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GPT-4o vs Gemini 1.5 Pro: Comparing New AI Models

GPT-4o vs Gemini 1.5 Pro: Comparing New AI Models


Last week, AI startup OpenAI held its Spring Update on the eve of Google's annual developer conference, I/O, which pitted bots against one another.

Both companies announced updates to their generative AI models, toying with terminology like tokens and parameters while showing off new interfaces and features.

The terminology can get murky, and it’s not always easy to understand the differences between OpenAI’s ChatGPT and Google’s Gemini, let alone all the competing models.

Don't get us wrong, there are differences. Read CNET's Imad Khan's review of AI chatbots to find out his real-life experiences and his thoughts on the pros and cons of each.

But when I thought about how the Gemini 1.5 Pro compares to the latest models, OpenAI's GPT-4o, I called up a longtime acquaintance to get his perspective: He's a technology executive with 30 years of experience who has helped me many times demystify complex topics. (He asked not to be named here because he's not authorized to speak publicly.)

“In my mind, it's like Coca-Cola and Pepsi, you know what I mean?” he said.

Here's what he means.

Coca-Cola and Pepsi are both cola, but they are made differently and any soda drinker will tell you they don't taste the same. Both GPT-4o and Gemini 1.5 Pro are advanced language models, designed to manufacturer specifications, that understand user-entered text prompts and generate human-like text responses. However, ChatGPT's responses are not exactly the same as Gemini's responses.

It's the same but different.

One is built to integrate with Microsoft products but also works on its own, and the other is designed for Google.

Both models offer free and subscription versions: ChatGPT Plus and Gemini Advanced each cost $20 per month and give you access to the latest models and more features.

Welcome to the AI ​​arms race, which has begun with the arrival of ChatGPT in late 2022. Startups like Anthropic and tech giants like Google and Microsoft are regularly updating their chatbots, while in some cases teasing advancements in video, audio, and gaming, as they compete for market share. (For reviews, advice, and news about these products, check out our new AI Atlas hub.)

And just like you might prefer the taste of one cola over another, which generative AI model you like best is really up to you, your needs and preferences (and, of course, each platform's branding and marketing efforts also play a role).

Let's take a closer look at how GPT-4o compares to Gemini 1.5 Pro.

Context Window

Last week, Google expanded Gemini 1.5 Pro’s token context window to 1 million tokens, promising to double that to 2 million tokens later this year (it launched with a context window of 128,000 tokens in February).

Meanwhile, GPT-4o and its predecessor GPT-4 have a context window of 128,000 tokens.

What does that mean?

The context window is the range of text that a language model can consider when generating a response; it's like a memory. The larger the context window, the more it can remember from previous conversations, and the more words, videos, audio, and lines of code it can incorporate on your behalf. (This is internal to the model, not the user interface window where you type and receive responses.)

This means that Gemini's capacity will be much larger at this point.

But when it comes to parameters…

Neither OpenAI nor Google have said much about the parameters.

what are they?

First, a quick review of tokens: Large language models break queries into tokens in order to process them and provide answers. A token can be as short as a single character or as long as a word. So in the example “Hello, reader”, one token would be “hello” and the other would be “reader” (remember that the model is looking for patterns to predict what comes next).

The parameters determine the model's ability to process these tokens and generate text accurately.

You can think of parameters as being like neurons in the brain: the more neurons you have, the more complex your thoughts are. The same can be said about parameters.

A spokesperson said Google doesn't disclose the parameters of the model, and estimates range from 1.6 trillion to 175 trillion.

It wasn't immediately clear how many parameters GPT-4o uses, but OpenAI CTO Mira Murati said in the announcement that the model “brings GPT-4 levels of intelligence to anything.” GPT-4, which debuted in March 2023, reportedly uses 1.8 trillion parameters to process queries.

So while we can't make an apples-to-apples comparison here, it's fair to say that both models have lots of neurons for complex thought.

Information Access

In his Gemini review, Khan noted that an internet connection would allow for more up-to-date information, which should give it an edge over GPT-3.5, the language model in ChatGPT's free version at the time.

This is important because language models have a knowledge cutoff, which means the training data only contains information up to a certain point in time. For GPT-4o, the knowledge cutoff is October 2023. For Gemini, it's “early 2023.”

But any advantage may now be moot, as OpenAI is not only training its tools on more recent data, but also inking deals with social platform Reddit and media company News Corp to pull in more up-to-date content.


GPT-4o will be available in 50 languages. Gemini 1.5 Pro will be available in 35 languages.

But given Google’s 18-year history with Google Translate, it’s likely they have much more data to train models for multilingual capabilities.


One final similarity: both models have recently introduced features that make them more conversational.

In the case of ChatGPT-4o, it includes a new interface that lets you converse with the chatbot and share live video footage (it even uses the familiar phrase, “Hey, ChatGPT”).

You can also interrupt your model's conversation and allow them to sense your emotions.

Google has introduced Gemini Live, which allows you to talk to Gemini, and you can even barge into Gemini Live.

Editor's note: CNET has used an AI engine to create dozens of articles and labeled them accordingly. The notes you're reading are attached to articles that substantively address AI topics, but are all created by our expert editors and writers. For more information, see our AI policy.




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