---
title: BAAI/bge-reranker-base
description: We have updated the new reranker, supporting larger lengths, more languages, and achieving better performance.. XLM-RoBERTa, 278M parameters.
canonical_url: https://superlinked.com/models/baai-bge-reranker-base
last_updated: 2026-09-05
---

# BAAI/bge-reranker-base

We have updated the new reranker, supporting larger lengths, more languages, and achieving better performance.

Source: [BAAI/bge-reranker-base on HuggingFace](https://huggingface.co/BAAI/bge-reranker-base)

## Overview

| Field | Value |
|-------|-------|
| Architecture | XLM-RoBERTa |
| Parameters | 278M |
| Tasks | Score |
| Outputs | Score |
| Max sequence length | 512 tokens |
| License | mit |
| Inputs | text |
| Languages | en, zh |

## Benchmarks

### AskUbuntuDupQuestions

Domain: technology · Task: reranking · Language: en

Duplicate question detection from AskUbuntu

Corpus: 6,743 · Queries: 360

**Quality:** ndcg at 10: 0.5926 · map at 10: 0.4326 · mrr at 10: 0.6741

**Performance (L4 b1 c16):** Query 5.0K tok/s · Query p50 33.2ms

[Reference](https://github.com/taolei87/askubuntu)

### CMedQAv1Reranking

Domain: medical · Task: reranking · Language: zh

Chinese medical question answering reranking (v1)

Corpus: 100,000 · Queries: 2,000

**Quality:** map at 10: 0.8073 · mrr at 10: 0.8414

[Reference](https://github.com/zhangsheng93/cMedQA)

### CMedQAv2Reranking

Domain: medical · Task: reranking · Language: zh

Chinese medical question answering reranking (v2)

Corpus: 108,000 · Queries: 4,000

**Quality:** map at 10: 0.8358 · mrr at 10: 0.8679

[Reference](https://github.com/zhangsheng93/cMedQA2)

### CQADupstackPhysicsRetrieval

Domain: scientific · Task: retrieval · Language: en

Duplicate question retrieval from StackExchange Physics

Corpus: 38,314 · Queries: 1,039

**Quality:** map at 10: 0.3342 · mrr at 10: 0.4022 · ndcg at 10: 0.3924

[Reference](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/)

### CosQA

Domain: technology · Task: retrieval · Language: en

Code search with natural language queries

Corpus: 6,267 · Queries: 500

**Quality:** map at 10: 0.2056 · mrr at 10: 0.2240 · ndcg at 10: 0.2696

[Reference](https://arxiv.org/abs/2105.13239)

### FiQA2018

Domain: finance · Task: retrieval · Language: en

Financial opinion mining and question answering

Corpus: 57,599 · Queries: 648

**Quality:** map at 10: 0.2768 · mrr at 10: 0.4362 · ndcg at 10: 0.3591

[Reference](https://sites.google.com/view/fiqa/)

### LegalBenchConsumerContractsQA

Domain: legal · Task: retrieval · Language: en

Question answering on consumer contracts

Corpus: 153 · Queries: 396

**Quality:** map at 10: 0.6649 · mrr at 10: 0.6688 · ndcg at 10: 0.7246

[Reference](https://huggingface.co/datasets/nguha/legalbench)

### MMarcoReranking

Domain: general · Task: reranking · Language: zh

Multilingual MARCO passage reranking (Chinese)

**Quality:** map at 10: 0.3422 · mrr at 10: 0.3460

[Reference](https://arxiv.org/abs/2304.03679)

### NFCorpus

Domain: medical · Task: retrieval · Language: en

Biomedical literature search from NutritionFacts.org

Corpus: 3,593 · Queries: 323

**Quality:** map at 10: 0.2319 · mrr at 10: 0.5476 · ndcg at 10: 0.3292

[Reference](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/)

### SCIDOCS

Domain: scientific · Task: retrieval · Language: en

Citation prediction, document classification, and recommendation for scientific papers

Corpus: 25,656 · Queries: 1,000

**Quality:** map at 10: 0.0998 · mrr at 10: 0.3074 · ndcg at 10: 0.1742

[Reference](https://allenai.org/data/scidocs)

### SciFact

Domain: scientific · Task: retrieval · Language: en

Scientific claim verification using research literature

Corpus: 5,183 · Queries: 300

**Quality:** map at 10: 0.6750 · mrr at 10: 0.6924 · ndcg at 10: 0.7232

[Reference](https://github.com/allenai/scifact)

### StackOverflowQA

Domain: technology · Task: retrieval · Language: en

Programming question answering from Stack Overflow

Corpus: 19,931 · Queries: 1,994

**Quality:** map at 10: 0.3712 · mrr at 10: 0.3879 · ndcg at 10: 0.4310

[Reference](https://arxiv.org/abs/2407.02883)

### T2Reranking

Domain: general · Task: reranking · Language: zh

Chinese passage ranking benchmark

**Quality:** map at 10: 0.5590 · mrr at 10: 0.7716

[Reference](https://arxiv.org/abs/2304.03679)