ModelRefs / Foundation Model — AI Glossary
Foundation Model — AI Glossary
A large model trained on broad data at scale that can be adapted to a wide range of downstream tasks. Also called FM or pretrained model.
Overview
The term, coined by Stanford HAI (2021), captures models like GPT, Claude, Gemini, and Llama — trained on diverse internet-scale corpora and adapted via fine-tuning, RLHF, or prompting rather than retrained per task.
Reference details
| Topic | models |
|---|---|
| Also known as | FM, pretrained model |
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
Foundation model describes breadth and adaptability — trained on broad data, useful across many downstream tasks, and not restricted to text. Base model describes a training stage: pretrained but not yet instruction-tuned. They are different axes, so an instruction-tuned assistant is still a foundation model and is no longer a base model.
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Frequently asked questions
What is Foundation Model?
A large model trained on broad data at scale that can be adapted to a wide range of downstream tasks.
Is Foundation Model the same as FM?
Yes — FM, pretrained model are common aliases for Foundation Model.
What concepts are related to Foundation Model?
Closely related concepts include llm, pretraining, fine tuning.