive, conversation-oriented design
  • Excellent “Related” section that encourages topic exploration
  • Clean visual hierarchy with bulleted information
  • Features like “Export” and “Rewrite” for content manipulation

The “Related” section at the bottom of Perplexity’s interface is particularly useful. In the screenshot, it shows related queries like:

  • How does Flask compare to Django
  • What are some common use cases for Flask
  • Can you explain the concept of a microframework in Flask

This feature facilitates natural topic exploration without requiring you to formulate new searches manually—something that appears to be missing in Google’s current implementation.

Conclusion

While Google’s AI Mode brings powerful capabilities through Gemini 2.0 and Google’s vast information resources, Perplexity’s interface seems more purposefully designed for interactive AI research, particularly with its “Related” section that helps guide further exploration.

For a Flask front-end project, either tool would provide valuable information, but Perplexity’s structured format and exploration-friendly features might give it an edge for developers who want to quickly understand and navigate Flask concepts.

As Google continues to refine its AI Mode beyond this initial Labs release, it will be interesting to see if they incorporate more conversational features like Perplexity’s related queries section.