At the beginning of the year, most people (including me) could see that we were on the verge of an AI explosion. The growing competition and new releases were tell-tale signs. That prediction is quickly becoming a reality. In a recent article, I compared DeepSeek vs. OpenAI, and today, I’ll be breaking down Perplexity Deep Research vs OpenAI Deep Research.
Like most AI tools, the main differences between OpenAI Deep Research vs Perplexity Deep Research boil down to speed, cost, accuracy, and ideal use cases.
Perplexity is fast, especially for a deep research tool. It wraps up research in about three minutes, while OpenAI takes between 7 and 20 minutes.
In tests and user examples, Perplexity sometimes hallucinates or provides inaccurate answers. OpenAI is also not entirely accurate but is largely more reliable for now.
Regarding cost, Perplexity has a free tier, while OpenAI Deep Research is only available at $200 per month. Perplexity’s paid version, the Pro, only costs $20/month.
So, which one should you use? I’ll answer that question and more in this article.
Perplexity Deep Research is a relatively new entrant, launched on February 14, 2025, just two weeks after OpenAI’s release. What makes this new tool different from the Auto version? Perplexity AI’s CEO, Aravind Srinivas, described it as a tool designed to provide “expert-level research on any topic.”
According to Perplexity, its Deep Research tool can tackle subjects across finance, marketing, health, travel planning, and more. So, I tested Perplexity’s Auto and Deep Research models on a finance topic using the same query for both models.
My Prompt: Analyze the impact of interest rate hikes on the U.S. stock market in 2024, including sector-wise effects and expert predictions. Use the most recent stats and also include comments from industry experts.
Here are the results of both responses side by side:
My Results:
One of my favorite features is how it inserts citations directly after each sentence or phrase. This makes it so much easier to cross-check sources and spot inaccuracies, a major plus when conducting data-heavy research.
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Perplexity Deep Research uses a proprietary framework called Test Time Compute (TTC) expansion, which enables a systematic and dynamic exploration of complex topics. Unlike traditional search engines that serve up static results, Perplexity’s architecture mirrors human cognitive processes—it iteratively refines its understanding through multiple analysis cycles.
The system starts by breaking down the query into subcomponents. Then, it autonomously runs dozens of web searches, evaluates hundreds of sources, and synthesizes findings using probabilistic reasoning models.
One of the things I find impressive is its parallelized data ingestion and hierarchical summarization techniques. These allow it to generate reports in two to four minutes. Sure, that’s longer than a quick chatbot response, but it’s still remarkably fast when I think about how long I’d spend researching the same topic, clicking through pages, cross-referencing studies, and double-checking sources. Moreover, I don’t expect deep research tools to be as fast as chatbots, at least not for now. Maybe in the future.
Perplexity Deep Research can resolve contradictions in information, detect emerging trends, and prioritize authoritative sources. This level of sophistication is reflected in its 21.1% score on “Humanity’s Last Exam,” a benchmark designed to test AI’s ability to tackle complex, high-stakes reasoning problems.
Another thing I appreciate is Perplexity AI’s commitment to accessibility. It operates on a freemium model, where non-subscribers can run a limited number of daily queries, while Pro users ($20/month) get unlimited access. This is such a great way to democratize access to Deep Research tools.
The tool is currently available on the Perplexity website, but iOS, Android, and Mac versions are coming soon, which I’ll be watching.
OpenAI’s Deep Research is positioned as an advanced AI agent designed to conduct autonomous research, synthesize knowledge, and generate in-depth reports. It runs on a customized version of OpenAI’s o3 model, optimized for web browsing, data analysis, and multi-step reasoning. So, basically, it’s built to think through complex research topics rather than just retrieve information.
It officially launched on February 2, 2025, and as of February 12, 2025, it’s available to all Pro users across web, iOS, Android, macOS, and Windows.
One of the standout stats I noticed is that OpenAI Deep Research scored 26.6% on “Humanity’s Last Exam,” which puts it ahead of Perplexity’s 21.1%—suggesting a stronger ability to reason through complex questions.
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Check out this OpenAi and Perplexity comparison on their Humanity’s Last Exam benchmark via Perplexity’s website:
The best choice between Perplexity Deep Research vs OpenAI Deep Research depends on your needs:
I wouldn’t recommend relying on either tool for legal reports. But that’s just my take: these fields require absolute accuracy, and no AI research tool, no matter how advanced, can fully guarantee that yet.
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Perplexity is faster, more affordable, and accessible, while OpenAI is more accurate, detailed, and expensive. OpenAI scored 26.6% on “Humanity’s Last Exam”, outperforming Perplexity’s 21.1%, making it better for high-stakes research. However, Perplexity’s inline citations and speed make it a great alternative to Google searches and manual research.
Yes, Perplexity follows a freemium model. You get limited free queries, but unlimited access costs $20/month.
OpenAI Deep Research costs $200/month, with a limit of 100 queries per month.
There are a few alternatives to these two deep research tools, including Google’s Deep Research, Hugging Face’s open-source deep research tool, and Open Deep Research, which already has over 13K stars on GitHub.
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