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The AI research space is getting crowded. Every few months, a new tool launches, promising to outperform competitors, save time, and deliver deeper insights. From OpenAI’s ChatGPT Deep Research to Google Gemini AI, Alibaba’s Qwen, Kimi K1.5 Loong Thinking, and even Microsoft Copilot’s Think Deeper feature, companies are in a race to develop the most powerful AI research assistant.
So, where does Perplexity Deep Research fit into this landscape? Is it just another AI tool, or does it bring something truly new? In this blog, we take a detailed, no-hype look at Perplexity Deep Research, how it works, how it compares, and whether it truly changes the research game.
Perplexity Deep Research is an AI-powered research assistant designed to provide detailed, structured reports on complex topics. Unlike traditional AI chatbots that summarize content or give quick answers, Deep Research performs multi-step analysis, simulating how a human researcher would approach a question.
While many AI tools claim to save time and improve research, Perplexity Deep Research has a few unique advantages:
With multiple AI research assistants available, how does Perplexity Deep Research stack up?
Perplexity Deep Research achieved a 21.1% accuracy score on Humanity’s Last Exam, performing much better than models like Gemini Thinking, o3-mini, o1, and DeepSeek-R1. Humanity’s Last Exam is a detailed test for AI systems with over 3,000 questions covering 100+ subjects, including math, science, history, and literature.
Image Source: Perplexity
Perplexity Deep Research scored 93.9% accuracy on the SimpleQA test, which includes thousands of fact-checking questions. This is much higher than other leading AI models.
Image Source: Perplexity
Perplexity Deep Research not only scores high on tests but also completes most research tasks in under 3 minutes, and we’re working to make it even faster!
Image Source: Perplexity
AI research tools always make big promises, better accuracy, faster results, and deeper insights. But do they actually deliver? Let’s break it down.
Deep Research helps anyone explore complex topics with expert-level analysis. It works well for subjects like finance, marketing, and technology. You can also use it for personal needs like health advice, product research, and travel planning. Here are some ways to use Deep Research on Perplexity.
Technology
Image Source: Perplexity
Healthcare
Image Source: Perplexity
Perplexity AI has rapidly gained traction, even as it faces legal disputes with major media companies regarding alleged unauthorized content use. In October 2024, News Corp and its subsidiaries, including The Wall Street Journal and The New York Post, filed a lawsuit claiming that Perplexity’s AI-driven search engine reproduces large portions of their content without proper authorization or compensation.
In response, Perplexity AI has initiated partnerships with publishers to create revenue-sharing agreements with outlets such as Time and Fortune, ensuring that media companies receive compensation when their content appears in AI-generated responses. This move reflects a broader industry shift where AI developers seek to balance technological advancements with intellectual property rights.
Perplexity Deep Research is a great fit for:
AI research tools are evolving at breakneck speed, each promising a new standard of intelligence and efficiency. Perplexity Deep Research offers a compelling blend of speed, accuracy, and transparency, challenging traditional search engines and AI assistants alike. But as AI-driven research becomes more sophisticated, a bigger question emerges:
Are we heading toward a future where AI becomes the ultimate research companion, or will its limitations always require human oversight?
While Perplexity closes many gaps, the evolution of AI research isn’t just about speed or citations, it’s about trust. As AI systems grow more advanced, the real challenge isn’t just generating information but ensuring that knowledge remains verifiable, ethical, and truly insightful.
The AI research race is far from over. Perplexity has made its mark, but the real question is: What comes next?
I have nearly five years of experience in content and digital marketing, and I am focusing on expanding my expertise in product management. I have experience working with a Silicon Valley SaaS company, and I’m currently at Arbisoft, where I’m excited to learn and grow in my professional journey.
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