We have analyzed the growth of advanced text summarization method leveraging LLM for Indic language. Text summarization involves transforming a longer text information into a more concise version, ensuring that the most prominent information and key meanings are maintained. Our goal is to produce concise and accurate summaries from longer texts, focusing on maintaining detailed information and coherence. We utilize NLP techniques for text cleaning, keyword extraction and summarization, along with performance evaluation metrics such as ROUGE score, BLEU score and BERT Score. The results demonstrate an incremental improvement in the quality of generated summaries, with a particular emphasis on enhancing informativeness while minimizing redundancy. This research work also highlights the importance of tuning parameters and leveraging advanced models for producing high quality summaries in diverse domains for Indic Language.