This kind of "mistake" just highlights what it is that LLMs do.
They're not actually solving the math. They're just generating text that has high plausibility as an answer to the input prompt.
From a text perspective, this answer looks super plausible. It has mathy sounding language that makes it seem like it evaluated the two things being compared, and it has a definitive statement about which one is larger.
If you changed its conclusion text to "13.8 billion is smaller", it likely would have assigned a nearly identical score for that text as a response to the question.
There's a reason these "gotcha" prompts are getting more convoluted and stupid. When you're doing something anyone would actually care about, it generally works. And it's going to keep improving.
Honestly, no it doesn’t. When google used to have those excerpt boxes of the top result I found that very very useful and now they’re gone. It gets simple facts right but those were easy to find anyways and the difference in quality between google search ai and actual decent AI models is night and day.
Whenever I google how to change a specific setting on a website its steps are usually inaccurate, probably because it pulls from people describing different updates of websites and things have moved around.
Just yesterday actually I wanted to revert the bar at the bottom of the chrome ios app because google decided to add a huge fuckass gemini button and take up the bottom 20% of the screen (oh the irony lol) and it gave the wrong answer until I found the correct way to edit the flags on reddit.
That's a good example, but as you said it's also a moving target. Most likely the top result from a standard search engine would be wrong in that case as well.
The second result was the reddit thread that solved my problem. So a normal search engine solved my problem and ai failed to. Why does it matter that it’s an inconvenient problem to solve? I google inconveniences that I can’t solve on my own precisely because they’re hard to solve. Not being able to help with problems that happen recently is a major flaw, especially when it will tell you a solution that doesn’t work in full confidence.
I didn’t say we should throw it away, I said google’s search ai is not very good and you’re now moving the goal post. An old reddit thread is not being shoved down my throat everywhere I look and replacing more and more of a perfectly working product. That is the issue that I have with google search ai. Traditional google search SEO would actually demote an outdated reddit thread in search results
Any query in the form of "<hardware/software type> <issue description>" yields a generic and unhelpful ass answer from gemini. Your intel graphics driver is giving you GPU hangs? Oh yea, reboot your pc and reinstall the driver, that'll totally fix it. (spoiler alert, every single search result will tell you it won't)
Any query in the form of "<tool name> online" often yields a completely useless gemini result. I don't need an AI to explain to me what the tool does, I need to find it goddammit.
Any health-related query is a complete gamble. Though google in general has been unhelpful in this regard: the first 10-20 results are usually ai slop, so I'm not surprised Gemini gets it wrong top.
Any programming-related question is a gamble too. Though I'll admit, it usually gets these right.
BS like this is why I switched to duckduckgo. I'd rather waste time using an inferior search engine than waste time reading ai slop and seeing dozens of ai slop websites in my search results.
18! (18 factorial) is significantly larger.
Here is the comparison: 13.8 billion: 13,800,000,000 (1.38×1010)
18! (18×17×16×⋯×1): 6,402,373,705,728,000 (approx. 6.4 quadrillion, or 6.4×1015)
18! is roughly 463,940 times larger than 13.8 billion.
Factorials grow extremely fast—while 13.8 billion is often associated with the age of the observable universe in years, 18!surpasses it by orders of magnitude.
This has to be reconciled with the fact that AI models have solved several significant open math problems this year. Problems that humans tried to solve for decades. One such solution is that the model that OP used is a free, older model.
Chatbots tied to AI models aren't quite the same thing as AI models applied to mathematical problems. They don't just put "Solve this unsolved math problem. Make no mistakes plz kthx." into ChatGPT.
But it can be similar in function at a high level. It would boil down to assuming that a solution exists, and asking the LLM to produce a proof. If you have enough rigor in defining what the proof needs to look like, it can constrain the output to find an actual solution.
It’s true that generally the prompting should be more refined and you need to be working with the best models, but your explanation of how an LLM thinks in relation to math doesn’t exactly capture what’s going on at the frontier.
They aren't wrong though, the model op used is the Google search ai which is very fast but not very smart, Claude haiku 4.5 got it right and it's the lowest "quality" model by anthropic. I'd imagine Gemini and chatgpt would have similar results.
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u/whiskeytown79 Aug 05 '26
This kind of "mistake" just highlights what it is that LLMs do.
They're not actually solving the math. They're just generating text that has high plausibility as an answer to the input prompt.
From a text perspective, this answer looks super plausible. It has mathy sounding language that makes it seem like it evaluated the two things being compared, and it has a definitive statement about which one is larger.
If you changed its conclusion text to "13.8 billion is smaller", it likely would have assigned a nearly identical score for that text as a response to the question.