Comparing the Deep Research Tools

Disclosure: This blog post was written by ChatGPT based on prompts and information that I gave it as a way to test how well it could approximate my writing voice. To read about how well it did, check out Putting My AI Ghost Writer to the Test, which I wrote.

Comparing OpenAI Deep Research, Gemini Deep Research, and Perplexity Deep Research: Which One Delivers True Insight?

In the fast-moving world of AI-assisted research, deep research tools promise to save us time, synthesize vast amounts of information, and provide meaningful insights. But how deep do they really go?

I recently tested OpenAI Deep Research, Gemini Deep Research, and Perplexity Deep Research to see how well each tool could surface, synthesize, and analyze complex topics. My goal was to determine which model produces the most valuable research reports and which is best suited for different use cases.

Here’s what I found.

Key Findings: OpenAI Delivers True Deep Research

Each of these tools is designed to scour the web, pull together sources, and generate a research report. But not all deep research models are created equal.

• OpenAI Deep Research provided the most in-depth responses and the most thoughtful research report. Instead of simply summarizing sources, it felt like it had a point of view—almost as if an expert had done the work and was synthesizing insights based on deep analysis. It wasn’t just a list of findings; it was a structured, insightful document that helped advance my thinking rather than just giving me an overview.

• Gemini Deep Research and Perplexity Deep Research performed similarly to each other. Both provided solid overviews with links to explore further, but they didn’t quite reach the same depth as OpenAI. The reports felt more like a well-organized summary of information rather than a true research report. They were great for quickly getting up to speed on a topic, but they lacked the deeper synthesis and analysis that OpenAI produced.

Use Cases: Which Tool Should You Use?

Depending on how much depth you need, each model has strengths:

• If you need a quick but credible summary with a well-curated list of sources, Gemini or Perplexity are great options. They efficiently aggregate information and provide a solid starting point.

• If you need a truly in-depth research report that pushes your thinking forward, OpenAI Deep Research is the better choice. It goes beyond summarization and creates something that feels more expert-driven, which is useful when trying to form a point of view on a topic.

Limitations: AI Research Still Requires Human Oversight

While all three tools are impressive in their ability to pull together research, they share one critical limitation: hallucinated sources and information.

Each model, at times, referenced sources that didn’t exist or misrepresented the content of articles. This means that no matter which tool you use, fact-checking is essential. Blindly using any AI-generated research report without verifying its accuracy is risky.

Final Verdict: Which One is Best?

For actual deep research, OpenAI’s model is my preferred choice. It produces reports that are structured, insightful, and genuinely useful for advancing thinking on a topic.

For those who simply need a well-organized summary and a collection of relevant sources, both Gemini and Perplexity are strong options. They efficiently pull together information and provide a reliable starting point for further exploration.

Bottom Line:

• For serious research that requires deep synthesis? Go with OpenAI Deep Research.
• For quick, credible overviews with useful links? Gemini and Perplexity will do the job.
• Regardless of the model, always fact-check the sources.

As AI research tools continue to evolve, it will be interesting to see how each platform refines its approach. For now, OpenAI seems to be leading in terms of producing true deep research, but all three tools offer value depending on your needs.