ChatGPT, Gemini, Perplexity: what does each one say about Hungarian businesses?

The four big AI platforms don't say the same thing about your company. They draw on different sources, name different businesses, and handle Hungarian with varying quality. What ranks as the top recommendation in one can be missing entirely from another. That's why optimizing for a single model is misleading: focus only on ChatGPT and you may stay invisible in Gemini's answers — and vice versa. Here's how they differ, and what that means in practice for a Hungarian SME.

Many people talk about artificial intelligence as if it were one single, unified thing. But a buyer doesn't ask "the AI" — they ask a specific tool: ChatGPT, Gemini, Perplexity, or Claude. And each of those decides differently which company it names. If you don't know that, it's easy to put your energy in the wrong place.

How do the four big platforms differ?

The difference isn't about style — it's about sources. Each model draws what it knows from somewhere different, and on the Hungarian market they aren't equally strong, either. It's worth going through them one by one.

Gemini — on the Hungarian market, this is the standout platform. Google's model is tightly tied to the Google search index, and it favors official company pages and a well-filled-out Google Business Profile. Its local logic essentially mirrors the traditional search ranking, which makes it the most predictable platform for anyone building on their Business Profile. The accuracy of company data is also best here: in one measurement Gemini scored 100%, while ChatGPT and Perplexity hovered around 68%. On top of that, the quality of its Hungarian is the most convincing of all the models.

ChatGPT — training-data-centric. Most users reach for this one, but it makes its decisions largely from its training data: Wikipedia, Reddit, major news sites. Whatever appeared in many places before 2024 is in there — whatever didn't, it tends to omit or invent. A newly launched or only-locally-known Hungarian company starts from the biggest disadvantage here, because Hungarian local businesses are underrepresented in that material.

Perplexity — works from many sources, and it's stable. This model is the most balanced when it comes to citations: it draws on official pages and directories alike, and it flags far more sources per answer than ChatGPT does. If there's a good-quality Hungarian-language source for the question, it cites it. But if all it finds is weak, machine-translated content, it'll bring in a competitor or an English page instead.

Claude — leans on user-generated content. The most distinctive of the four: it cites content written by users — forums, reviews — two to four times more often than the other models. Where there are plenty of reviews and community mentions, this model responds to them sensitively.

The difference between the platforms is most tangible in the local recommendation rates. These figures show what share of the time a given local business received a specific, named recommendation:

The lesson isn't that "AI is bad," but that it's far choosier than traditional local search — and to a different degree on each platform. Gemini's 11% rate is no longer negligible at all, whereas ChatGPT's 1.2% means that there, most local companies effectively don't exist. One very important connection runs through all of this: 95-97% of the sources cited by Google's AI summaries already appear on the first page of Google's results, too. Traditional search hasn't disappeared, then — it's become the breeding ground for AI citation instead.

What does this mean in practice for an SME?

It means there's a sensible order, and where you start matters. For a Hungarian local business, Gemini is the best entry point, because it's the most tightly tied to what a company already holds in its own hands.

The first step, therefore, is getting your Google Business Profile in order: an accurate name, address, phone number, opening hours, category — everything matching what's on your website and in the directories. On top of that comes the deliberate gathering of reviews, since review volume is the engine of local recommendation. Only after that does the responsive, Hungarian-language content come into play — the content that gives the other models, ChatGPT, Perplexity, and Claude, something to grab onto. This order is no accident: with Gemini the payoff is fastest, with the others it's slower and more indirect.

My own dated measurement made exactly this cross-platform scatter visible. I queried several free models about fifteen Hungarian dental practices, at three geographic levels of detail, across 48 queries in total (measured in May 2026). The result is instructive enough that two patterns are worth highlighting.

The first: the models listed different companies. For the same question, one model gave a list of international clinics aimed at tourists, another a completely different set of names, and a third returned practice names that led nowhere when searched back. In effect, there weren't two models that put the same practice in first place. So if you perform well in one model, it doesn't follow that you'll show up in another.

The second: not a single one of the 15 real practices was named by any of the free models examined in a way that the recommendation was traceable and reliable. In some cases the model carefully dodged the answer; in others it confidently invented a name that doesn't exist. I unpack the detailed case in the zero out of fifteen piece, and why a good score doesn't equal a recommendation is covered in the GEO score and AI recommendation article.

One detail specific to the Hungarian market deserves separate attention. According to an analysis of 1.3 million references, sites that translated their content into another language earned up to +327% more AI references on that language's searches than they did without translation (Weglot). To become visible to Hungarian buyers, it's worth being visible in Hungarian, and this matters with every model, but especially with the source-sensitive Perplexity and Gemini.

How can you check this model by model?

The good news is you don't have to take my word for it — in a few minutes you can see it with your own eyes. The key is to look at each model separately, because, as you just saw, the results scatter.

The quick protocol is as follows. Open the free version of ChatGPT and Gemini one after the other, and then — if you have the option — Perplexity too. Ask each of them the same question, phrased exactly the way one of your buyers would, in Hungarian:

"Which is the best [trade] [in your city]? Give me 5 specific names and websites."

Watch for three things. Does your company's name come up at all? If not, who shows up instead — a real competitor, or a provider from another city? And finally: are the names and websites given actually searchable, or did the model make something up? If you get a different name in each model, that's not a flaw in how you asked — it's exactly the difference between the platforms that this article is about.

This half hour will tell you more about your market position than many an expensive report. I've put together the step-by-step, more detailed guide in the what does ChatGPT say about your business piece, and I lay out the full logic of the scoring, point by point, on the methodology page.

The question today is no longer which model your buyers use — it's whether you make yourself visible in all of them, or bet on just one. If you'd like a dated, verifiable measurement of what each platform says about your company today, get in touch on the contact page. I'll measure it, and show you where the open ground is.

Kindl Dávid · Published: June 1, 2026 · Updated: June 6, 2026