Understand it in 10 seconds
Fine-tuning continues training an existing model on selected examples for a particular behavior or task.
In plain language
Fine-tuning continues training an existing model on selected examples for a particular behavior or task. This describes what the model or system does, not a promise that every product behaves identically.
An analogy
It is specialist training after a broad education, not learning everything from scratch.
The analogy is a shortcut, not a complete technical definition.
An everyday example
Where you will encounter it
The term appears in model customization, AI platforms and production ML projects.
Should you care?
Most users do not need it. Teams should first ask whether prompting or retrieval solves the actual problem.
How it differs
Uploading documents is not automatically fine-tuning. RAG retrieves information; prompts guide a request; fine-tuning changes a model through further training.
Related Terms
Related terms
Continue with these published explanations.
Sources & last checked
Checked against official documentation. Editorial recommendations are distinguished from vendor positioning; no runtime benchmark was performed.
Official documentation
01Last checked: September 5, 2026
official-docs