**Highlight 1:** Perplexity launches the Deep Research tool, performing exceptionally well in multiple benchmark tests, even surpassing models like Google Gemini Thinking, providing enterprise-level AI research report generation capabilities at a low price.
**Highlight 2:** Perplexity Deep Research excelled in the “Humanity’s Last Exam” test, outperforming most models but still slightly lagging behind OpenAI.
**Highlight 3:** Perplexity Deep Research offers a free version, making it more attractive compared to OpenAI’s high subscription fees.
**Perplexity Releases Deep Research**
AI companies are competing to launch deep research tools! On February 14, Perplexity announced the launch of its latest feature, “Deep Research,” joining the competitive landscape alongside Google and OpenAI. Google introduced a similar feature for its Gemini platform last December, while OpenAI launched its own research agent earlier this month, with all three companies even using the same name: Deep Research.
The goal of Deep Research is to provide more in-depth answers and verifiable citations to meet the needs of professional users. In a blog post announcing Deep Research, Perplexity noted that the feature “excels at a range of expert-level tasks—from finance and marketing to product research.”
Perplexity Deep Research is currently available on the web, and the company stated that it will soon be added to its applications for Mac, iOS, and Android to facilitate use by mobile users.
To use Perplexity Deep Research, simply submit a query in Perplexity and select “Deep Research” from the dropdown menu; it will generate a detailed report. The generated results can be exported as a PDF file or displayed directly within Perplexity.
Perplexity stated that Deep Research “iteratively searches, reads documents, and considers what to do next; as it learns more about the subject area, it continuously refines its research plan,” which is said to be “similar to how humans research new topics.”
**Slightly Behind OpenAI! Free users can “deep query” 5 times a day**
Perplexity AI also emphasized the performance of Deep Research in the Humanity’s Last Exam (a benchmark test containing expert-level questions across various academic fields; the higher the score, the closer it is to “general artificial intelligence”), achieving a score of 21.1%, easily surpassing most other models, such as Gemini Thinking (6.2%), Grok-2 (3.8%), and OpenAI’s GPT-4o (3.3%), only trailing behind OpenAI’s Deep Research (26.6%).
Perplexity Deep Research’s performance in the Humanity’s Last Exam, achieving a score of 21.1%.
Image / Perplexity
However, in the SimpleQA benchmark test, composed of thousands of factual questions, Perplexity Deep Research achieved an accuracy of 93.9%, far exceeding the performance of other leading models.
Perplexity Deep Research achieved an accuracy of 93.9% in the SimpleQA benchmark test.
Image / Perplexity
But what is most important to general consumers is that currently, to use OpenAI’s Deep Research, one still needs to subscribe to the Pro plan at $200 per month, even though OpenAI has indicated plans to expand to other subscription options; in contrast, Perplexity’s Deep Research is offered for free, allowing free users to make five free queries daily, while professional subscribers paying $20 per month can enjoy 500 queries daily and faster processing speeds.
Thankful for open source! We’re going to keep making this faster and cheaper. Knowledge should be universally accessible and useful. Not kept behind obscenely expensive subscription plans that benefit the corporates, but not in the interests of humanity! [https://t.co/mtG4oZhl4z](https://t.co/mtG4oZhl4z) pic.twitter.com/M1yHtXJKUe — Aravind Srinivas (@AravSrinivas) February 14, 2025
**What is the difference between Deep Research and regular search?**
To simply explain, the difference between deep search and regular search can be described as “the volume of data the AI reads.” According to a test conducted by Digital Times, when asking Perplexity, “Please find the top 3 largest ETFs in Taiwan’s stock market and compare their stock selection logic and performance over the past year,” the differences were quite significant.
In a regular search, Perplexity indeed cited data to identify the three largest Taiwan stock ETFs, namely Yuanta Taiwan 50 (0050), Cathay Sustainable High Dividend (00878), and Yuanta High Dividend (0056), but did not provide a discussion or data on “stock selection logic” and “performance over the past year.”
Perplexity’s regular search has limitations in the ability to query specific data.
Image / Perplexity
However, when switching to deep search, it generates a well-structured article, and it is evident that Perplexity breaks down the user’s question into more detailed inquiries to assist in content generation.
The results of deep search are evidently better.
Image / Perplexity
**Comparison of Perplexity, OpenAI, and Google**
When asked to “compare the three deep research products,” Perplexity outlined differences in technology, pricing models, and performance in various use cases and topics, summarized as follows:
– **Perplexity AI:** Utilizes iterative search and reasoning capabilities, enabling rapid generation of research reports, typically completed within 3 minutes. It excels at handling high-level professional tasks such as finance, marketing, and product research, suitable for preliminary research and quick information retrieval, applicable in fields like market analysis and technology trend reports.
– **OpenAI Deep Research:** More suitable for enterprise-level applications, providing in-depth analysis but requiring longer time (5 to 30 minutes) to complete reports, making it better suited for handling complex, challenging questions and for complex reasoning and professional field validation.
– **Google Gemini AI:** Compared to the other two, less detailed information about its Deep Research feature is publicly available, but it has integrated similar deep research tools, potentially advantaged by seamless integration with existing productivity ecosystems, although specific application scenarios remain unclear.
**Further Reading:** Behind the rapid growth of Taiwan’s unicorn Appier: “Only adding 2 employees a year” with the arrival of the AI revolution!
This article is collaboratively reprinted from: Digital Times
Editor: Li Xiantai
Source: Perplexity, TechChurch