Generative AI: which one answers better between ChatGPT and Claude?
The news generated a lot of buzz: last March 27, 2024, for the first time ChatGPT-4 lost the scepter of the Chatbot Arena rankings, overtaken by the disruptive Claude 3 model. And since we can’t help but talk about Generative Artificial Intelligence and its applications, we thought we’d test these systems a little better to see how they really work and what kind of answers they provide for those who want to exploit their applications in SEO and beyond. So here is what emerged from a quick and totally non-scientific comparison of ChatGPT-4, Claude and Gemini.
Why the comparison of Generative AI models
We should be sufficiently familiar by now with Artificial Intelligence, which has been at the center of virtually every discussion (and prediction) on digital issues for more than 16 months. In fact, we know how to use AI to create text and we may even have mastered enough of the tools to leverage it for various SEO tasks, and in general AI is revolutionizing the way we interact with machines and how they can assist in content creation.
Large language models (LLMs) such as ChatGPT, Gemini and Claude represent the frontier of this innovation, offering increasingly sophisticated natural language generation capabilities. Designed to understand and generate text in a way that is indistinguishable from text written by a human, these models open up new possibilities in fields ranging from customer service to creative content production.
Yet is it really all “gold that glitters”? Are these systems really virtually perfect and respond impeccably to prompts and instructions?
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In light of these concerns, we launched a comparison of ChatGPT, Gemini, and Claude that is useful for understanding the nuances and potential of each platform. Since each of these tools was developed with slightly different approaches and goals, it is important to evaluate their performance in real-world scenarios to identify which one best fits specific needs and contexts.
The characteristics of these Generative AI models
Just as a reminder, it is worth opening a parenthesis to reiterate that