# How Embedding Models Affect Retrieval-Augmented Generation Quality

DevFeed: [How Embedding Models Affect Retrieval-Augmented Generation Quality](<https://devfeed.tech/articles/why-your-rag-system-is-only-as-good-as-its-translator-model-17993.md>)

Original publisher: [Read original article](<https://blog.bytebytego.com/p/how-to-shrink-a-language-model-without>)

Author: ByteByteGo

Published: 2026-09-02T15:31:12Z

Content type: tutorial

Language: en

Sources: [ByteByteGo](<https://devfeed.tech/sources/bytebytego.md>)

Topics: [Embeddings](<https://devfeed.tech/topics/embeddings.md>), [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [Language models](<https://devfeed.tech/topics/language-models.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>)

Tags: [embedding](<https://devfeed.tech/tags/embedding.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [model](<https://devfeed.tech/tags/model.md>), [rag](<https://devfeed.tech/tags/rag.md>), [retrieval-augmented-generation](<https://devfeed.tech/tags/retrieval-augmented-generation.md>)

## AI overview

This article explains how embedding models support retrieval-augmented generation by translating words into vectors and controlling the search for relevant information before an answer is generated. It discusses why poor retrieval can produce incorrect answers even when the language model is capable, and outlines considerations for evaluating and selecting embedding models.

## Source excerpt

In this article, we're going to look at how this embedding model works in an RAG setup and what makes it such a critical part of the system.