The growing prominence of large language models (LLMs) necessitates the exploration of their capabilities beyond English. This research investigates the Telugu language proficiency of ChatGPT and Gemini, two leading LLMs. Through a designed set of 20 questions encompassing greetings, grammar, vocabulary, common phrases, task completion, and situational reasoning, the study delves into their strengths and weaknesses in handling Telugu. The analysis aims to identify the LLM that demonstrates a deeper understanding of Telugu grammatical structures, possesses a broader vocabulary, and exhibits superior performance in tasks like writing and reasoning. By comparing their ability to comprehend and use everyday Telugu expressions, the research sheds light on their suitability for real-world language interaction. Furthermore, the evaluation of adaptability and reasoning capabilities provides insights into how each LLM leverages Telugu to respond to dynamic situations. This comparative analysis contributes to the ongoing discussion on multilingual capabilities in AI and paves the way for future research in developing LLMs that can seamlessly integrate with Telugu-speaking communities.

翻译：随着大语言模型（LLM）的日益普及，探索其在英语以外的语言能力变得至关重要。本研究调查了ChatGPT和Gemini这两种领先的LLM在泰卢固语方面的熟练程度。通过设计一组包含问候语、语法、词汇、常用短语、任务完成和情境推理等20个问题，本研究深入探讨了它们在处理泰卢固语时的优势和劣势。分析旨在识别出对泰卢固语语法结构有更深入理解、词汇量更广、在写作和推理等任务中表现更优的LLM。通过比较它们理解和运用日常泰卢固语表达的能力，本研究揭示了它们在实际语言交互中的适用性。此外，对适应性和推理能力的评估提供了关于每个LLM如何利用泰卢固语应对动态情境的见解。这一对比分析有助于当前关于人工智能多语言能力的讨论，并为未来开发能够无缝融入泰卢固语社区的LLM研究铺平了道路。