What Is GPT? A Complete Guide

Last updated: January 2026

GPT stands for Generative Pre-trained Transformer. It's a type of AI model that generates human-like text by predicting the next word in a sequence. Developed by OpenAI, GPT models power ChatGPT and many other AI applications. The latest version, GPT-5, supports up to 400,000 tokens of context and includes specialized reasoning capabilities.

GPT has become synonymous with modern AI, but there's confusion about what it actually is. GPT is not a company (that's OpenAI). It's not a chatbot (that's ChatGPT). It's a family of AI models that understand and generate text.

This guide explains what GPT is, how it works, and how it evolved from a research project to the technology behind the AI revolution.

Quick Overview

What Does GPT Stand For?

G - Generative: Creates new content (text, code, etc.) rather than just analyzing existing content.

P - Pre-trained: Trained on massive amounts of text data before being fine-tuned for specific tasks.

T - Transformer: Uses the transformer architecture, a type of neural network designed for processing sequences.

Each word describes a key aspect of how the technology works.

How GPT Works

The Transformer Architecture

GPT is built on the transformer architecture, introduced by Google researchers in 2017. Before transformers, AI struggled with long text because it processed words one at a time, losing context over distance.

Transformers solved this with an "attention mechanism" that processes entire sequences at once. The model can "attend" to any part of the input when generating each word, maintaining context across long conversations.

Key innovations:

• Self-attention: The model weighs the relevance of each word to every other word
• Parallel processing: Processes entire sequences simultaneously (faster training)
• Long-range dependencies: Maintains context across thousands of words

Pre-training

GPT models are "pre-trained" on enormous datasets of text from books, websites, and other sources. During pre-training, the model learns:

• Grammar and syntax
• Facts and knowledge
• Reasoning patterns
• Writing styles

This creates a general-purpose language understanding that can be applied to many tasks.

Text Generation

GPT generates text by predicting the most likely next word (technically, "token") given all previous words. It does this repeatedly to produce sentences, paragraphs, or entire documents.

Example process:

1. Input: "The capital of France is"
2. Model predicts: "Paris" (highest probability)
3. New input: "The capital of France is Paris"
4. Model predicts next word, and so on

The model doesn't "know" facts like a database. It predicts what text is likely to come next based on patterns in its training data.

The Evolution of GPT

GPT-1 (June 2018)

The original. 117 million parameters. Trained on BookCorpus (7,000 unpublished books). Proved that pre-training on unlabeled text, then fine-tuning for specific tasks, worked remarkably well.

Capabilities: Could complete sentences coherently, basic language understanding.

GPT-2 (February 2019)

10x larger at 1.5 billion parameters. Trained on WebText (8 million web pages). Generated coherent paragraphs that were sometimes indistinguishable from human writing.

OpenAI initially withheld the full model over concerns about misuse for generating misinformation.

Capabilities: Multi-paragraph text generation, basic reasoning, some creative writing.

GPT-3 (June 2020)

The breakthrough. 175 billion parameters (117x larger than GPT-2). Trained on 300 billion tokens. Introduced "few-shot learning" where the model could solve new tasks from just a few examples in the prompt.

GPT-3 powered the first wave of AI writing tools and coding assistants.

Capabilities: Complex writing, code generation, question answering, translation, basic reasoning.

GPT-4 (March 2023)

Estimated 1-1.8 trillion parameters. First multimodal GPT (understands images, not just text). Major improvements in reasoning, reliability, and safety. Passed professional exams (bar exam, medical licensing).

Capabilities: Image understanding, complex reasoning, longer context (32K tokens), reduced hallucinations.

GPT-5 (August 2025)

The current generation. Uses a routing system with multiple specialized models (gpt-5, gpt-5-mini, gpt-5-thinking). Up to 400,000 tokens of context. Integrated chain-of-thought reasoning. Significant reductions in hallucinations.

Capabilities: Deep reasoning, massive context windows, improved accuracy, multimodal understanding (text, images, audio).

GPT Model Comparison

GPT vs ChatGPT

GPT is the underlying AI model. It's an API that developers use to build applications.

