Accuracy and Completeness of AI Chatbot Responses for Leopard Gecko ( <i>Eublepharis macularius</i> ) Husbandry: An Exploratory Comparison of ChatGPT-4o and Gemini 2.5 Pro

Abstract

Large Language Models (LLMs) like OpenAI's ChatGPT-4o and Google's Gemini 2.5 Pro are increasingly used to retrieve care advice on specialized topics including exotic pet husbandry, raising concerns about accuracy and animal welfare. This study, to our knowledge, is the first direct comparison of these models for husbandry knowledge on the widely kept reptile leopard gecko (<i>Eublepharis macularius</i>). Both were queried with 21 questions (biology, care, health) using two prompting styles: questions asked individually in separate chats and all questions asked within a single chat; responses were scored for accuracy and completeness. Both provided generally accurate information (≥2/3) without dangerous errors or "hallucinations." However, completeness varied; Gemini 2.5 Pro providing more detail. Prompting style was critical: individual prompts yielded far more comprehensive responses (average words: ChatGPT 136, Gemini 387) than combined prompts (ChatGPT 12, Gemini 64), which were sometimes incomplete, especially for ChatGPT-4o. Furthermore, the models demonstrated potential data biases - such as omitting commercial diets while recommending only larger-than-standard enclosures. LLMs can be useful starting points, but critical evaluation, effective prompting, and expert consultation remain essential to ensure animal welfare.

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