---
title: How to measure prompt performance?
description: Discover different approaches to evaluate and benchmark the performance of your prompts using Langfuse features like Playground, Releases & Versioning, and Datasets.
tags: [prompt-management]
---

# How to measure the performance of prompts?

Depending on the scale of your experiments, you can take several approaches:

1. **[Playground](/docs/prompt-management/features/playground)** – ideal for quick, single-prompt experiments directly in the UI.
2. **[Releases and Versioning](/docs/observability/features/releases-and-versioning)** – perform A/B tests and structured experiments in production to compare prompt iterations.
3. **[Datasets](/docs/evaluation/features/datasets)** – benchmark prompts or entire applications offline (or in dev) against a set of reference inputs.

Each of these features integrates tightly with Langfuse’s tracing and evaluation capabilities, allowing you to track metrics, costs, and quality scores over time.

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## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/faq/all/how-to-measure-prompt-performance.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.