OpenAI and Google have both recently introduced powerful AI agents designed to conduct in-depth research and analysis. These "Deep Research" capabilities promise to revolutionize how we gather and synthesize information online. But how do these two offerings stack up against each other? This article delves into the features, limitations, and potential use cases of OpenAI's Deep Research and Google's Gemini to provide a comprehensive comparison.
OpenAI's Deep Research
OpenAI's Deep Research is an AI-powered research tool integrated into ChatGPT. Described as an "agentic capability," it operates autonomously to analyze vast amounts of online data, including text, images, and PDFs, to generate comprehensive reports. It's also been described as the ChatGPT AI agent we've all been waiting for.
Features
Autonomous Research: Deep Research operates independently, requiring only a user prompt to initiate the research process.
Comprehensive Reports: It synthesizes information from various sources to create detailed reports comparable to those produced by human research analysts.
Source Citation: Every claim in the report is meticulously cited, ensuring transparency and facilitating verification.
Contextualization: Users can upload files and spreadsheets to provide context and guide the research process.
Efficiency: OpenAI claims Deep Research can complete tasks in "tens of minutes" that would take a human analyst hours or even days.
Accessibility: Deep Research is available through the ChatGPT web interface, with plans to expand to mobile and desktop apps.
Finding Specific Information: Deep Research can uncover hard-to-find information, such as identifying the exact episode of a TV show where a specific scene occurs, based on a user's description.
Feature | Description |
Autonomous Research | Operates independently based on a user prompt. |
Comprehensive Reports | Synthesizes information to create detailed reports. |
Source Citation | Provides citations for every claim in the report. |
Contextualization | Allows users to upload files to provide context. |
Efficiency | Completes tasks much faster than a human analyst. |
Accessibility | Available through ChatGPT web interface. |
Finding Specific Information | Can locate niche information, like specific scenes in TV shows. |
Limitations
Hallucinations: While generally reliable, Deep Research can sometimes generate inaccurate information or "hallucinate" facts.
Verbosity: Reports can be lengthy and repetitive, especially if the initial prompt lacks specificity.
Limited Control: Users have limited control over the research process once initiated.
Cost: Deep Research is currently only available to ChatGPT Pro subscribers, which costs $200 per month.
Geographic Restrictions: It is not yet accessible in the UK and the European Union.
Pricing
Deep Research is currently available as part of the ChatGPT Pro subscription, which costs $200 per month. OpenAI has indicated plans to make it available to ChatGPT Plus and Team users in the future.
User Reviews
Initial user reviews of OpenAI's Deep Research are mixed. Some users have praised its ability to uncover niche information and generate detailed reports, likening it to having a personal research department on call. Others have cautioned about the potential for hallucinations and the need to carefully verify the information presented. One user described it as "pretty neat" but advised treating the output with caution and following the provided links to ensure accuracy.
Use Cases
OpenAI suggests Deep Research can be used for various tasks, including:
Use Case | Description |
Competitive Analysis | Analyzing competitors in a specific market. |
Product Research | Finding and comparing products based on user needs. |
Investment Research | Gathering information and insights for investment decisions. |
Content Creation | Generating ideas and research for articles and other content. |
Personal Tasks | Finding information on topics of personal interest. |
Operator: Expanding Deep Research's Capabilities
OpenAI has also developed another AI agent called "Operator," which can take real-world actions based on user instructions. While Deep Research focuses on information gathering and analysis, Operator can perform tasks like making restaurant reservations or online shopping. The combination of Deep Research and Operator could potentially enable ChatGPT to carry out even more sophisticated tasks, such as conducting research to inform real-world actions.
Google's Gemini Deep Research
Google's Deep Research is an AI-powered research tool integrated into the Gemini web app. It leverages Google's vast knowledge base and search capabilities to provide comprehensive research reports. It's been described as a personal AI research assistant that can save users hours of time.
Features
Research Plan: Gemini creates a research plan outlining the steps it will take, allowing users to review and modify it before execution.
Integration with Google Services: Deep Research seamlessly integrates with other Google services, such as Google Docs, for easy export and sharing of reports.
Multimodal Capabilities: Gemini's underlying model, Gemini 2.0, supports multimodal input and output, including text, images, and audio.
Agentic Capabilities: Gemini is designed to be more than just a research tool, with the potential to evolve into a universal AI assistant. Deep Research is an early example of this agentic capability, showcasing how Gemini can tackle complex tasks and save users time.
1M Token Context Window: Gemini boasts a 1M token context window, allowing it to process and understand significantly larger amounts of text compared to other models. This enhances its ability to analyze and synthesize information from multiple sources.
Multi-step Question Handling: Gemini 2.0 is being integrated into AI Overviews in Google Search, enabling it to handle more complex, multi-step questions. This will allow users to perform more sophisticated searches and receive more comprehensive answers
Benchmarks
OpenAI's Deep Research has been evaluated on several benchmarks. Here's a summary of their performance:
Humanity's Last Exam: This benchmark, designed by experts, consists of 3,000 challenging reasoning problems. OpenAI's Deep Research significantly outperformed other models, achieving 26.6% accuracy. In comparison, DeepSeek R1 scored 9.1%, Google's Gemini Thinking scored 6.2%, and Grok 2 scored 3.8%.
GAIA Benchmark: This benchmark evaluates AI models on reasoning, multimodal fluency, web browsing, and tool use. OpenAI's Deep Research achieved state-of-the-art results, outperforming previous models. While DeepSeek R1 hasn't been specifically tested on GAIA, it excels in algorithmic problem-solving and scientific computation.
Simple Bench: One user tested OpenAI's Deep Research on their own benchmark, "Simple Bench," which focuses on spatial reasoning and common sense. However, the model repeatedly asked clarifying questions instead of answering directly.
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