I'd be curious how much better a more expensive LLM would do - gpt-4o-mini and gemini-2.5-flash-preview-05-20 are definitely not the most capable LLMs one could have chosen.

Maybe I simply don't know how advertising works, but wouldn't it be totally possible that these fonts are just one-off drawn in text?

How close are the wrong guesses? Fonts are fairly incestuous because the shapes of the characters themselves can't be copyrighted (only the code), so there are sometimes dozens of clones of very similar fonts... especially on a free site like dafont

Missing from the methodology: - was thinking on or off? (At least for Gemini) - was web search allowed? - was tool use allowed?

It’s quite likely LLMs don’t “know” the fonts in the dataset, but they could figure many of them out.

I've asked LLMs to suggest fonts/similar fonts for me from screenshots and seems like they are close enough to my untrained eye

Why don't you just ask the document creator?

Every time I turn around these days I encounter someone ready to use an infinite amount of energy that is being paid for by other people, to 'simulate' some analog process by temporarily taking the reins of some data center that is burning megawatts of energy. We are being given the reins for 0.5 seconds but very soon the horse will gallop away unless we have a lot of money to spend.

I would have never thought to not use "what the font"

https://www.myfonts.com/pages/whatthefont

I suspect that few professional (paid for) adverts use any fonts from dafont.com, and many fonts would anyway be unavailable to ordinary users. The current font recogniser programs are usually trained on commercially available fonts

With the latest Microsoft Word, if you open a PDF that is a scanned image of a document and convert it to Word format, it does a pretty decent job of not only OCR (optical character recognition) but also picking matching fonts for various sections.

I just tested this with my internet connection disabled and it still worked. Since it's doing local processing, I suspect it uses traditional OCR algorithms rather than LLMs.

As the article concludes, LLMs aren't magic, they're just one useful tool to include in your toolbox.

I recently tried to identify a font from a screenshot of an ad and used everything I could find, from WhatTheFont to LLMs. The LLMs were hopeless at identifying the font from the screenshot, but ChatGPT eventually led me to the correct result after I threw away the image and started describing the font in plain text: monospacing, a dot in the middle of the 0, and (presumably) wide usage. It turned out to be Ubuntu Mono. It was surprising that so many obscure fonts were suggested, none of which were even a reasonably close match, while Ubuntu Mono was completely overlooked.

Results here are bad, obviously, but it'll be interesting when LLMs can not just identify fonts but unredact pieces of documents in places where just a few words are removed by analyzing the length of redaction, combos of letters that fit into it, and the context.

What makes us think font information made it into the traning set atll, rather than something more along the line of "all chars that look like this one are to be interpreted as 'a'". doesnt need to provide font name for it.