Two prominent players, OpenAI and xAI, have introduced advanced research tools aimed at enhancing the capabilities of their respective AI models—ChatGPT and Grok 3. OpenAI's Deep Research function and xAI's DeepSearch function represent the latest efforts to transform chatbots into powerful research assistants. These tools have sparked widespread discussion among AI enthusiasts, researchers, and professionals about their strengths, limitations, and overall effectiveness.

What Are These Tools?

OpenAI unveiled its Deep Research function earlier this month, describing it as an autonomous agent capable of executing complex, multi-step research tasks. Built on a specialized version of the o3 reasoning model, this tool is engineered to scour the internet, process data, and deliver detailed reports complete with citations and a summary of its methodology. It targets users engaged in intensive knowledge work, such as those in finance, science, and policy, but is also marketed for everyday research needs like product comparisons.

Meanwhile, xAI launched Grok 3’s DeepSearch function on February 17, branding it as a reasoning-based chatbot feature that leverages real-time data, particularly from the X platform. Integrated into the Grok 3 model, which boasts over ten times the compute power of its predecessor, DeepSearch aims to provide concise, citation-supported answers for a broad range of queries, from current events to technical questions. Both tools signal a shift toward AI agents that go beyond simple text generation, but their approaches and outcomes differ significantly.

Design and Functionality

The design philosophies behind Deep Research and DeepSearch reveal distinct priorities. OpenAI’s Deep Research operates as a thorough, deliberate investigator. It takes between 5 and 30 minutes to complete a task, navigating multiple online sources and synthesizing findings into structured, in-depth reports. Users can upload files like PDFs or spreadsheets to provide context, and the tool promises transparency by documenting its process in a sidebar, complete with citations. OpenAI emphasizes precision and reliability, targeting professionals who need comprehensive analyses.

In contrast, xAI’s DeepSearch prioritizes speed and breadth. Typically completing queries in just a few minutes, it draws heavily on real-time X posts and web data to deliver concise summaries. It offers options for research, brainstorming, and data analysis, and while it provides citations, its reports are less detailed than those of Deep Research. The integration with X gives it an edge in accessing up-to-the-minute information, making it appealing for users tracking trends or breaking news.

Performance and Accuracy

Performance is a critical metric in evaluating these AI tools, and both have strengths and weaknesses. OpenAI claims its Deep Research model, powered by an enhanced o3 variant, achieves superior accuracy on complex tasks. On the Humanity’s Last Exam benchmark—a test of expert-level questions—OpenAI reports a score of 26.6% with browsing and Python tools enabled, far surpassing its earlier GPT-4o model’s 3.3%. However, the company acknowledges that Deep Research can still produce errors, such as hallucinations or incorrect inferences, particularly when distinguishing rumours from verified facts.

Grok 3’s DeepSearch, built on a model that xAI touts as outperforming competitors in math, science, and coding benchmarks, has impressed early users with its speed and relevance. During its livestream debut, xAI showcased DeepSearch generating a 1300-word report in just over a minute, a feat that highlights its efficiency. Yet, its accuracy has drawn scrutiny. Some users report that while it excels at summarizing broad topics, it occasionally cites dubious sources or overlooks nuance, raising questions about its reliability for in-depth research.

AI expert Andrej Karpathy, a former OpenAI co-founder, offered an early assessment of DeepSearch, suggesting it operates “approximately around Perplexity’s DeepResearch offering” but falls short of OpenAI’s Deep Research in thoroughness and dependability, indicating that OpenAI’s tool retains an advantage in rigorous analysis.

Accessibility and Cost

Accessibility shapes how widely these tools can be adopted. OpenAI’s Deep Research was initially available only to ChatGPT Pro subscribers at US$200 per month, with a limit of 120 queries. However, OpenAI has recently extended limited access to Plus (US$20/month), Team, Edu, and Enterprise users, who receive 10 queries per month.

Grok 3’s DeepSearch is integrated with the X ecosystem. It is available to Premium+ subscribers, with the subscription price recently increased from $22 to $40 per month. Additionally, the new SuperGrok subscription tier has been officially launched, offering unlimited access to advanced reasoning tools and DeepSearch for $30 per month or $300 per year. On February 19, Elon Musk announced a temporary free access period for Grok 3, though the duration of this offer was not specified. This integration with X enhances accessibility for active users, though the recent price increase may affect affordability for some.

[Read More: OpenAI Launches ChatGPT-4o with Canvas: A New Era of User Experience]

Strengths and Limitations

Each tool shines in specific scenarios. OpenAI’s Deep Research excels in depth and structure, making it ideal for academic, scientific, or professional research requiring detailed insights. Its ability to handle uploaded files and produce well-documented reports sets it apart for users who prioritize precision over speed. However, its longer processing times and higher cost may deter casual users or those needing quick answers.

Grok 3’s DeepSearch stands out for its agility and real-time focus. Its rapid responses and use of X data make it a strong contender for journalists, marketers, or anyone tracking current events. Yet, its lighter analysis and occasional accuracy issues limit its effectiveness for complex, niche, or highly technical inquiries where exhaustive exploration is essential.

Which Is Better?

Determining a clear winner depends on the user’s needs. For intensive, specialized research, OpenAI’s Deep Research appears superior due to its depth, transparency, and robust reasoning capabilities. Its higher accuracy on tough benchmarks and focus on verifiable outputs give it an edge for professionals who can afford the premium tier. However, its slower pace and cost may not suit all.

For fast, broad, and accessible research, Grok 3’s DeepSearch takes the lead. Its speed, affordability, and real-time data integration make it a practical choice for users seeking timely insights or overviews, even if it sacrifices some depth and reliability. As one observer trending on X noted, “Deep Research offers more depth, less breadth; DeepSearch offers less depth, more breadth”—a succinct summary of their trade-offs.

Combining the Best of Both Worlds

The rivalry between OpenAI’s ChatGPT Deep Research and xAI’s Grok 3 DeepSearch underscores the diverse paths AI development is taking. OpenAI’s tool leans into meticulous, high-stakes research, while xAI’s offering embraces speed and immediacy. Neither is definitively “better” in an absolute sense; their value hinges on context. For users with sufficient funding, there’s no need to choose between OpenAI’s ChatGPT Deep Research and xAI’s Grok 3 DeepSearch—why not harness both? By leveraging Deep Research’s meticulous, in-depth analysis alongside DeepSearch’s rapid, broad-reaching insights, users can achieve a rare blend of precision and immediacy. A practical approach is to start with DeepSearch for a quick overview, capturing real-time trends and key talking points from X and the web. Then, feed its summary into Deep Research as a contextual file, prompting it to expand on critical areas with detailed exploration and verified sources.

To combine the outputs, create a unified report: use DeepSearch’s concise findings as an executive summary or introductory section, followed by Deep Research’s comprehensive breakdown, complete with citations, for a document that offers both an accessible snapshot and exhaustive depth. This hybrid strategy, while resource-intensive, could set a new standard for AI-assisted research in 2025.

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Source: SentiSite, Tech Crunch, IBM, Business Insider, Yahoo! News, Unite.ai

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6 Mar 2025