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A comparison between three chatbots which are based on large language models,namely ChatGPT-3.5, ChatGPT-4 and Google Bard is presented, focusing on theirability to give correct answers to mathematics and logic problems. Inparticular, we check their ability to Understand the problem at hand; Applyappropriate algorithms or methods for its solution; and Generate a coherentresponse and a correct answer. We use 30 questions that are clear, without anyambiguities, fully described with plain text only, and have a unique, welldefined correct answer. The questions are divided into two sets of 15 each. Thequestions of Set A are 15 "Original" problems that cannot be found online,while Set B contains 15 "Published" problems that one can find online, usuallywith their solution. Each question is posed three times to each chatbot. Theanswers are recorded and discussed, highlighting their strengths andweaknesses. It has been found that for straightforward arithmetic, algebraicexpressions, or basic logic puzzles, chatbots may provide accurate solutions,although not in every attempt. However, for more complex mathematical problemsor advanced logic tasks, their answers, although written in a usually"convincing" way, may not be reliable. Consistency is also an issue, as manytimes a chatbot will provide conflicting answers when given the same questionmore than once. A comparative quantitative evaluation of the three chatbots ismade through scoring their final answers based on correctness. It was foundthat ChatGPT-4 outperforms ChatGPT-3.5 in both sets of questions. Bard comesthird in the original questions of Set A, behind the other two chatbots, whileit has the best performance (first place) in the published questions of Set B.This is probably because Bard has direct access to the internet, in contrast toChatGPT chatbots which do not have any communication with the outside world.

Chatbots put to the test in math and logic problems: A preliminary comparison and assessment of ChatGPT-3.5, ChatGPT-4, and Google Bard