What is Large language model (LLM)?
A very large neural network trained on huge amounts of text to predict and generate language.
In plain English
An LLM reads text as small pieces called tokens and learns patterns in how they follow one another. After training it can answer questions, summarise, translate and write code. It works with probabilities rather than looking facts up, which is why it can sound confident and still be wrong.
Example
GPT, Claude and Gemini are all LLM families.
Easy to confuse with
- Generative AI: An LLM is one type of generative AI model.
Where you will meet it
This idea belongs to the subject area of these practice tests. We do not publish or predict real exam questions.
- NVIDIA NCA-GENL practice tests
- Google Cloud Generative AI Leader practice tests
- AWS AIF-C01 practice tests
- Databricks GenAI Engineer Associate practice tests
Related terms
- Tokens: The small chunks of text that a language model reads and writes, and that usage is measured in.
- Hallucination: When an AI model states something false or invented as if it were true.
- Prompt engineering: Writing instructions and context so an AI model gives a more useful answer.
- Retrieval-augmented generation (RAG): Letting a model look up relevant documents first and answer using them.
Test yourself
Practice tests with an explanation for every answer option, so each mistake teaches you something.
Browse practice testsAll glossary termsWritten and checked by the Be Ready Education team, last reviewed 2 November 2026. General study information, not professional advice. Providers change names and rules, so confirm details on the official documentation. Not affiliated with, endorsed by or sponsored by any certification vendor or exam body. Certification names, exam codes and product names are trademarks of their respective owners and are used only to identify the exam a practice product prepares for. Our questions are original and are not actual exam questions.