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ChatGPT search vs. Google: How do they differ?

By Sean Michael Kerner

For the past two decades, the Google search engine has been the de facto standard for internet search. That dominant position has been challenged in recent years by the emergence of an entirely different approach to knowledge-based search discovery: ChatGPT.

When ChatGPT arrived in November 2022, it introduced a very different experience for users with questions. While traditional search engines dispense a list of links in response to a query, ChatGPT provides answers.

In October 2024, ChatGPT introduced ChatGPT search, which delivers updated, live information -- something missing from its original version. And Google hasn't been idle either. With Google AI Overviews, the search giant integrated generative AI capabilities into its search, providing users with summaries and answers to content queries.

Both ChatGPT and Google are also exploring additional AI-powered approaches to search. One of the approaches is known as deep research. With the deep research approach, reasoning models, such as OpenAI's o3 and Google Gemini 2.0 are used to enable a more comprehensive, detailed approach to search.

How does ChatGPT search work?

The original ChatGPT based its service entirely on knowledge collected by a large language model (LLM) through a training phase. The regular version of ChatGPT has a knowledge cutoff date -- based on when training of its underlying model was completed -- and is unaware of information or events after that date.

ChatGPT search ignores that knowledge cutoff, operating through a combination of technologies, with its foundation built on a specially fine-tuned version of OpenAI's GPT-4o LLM. OpenAI enhanced this base model using post-training techniques, particularly by distilling outputs from its o1-preview model. The OpenAI o1 model is specifically noted for its improved reasoning capabilities, underpinning its more refined and accurate search experience, according to the vendor.

To access information beyond the LLM's training cutoff, ChatGPT search integrates information from additional sources, including the following:

• Third-party search providers. ChatGPT search uses third-party search providers such as Microsoft Bing.
• Media partnerships. Additionally, ChatGPT search incorporates content feeds from numerous media partners, including The Associated Press, Reuters and Financial Times.

The ChatGPT search service processes user queries through a natural language interface and maintains context across multiple questions, building interactions that are more conversational and intuitive. Beyond simply returning links, ChatGPT search provides concise summaries of information as well as source links.

What are the functional distinctions between ChatGPT search and Google Search?

ChatGPT search and Google Search take divergent paths to provide results to user queries.

• Interface. ChatGPT offers users a conversational AI interface, where users ask questions in a more back-and-forth approach. When engaged with Google's traditional search engine, users type in terms and don't have conversation interactions with the search engine.
• Follow-ups. ChatGPT's conversational AI approach typically maintains context far better than Google's during follow-up questions that dive into a specific topic.
• Information processing. By default, ChatGPT search summarizes information that responds directly to a user query. The core Google Search model doesn't summarize information; it relies on its own set of complex Google algorithms to rank and display relevant results. However, Google AI Overviews offers summarized responses that answer questions as well.
• Real-time information. ChatGPT search has limited real-time capabilities through its partnerships and third-party providers. Google continuously crawls and indexes the web, providing more up-to-date information across a variety of topics.
• Results format. Google Search provides a list of links that includes webpages, images, videos and featured snippets. While Google AI Overviews does enhance some search results with summarized information and source links, ChatGPT delivers detailed, paragraph-style responses that also include links to cited sources.

Key differences between Google Search and ChatGPT search

The following chart details the important differences between Google Search and ChatGPT search.

Feature	Google Search	ChatGPT search
Core technology	Google algorithms	GPT-4o LLM
Information source	Real-time web crawling	Pretrained data set plus limited real-time search
User interface	Query-based search box	Conversational chatbot
Results format	List of links with snippets	Coherent, conversational responses
Context handling	Limited	Maintains context across multiple queries
E-commerce integration	Product listings and price comparisons	Limited product information
Citation method	Links to sources	Inline citations with source links

What are the limitations of ChatGPT search compared with Google Search?

Despite its advancements, ChatGPT search faces several limitations when compared with Google Search, including the following:

• Information access and data scope. Google Search has a massive index of information thanks to its decades-old web crawler. ChatGPT has neither that lineage nor access to the internet's total volume of information.
• Real-time information. While ChatGPT search provides some real-time capabilities, it trails Google in providing the most up-to-date information across various topics.
• Accuracy concerns. A persistent issue with LLMs in general is the risk of AI hallucinations. Though that risk persists with Google AI Overviews, it is less likely to occur due to its web crawling process.
• Verification challenges. While ChatGPT search provides citations, verifying a source's accuracy and credibility is more challenging compared with Google's established page ranking system.

ChatGPT search pros and cons

There are some key advantages and limitations of ChatGPT search.

Pros

• Natural language understanding for intuitive queries.
• Contextual awareness for follow-up questions.
• Detailed explanations and summaries.
• Potential for creative and analytical tasks.
• Conversational AI for a more engaging user experience.

Cons

• Limited access to real-time information.
• Generating inaccurate responses at times.
• Narrower scope of information compared with traditional search engines.
• Lack of visual search capabilities.
• Biases inherited from training data.

Google Search pros and cons

Google also has its key advantages and limitations.

Pros

• Massive index of webpages crawled across decades for a deep level of search results.
• Real-time information updates that span multiple categories.
• Integration of various media types, including images, videos and maps.
• Google algorithms' higher degree of assurance and authenticity for ranked, relevant results.

Cons

• Less conversational interface.
• Overwhelming amount of information presented at times.
• Less user-friendly information summaries, though Google AI Overviews narrows that gap.
• Limited ability to understand complex, contextual queries.

Deep Research with Google and ChatGPT for reasoning-based search

With the advent of reasoning models, there is another level of comparison and competition to consider between Google and ChatGPT.

Reasoning models -- which include OpenAI's o1 and o3 models as well as Google's Gemini 2.0 -- provide a different level of output. The basic idea is that the model will reason -- or think through the various steps requested by a user prompt -- to generate an output.

With the reasoning models, it is possible to execute a more detailed level of search. Both Google and OpenAI refer to the reasoning-based search as deep research. The basic idea behind a deep research search is that the model will reason through the steps to find and assemble the best content response to a specific user query.

The level of detail in a deep research response is greater than what a nonreasoning-based model search provides, as the models attempt to better understand what the prompt is asking and reason through identifying and presenting the best results.

	OpenAI deep research	Google Deep Research
Model	Based on o3	Based on Gemini 2.0 Flash experimental
Process	Uses a reinforcement learning approach Plans and executes multistep search Searches over files and images Generates detailed report	Creates a research plan that the user needs to approve Conducts an iterative search to find information Generates report
Availability	ChatGPT Pro users	Gemini Advanced subscribers

Can ChatGPT search replace Google Search?

The simple answer is no. ChatGPT is not a full replacement for Google Search, at least in the short term.

There are many reasons that Google remains the dominant search engine on the internet. Google effectively serves its users' needs. Its web crawling approach to information collection easily outstrips ChatGPT's service. Even with its large training data set and media partnerships, ChatGPT search can't match Google's whole-internet access. For an entire generation of internet users, Google Search is the default way to find an answer -- and that's not something easily replaced.

It doesn't mean ChatGPT won't displace Google for some kinds of searches. Users looking for direct answers to queries -- quickly -- are well served by the ChatGPT interface. But it won't replace Google anytime soon. How ChatGPT search evolves, of course, will determine if it narrows the gap with Google Search's wider internet access and search capabilities.

Sean Michael Kerner is an IT consultant, technology enthusiast and tinkerer. He has pulled Token Ring, configured NetWare and been known to compile his own Linux kernel. He consults with industry and media organizations on technology issues.