Perplexity vs Google AI

AI has changed the way we search for things online forever.

Instead of scanning through sources on a SERP (search engine results page), we now rely on AI summaries generated from the most useful links.

Some people simply ask ChatGPT. In simple scenarios, it works fine since AI chats now have access to web search tools. But they aren’t optimized for gathering diverse sources for each query and summarizing results into a “knowledge pillow.”

For quite a long time, the only effective AI search tool was Perplexity. However, Google has recently introduced its native AI search.

The flow with AI search tools is simple:

• you search for a specific query (in natural language or a more “Google” style)
• the agent finds relevant sources through web search and summarizes them while listing all used resources
• you can ask follow-up questions

Let’s compare Google AI and Perplexity.

Disclaimer: For comparison, I’m using Perplexity Pro. The free version is also very good, but the Pro version improves searches.

1. UX / UI

Both apps look relatively similar.

They are also both very fast with results, but Google AI feels smoother and faster - although it’s mostly just a perception.

The biggest difference is how the output is presented.
In Google AI’s result page, you see a minimalistic chat interface with a list of sources.
Perplexity, on the other hand, presents results like a notebook page with questions and answers. You can easily export a page with results to PDF, Markdown, or DOCX, or simply bookmark it to revisit later - something impossible with Google AI at the moment.

Perplexity is also more transparent. It directly shows which queries were used and what sources were analyzed.

2. Sources

Trash in = trash out. Even the most powerful AI agent and smartest LLM won’t provide decent results if the summarized sources are poor. So, picking the right sources is the most important part of the AI search process.

Google AI relies on the typical Google search engine, so the sources are similar to what you’d find by querying Google directly. Google AI just adds an LLM layer that analyzes your input and converts it into a few simpler queries.

Perplexity uses its own AI-powered search engine. It offers much more flexibility when it comes to sources. You can pick the type of sources you want to browse:

• Web (all pages, similar to Google)
• Academic papers
• Social
• SEC (Securities and Exchange Commission - official financial data)

This gives you flexibility in what data quality you expect. Some searches require academic resources, while others work better when verified through social discussions like Reddit.

Even when limited to “Web”, the sources differ from Google AI.
Google tends to prioritize large, well-known websites, as they are considered the most trustworthy. Perplexity often includes smaller blogs, niche sites, or even YouTube videos.

Another big difference is the number of sources used.
Google AI usually summarizes around 5 sources.
Perplexity Pro typically uses 20+ sources.
This can be both good and bad, so it’s hard to say which approach is better overall.

3. Additional Features

Google AI is mostly a lightweight wrapper around Google Search. It converts your question into multiple queries and summarizes the results using Gemini.

Perplexity, on the other hand, is a much more complex tool with tons of use cases and features:

• Deep Research + Labs
• Support for multiple LLMs (even with “thinking” mode) for agentic searches or source-free answers
• News section based on popular sources with the option to ask follow-up questions - great for learning and trend discovery
• Spaces - equivalent to Projects, where you can predefine prompts, sources, and input files for reusability
• Finance dashboard with US stocks, crypto data, and earnings call transcripts
• AI-based stock screener

4. Output Quality

Output quality is hard to measure and depends heavily on your use case and expectations.

When I first started using Google AI, it seemed better than Perplexity - especially since Perplexity occasionally produced weird responses back then.

Now, I’m mostly back to using Perplexity. Google AI is my go-to for simple searches, but if the topic is more complex, Perplexity usually performs better at finding resources hidden deeper in the web. This makes it more versatile.

Perplexity also shines with its model picker, allowing you to select the most suitable model for your specific use case.

5. Conclusion

For me, Perplexity currently wins - with more features, a more agentic and in-depth approach to searching, and built-in financial tools.

However, Google AI is still a big step forward for AI search and a sign that Google doesn’t want to fall behind.