Well, that's easy: zero.
Because even a single training example would 'solved' it by memorizing the simple easy answer within weeks of 'strawberry' first going viral , which was like a year and a half ago at this point - and dozens of minor and major model upgrades since. And yet, the strawberry example kept working for most (all?) of that time.
So you can tell that if anything, OA probably put in extra work to filter all those variants out of the training data...
(This is, by the way, why you can't believe any LLM paper about 'forecasting' where they are just doing backtesting, and didn't actually hold out future events. Because there are way too many forms of leakage at this point. This logic may have worked for davinci-001 and davinci-002, or a model whose checkpoints you downloaded yourself, but not for any of the big APIs like GPT or Claude or Gemini...)
Because it gets tokenised, of course a model could never count the rs.
But I suppose if we want these models to be capable of anything then these things need to be accounted for.