The recent advancements in the field of artificial intelligence (AI) has led to the development of a landmark innovation in the form of generative large language models (LLM). Generative LLMs are the models which take large number of input parameters and generate textual output. Natural language processing (NLP) is a subset of AI that equips machines to comprehend, interpret, and respond to human language. NLP comprises of statistical and deep learning models for providing quality data and understanding the meaning of input. In relation to NLP, generative LLM models can produce contextually correct and relevant response which resembles human-created content given the appropriate prompt. Prompt to these models can be in any form that is unimodal (text, audio or video) or multimodal in nature and will be converted to newer text as output. With the generative power of LLM, NLP can now be used to develop wide range of creative, interactive and dynamic applications ranging from simple translations, conversational tasks to automatic document summarization. The impact of usage of generative LLMs is evident from the advances it has accelerated in high-stakes domain such as healthcare, law and finance. Generative LLMs has stimulated a shift from traditional NLP capabilities to creative content generation capabilities of NLP leading to human like interactions with text. This chapter provides the quantitative understanding of the role of generative LLMs in the field of NLP.