What is a Generative Pre-trained Transformer (GPT)?

A Generative Pre-trained Transformer (GPT) is a type of large language model (LLM) widely used in generative AI applications, especially conversational agents like chatbots. These models are built on a deep learning architecture known as the transformer, and they are initially trained on massive volumes of unlabeled text data. Once trained, GPTs can generate new, original content based on the patterns and structures they have learned.

The Origins of GPT Technology

OpenAI was the first to implement generative pre-training on the transformer framework, introducing the original GPT-1 model in 2018. Since then, OpenAI has continued to scale its models, launching increasingly powerful versions.

A major milestone came in late 2022, when OpenAI released ChatGPT, a chatbot powered by GPT-3.5. Its popularity sparked a wave of competing chatbot models using similar GPT-style architectures, including Gemini, Claude, and DeepSeek.

What Can GPTs Do?

Although GPTs are primarily designed for text generation, some versions have been adapted to handle other data types. For example:

• GPT-4o is a multimodal model, capable of processing and generating text, images, and audio.

• Some newer GPT models, such as OpenAI’s o3, focus on reasoning. These models take extra time to understand more complex tasks before producing a response, enhancing accuracy and depth.

• In 2025, GPT-5 introduced a routing system that automatically selects between a faster, lightweight model and a slower, reasoning-focused one—depending on the complexity of the task.