Large Language Models have presented an impressive performance and have become fundamental in real-world applications. These models are built upon vast amounts of text data and are trained to understand, generate, and manipulate human language with remarkable fluency. Large language models have applications in various fields, including content generation, language translation, sentiment analysis, and conversational agents. These models are based on neural networks and considered as pre-trained, large-scale, statistical language models. LLMs are playing a significant role in advancement of AI agents. This chapter has explored different existing surveys and summarized in two categories, 7 general survey papers and 15 domain specific survey papers. Primary focus of chapter is to explore the types of large language models, tasks of LLMs, frame-works, applications and challenges.