# What is LLM Inference?

The process of a trained artificial intelligence model generating a response to a given question.

## Overview
Inference is the process where an artificial intelligence model uses the information learned during the training phase to make predictions and generate results based on new input. This process is the moment the model 'thinks' or 'responds'. Unlike the training phase, the model does not learn anything new here; it only applies what it already knows.

*Analogy: It is like a student answering questions during an exam by using the information from the books they previously studied.*

## How it works
The input (prompt) is given to the model, the model processes this input with its internal weights, and generates the response by predicting the next most logical word. This process requires very fast computation.

## Where it is used
It is used during the operation of artificial intelligence applications, in API calls, and in model performance tests.

## Commonly confused with
It should not be confused with training the model; training is the model's learning process, while inference is the application process.

## Frequently asked questions
**Does the model continue to learn during inference?**
No, inference is only the process of using existing knowledge; it does not learn anything new.

**Why is it important?**
The speed and cost of applications depend on how efficiently the inference process runs.


## Related terms
- [LLM](/en/dictionary/llm/)
- [Inference](/en/dictionary/inference/)
- [Generative AI](/en/dictionary/generative-ai/)

## Related tools
- [ODS](/en/discover/ods/)

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Source: TreScout Dictionary · https://trescout.com/en/dictionary/llm-inference/