# Inference

Inference is the process of using a trained model to produce an output from new input.

## Why it matters

Inference is where a trained model is used in a live workflow. Model size, hardware, input length, output length, batching, and tool use affect latency and cost, while the application still needs validation and monitoring around the model result.

## Example

A team routes simple classification requests to a smaller model and complex contract analysis to a larger model, then evaluates quality and cost for both paths.

## FAQ

### What is Inference in simple terms?

Inference is the process of using a trained model to produce an output from new input.

### Why does Inference matter for teams using AI?

Inference is where a trained model is used in a live workflow. Model size, hardware, input length, output length, batching, and tool use affect latency and cost, while the application still needs validation and monitoring around the model result.

### What is a practical example of Inference?

A team routes simple classification requests to a smaller model and complex contract analysis to a larger model, then evaluates quality and cost for both paths.


Source: https://www.luffy.so/ai-glossary/inference

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