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Qwen3 Embedding 4B GGUF

Developed by Mungert
Qwen3-Embedding-4B is a text embedding model built on the Qwen3 series, designed specifically for text embedding and ranking tasks, and performs excellently in multilingual text processing and code retrieval.
Downloads 723
Release Time : 6/10/2025

Model Overview

This model is a text embedding model with 4B parameters, supporting over 100 languages, including various programming languages, and providing powerful multilingual, cross - language, and code retrieval capabilities.

Model Features

Exceptional versatility
Achieves state - of - the - art performance in a wide range of downstream application evaluations and performs well on the MTEB multilingual leaderboard.
Comprehensive flexibility
Offers a full range of model sizes (from 0.6B to 8B) to meet different efficiency and effectiveness requirements, and supports user - defined instructions and vector dimensions.
Multilingual capabilities
Supports over 100 languages, including various programming languages, and provides powerful multilingual, cross - language, and code retrieval capabilities.

Model Capabilities

Text embedding
Text ranking
Multilingual processing
Code retrieval

Use Cases

Information retrieval
Search engine optimization
Used to improve the relevance ranking of search engines and enhance the accuracy of query results.
Performs well in retrieval tasks and can effectively match queries and documents.
Multilingual applications
Cross - language retrieval
Supports the matching of multilingual queries and documents, suitable for international content platforms.
Maintains high retrieval performance in a multilingual environment.
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