You've seen names like GPT-4 Turbo, Gemini Ultra, and Claude Opus. But these names mean different things for different companies!

Each AI company has its own naming system - let's decode them for smarter data analytics decisions.

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Which model names have confused you when choosing tools for data work?

OpenAI is notorious for using confusing model names. They have different families of models the two main ones being the GPT family and the o family which is short for omnious.

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Have you used the o family for complex data analysis before?

In the GPT family, early versions of chatGPT were launched with GPT 3.5. Now GPT-4o and GPT-4.1 have become dramatically faster and smarter. The GPT family is known for offering cutting edge combination of speed, cheaper cost, and fairly high intelligence.

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If you've used any of them for data cleaning or quick analysis, which is your favorite model?

Then comes the o family, these ones are reasoning models (we'll talk more about this in the future) but they are known to be far more intelligent than the models in the GPT family but they are more expensive and much slower.

So for complex statistical analysis or when you need deep insights from messy datasets, using a model like o3 is the best choice.

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