# Introducing RTEB: A New Standard for Retrieval Evaluation

DevFeed: [Introducing RTEB: A New Standard for Retrieval Evaluation](<https://devfeed.tech/articles/introducing-rteb-a-new-standard-for-retrieval-evaluation-7460.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/rteb>)

Author: Frank Liu; Kenneth Enevoldsen; Solomatin Roman; Isaac Chung; Tom Aarsen; Fődi, Zoltán

Published: 2025-10-01T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [LLM evaluation / benchmarking](<https://devfeed.tech/topics/llm-evaluation-benchmarking.md>), [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [generalization in machine learning](<https://devfeed.tech/topics/generalization-in-machine-learning.md>), [recommendation systems](<https://devfeed.tech/topics/recommendation-systems.md>)

Tags: [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [community](<https://devfeed.tech/tags/community.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [developers](<https://devfeed.tech/tags/developers.md>), [embedding](<https://devfeed.tech/tags/embedding.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [models](<https://devfeed.tech/tags/models.md>), [nlp](<https://devfeed.tech/tags/nlp.md>), [open](<https://devfeed.tech/tags/open.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rag](<https://devfeed.tech/tags/rag.md>), [recommendation-systems](<https://devfeed.tech/tags/recommendation-systems.md>), [research](<https://devfeed.tech/tags/research.md>), [retrieval](<https://devfeed.tech/tags/retrieval.md>), [search](<https://devfeed.tech/tags/search.md>), [zero-shot](<https://devfeed.tech/tags/zero-shot.md>)

## AI overview

Hugging Face introduces the beta Retrieval Embedding Benchmark (RTEB), designed to evaluate the retrieval accuracy and generalization of embedding models in real-world applications. It combines open and private datasets to provide a fairer, more transparent, application-focused evaluation standard.

## Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.