ChatGPT is a consumer application built on GPT. It adds:

• Conversational interface
• Safety guardrails
• Memory and context management
• User-friendly features (voice, file uploads, etc.)

Think of GPT as the engine and ChatGPT as the car built around it.

What GPT Can Do

Writing and Content

• Draft emails, articles, reports
• Edit and improve existing text
• Adapt tone and style
• Translate between languages

Coding

• Write code in multiple languages
• Debug and explain code
• Convert between programming languages
• Generate documentation

Analysis

• Summarize documents
• Extract key information
• Answer questions about content
• Compare and contrast topics

Reasoning

• Solve logic problems
• Break down complex questions
• Provide step-by-step explanations
• Evaluate arguments

Creative Tasks

• Brainstorm ideas
• Write stories and scripts
• Generate marketing copy
• Create outlines and structures

Limitations of GPT

Hallucinations: GPT can generate plausible-sounding but incorrect information. It predicts likely text, not verified facts.

Knowledge cutoff: Training data has a cutoff date. Without web access, GPT doesn't know recent events.

No true understanding: GPT doesn't "understand" in the human sense. It recognizes patterns and generates statistically likely responses.

Context limits: Even GPT-5's 400K tokens have limits. Very long conversations or documents may lose context.

Bias: Training data contains biases that can appear in outputs.

How GPT Is Used

ChatGPT and Assistants

Consumer chatbots for general assistance, writing help, coding support.

API Integration

Developers embed GPT into applications for customer service, content generation, data analysis.

Enterprise Tools

Microsoft Copilot, Salesforce Einstein, and other business tools powered by GPT.

Content Creation

Marketing copy, blog posts, product descriptions, social media content.

Code Development

GitHub Copilot, code completion, debugging assistance.

Research and Analysis

Document summarization, research synthesis, data interpretation.

The Future of GPT

GPT models continue to improve in several directions:

Reasoning: Better at complex, multi-step problems through chain-of-thought and specialized reasoning models.

Accuracy: Reduced hallucinations through better training and verification.

Multimodal: Understanding and generating text, images, audio, and video.

Efficiency: Smaller models that run locally on devices.

Specialization: Domain-specific models for medicine, law, science.

What Is GPT? Summary

GPT (Generative Pre-trained Transformer) is a type of AI model that generates human-like text. Developed by OpenAI, it powers ChatGPT and countless other applications.

The technology works by predicting the most likely next word based on patterns learned from massive training datasets. It's remarkably capable but not infallible. It hallucinates, has knowledge limits, and doesn't truly "understand" in the human sense.

From 117 million parameters in 2018 to systems with hundreds of billions today, GPT has evolved from a research curiosity to the foundation of modern AI applications.

FAQs About GPT

What does GPT stand for?

Generative Pre-trained Transformer. "Generative" means it creates new content. "Pre-trained" means it learned from massive datasets before fine-tuning. "Transformer" is the neural network architecture it uses.

Is GPT the same as ChatGPT?

No. GPT is the underlying AI model (the technology). ChatGPT is a consumer application built on GPT (the product). GPT is like an engine; ChatGPT is like the car.

How does GPT generate text?

By predicting the most likely next word given all previous words. It does this repeatedly to generate sentences and paragraphs. The predictions are based on patterns learned from training on billions of words of text.

What is the latest GPT version?

GPT-5, released August 2025. It features a routing system with multiple specialized models, up to 400,000 tokens of context, and integrated chain-of-thought reasoning. Earlier versions include GPT-4 (2023), GPT-3 (2020), GPT-2 (2019), and GPT-1 (2018).

Why does GPT sometimes give wrong answers?

GPT predicts likely text based on patterns, not verified facts. It can generate plausible-sounding but incorrect information (hallucinations). It doesn't have access to real-time information (unless given web access) and can reflect biases in its training data.

Can I use GPT for free?

ChatGPT has a free tier with access to GPT-4o. The GPT API requires payment based on usage. More advanced features (GPT-5, higher limits) require paid subscriptions ($20/month for ChatGPT Plus, $200/month for Pro).