Here are some popular AI language models that can be used for text-based prompts:

GPT-3 (Generative Pre-trained Transformer 3) - Developed by OpenAI, GPT-3 is one of the largest and most advanced language models available today, with 175 billion parameters. It can generate high-quality natural language responses to a wide variety of text prompts.

GPT-2 (Generative Pre-trained Transformer 2) - Also developed by OpenAI, GPT-2 is a slightly smaller version of GPT-3 with 1.5 billion parameters. It can still generate high-quality natural language responses to a wide variety of text prompts.

BERT (Bidirectional Encoder Representations from Transformers) - Developed by Google, BERT is a popular language model that is designed to help machines understand the nuances of human language. It can be used for tasks such as question answering, sentiment analysis, and more.

T5 (Text-to-Text Transfer Transformer) - Developed by Google, T5 is a versatile language model that can be used for a wide range of natural language processing tasks. It can be fine-tuned on specific tasks by providing it with text-to-text examples.

XLNet - Developed by Carnegie Mellon University and Google, XLNet is a highly accurate language model that is trained to generate natural language text. It uses a permutation-based approach to language modeling, which allows it to capture complex dependencies between words.

These are just a few examples of the many language models that are available for text-based prompts. Each model has its own strengths and weaknesses, so the best choice depends on the specific task and use case.