# RAGChecker

RAGChecker is an AI benchmark; this page records what it measures and traces its data, grader, and scores to primary sources.

Diagnoses retrieval-augmented generation systems with claim-level metrics for their retrieval and generation components.

## Details

- Address: Online, Global
- Website: [github.com/amazon-science/RAGChecker](<https://github.com/amazon-science/RAGChecker>)
- Tags: Helpful, Science
- Category: Retrieval
- Status: Active
- Data licence: Apache-2.0
- Data access: open
- Grader: llm-judge
- Organization: Amazon Science
- Released: 2024-06
- Paper: [arxiv.org/abs/2408.08067](<https://arxiv.org/abs/2408.08067>)
- Repository: [github.com/amazon-science/RAGChecker](<https://github.com/amazon-science/RAGChecker>)
- Top-score provenance: unknown
- ABI family: No

## Questions

### Where is RAGChecker?

RAGChecker is at Online, Global.

### How do I contact RAGChecker?

To contact RAGChecker, visit https://github.com/amazon-science/RAGChecker.

## Source

From [Benchmark primary sources](https://aibenchmarkindex.com/about), license CC0-1.0, checked 2026-10-15.

Last updated October 15, 2026.

## Links

- This benchmark on the [web page](<https://aibenchmarkindex.com/global/online/ragchecker>)
- [Retrieval in Online](<https://aibenchmarkindex.com/global/online/category/retrieval.md>)
- [More benchmarks in Online](<https://aibenchmarkindex.com/global/online.md>)

> **Check before you compare.** Benchmark methods and leaderboards change. Follow the cited primary source before using a result in a decision.