ChatGPT can be a helpful research partner because it quickly brings together information from many sources, making it easier to explore ideas, spot patterns, and understand complex topics. By reasoning through context, citing sources, and producing clear, structured summaries, it helps turn open questions into well-defined insights.
There are two different ways to search the public internet with ChatGPT—search and deep research. Below is an explanation of both, and when to use each.
ChatGPT search allows ChatGPT to pull in the latest information from the internet directly into your conversations. This means you can go beyond ChatGPT’s built-in training knowledge and get up-to-date answers on things like current events, market trends, competitor activity, or niche details not included in its training data.
Instead of toggling between multiple browser tabs and summarizing information yourself, search brings those updates directly into ChatGPT, streamlining your research and saving you time. It also makes it easy to combine fresh web data with the reasoning and summarization power of ChatGPT models.
#### How to use search in a chat
1. Open a new chat in ChatGPT. 2. Ask a question that requires current or detailed information (e.g., _“What are the top three AI trends in healthcare in 2025?”_), or click Web Search from your tools menu. 3. Look for the small globe icon 🌐 next to the model’s response—this indicates that search was used. 4. Click the citation links in the response to review the original sources. 5. Follow-up with clarifying prompts, like _“Summarize this in 3 bullet points for executives”_ or _“Turn this into a customer-facing email draft.”_
#### Additional considerations
See more: OpenAI Help Center: ChatGPT search(opens in a new window)
Deep research in ChatGPT uses reasoning to quickly gather, summarize, and interpret extensive information from across the web, helping you answer complex questions more thoroughly than a standard web search.
Every output is designed to be documented, with clear citations to sources, making it easy to verify and reference the information. Deep research is also particularly effective at finding niche, non-intuitive information that would otherwise require reviewing many sources.
Unlike a traditional web search, deep research is agentic, meaning that it actively plans and carries out a multi-step research process—searching, evaluating sources, refining queries, and synthesizing findings—rather than simply returning a list of links.
#### How to use deep research in a chat
1. Open ChatGPT and select deep research from your tools menu
2. Ask a clear and detailed prompt. Include your topic, goal, timeframe, and key details. If deep research needs more context, it will automatically ask follow up questions.
* _I’m researching [topic] for [audience/decision/meeting]. Provide a report including recent key opportunities and risks, and 3-5 actionable insights._
3. Review your report
## Search vs. deep research
These features sound similar, but are best for different use cases. Below is a quick comparison of the two features:
SearchDeep research PurposeQuickly retrieve specific facts, documents, or recent information from the web or connected sources.Conduct multi-step, in-depth analysis on complex or ambiguous questions that require reasoning and synthesis across multiple sources. Typical use caseFind a recent press release, product spec sheet, news article, or a single data point (e.g., “What was the attendance at last year’s summer Olympics?”).Explore broader questions like “What factors influence attendance at large international sporting events?” or “How do different countries prepare for hosting the Olympics?” Depth of outputReturns concise results, direct answers, or links—similar to a smart web search.Produces long-form, evidence-backed summaries, often with citations, tradeoffs, and reasoning steps. SpeedFast—typically a few seconds.Slower—may take several minutes or more due to multi-step reasoning. FreshnessPrioritizes the latest available information; ideal for breaking news or time-sensitive data.Uses fresh sources when relevant but focuses on contextual understanding, not just recency. Complexity of questionBest for well-defined, specific queries.Best for open-ended, exploratory or strategic questions without a single right answer.
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