> ## Documentation Index
> Fetch the complete documentation index at: https://narev.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Quality evaluations

> Configure automatic and human-in-the-loop quality evaluations in Narev to score LLM responses, detect regressions, and pick the best variant.

## What are quality evaluations?

Quality evaluations measure how well your [variants](/platform/concepts/variants) perform.

There are two types of quality evaluations:

* Evaluations that **require** a source of truth, such as expected output matching
* Evaluations that **don't require** a source of truth, such as structured output schema checks

You can define the source of truth with:

* **Expected output** defined when you create the benchmark, which works best when responses are deterministic
* **State-of-the-art model** output used as a reference baseline

## When do you use quality evaluations?

Use quality evaluations to measure how each variant performs on the same benchmark.

## How do quality evaluations work?

Quality evaluations take a model response as input and score the response against your selected evaluation criteria.