Reranker Models
Supported Models
Section titled “Supported Models”| Model | Max Length | Notes |
|---|---|---|
BAAI/bge-reranker-v2-m3 | 8192 | Multilingual |
jinaai/jina-reranker-v2-base-multilingual | 1024 | Multilingual |
Alibaba-NLP/gte-reranker-modernbert-base | 8192 | ModernBERT architecture |
cross-encoder/ms-marco-MiniLM-L-12-v2 | 512 | Smaller, faster |
See Full model catalog for the complete list.
Model Selection
Section titled “Model Selection”By Language Support
Section titled “By Language Support”English only:
BAAI/bge-reranker-base,BAAI/bge-reranker-largecross-encoder/ms-marco-MiniLM-L-6-v2,cross-encoder/ms-marco-MiniLM-L-12-v2
Multilingual (100+ languages):
BAAI/bge-reranker-v2-m3jinaai/jina-reranker-v2-base-multilingualjinaai/jina-colbert-v2
By Context Length
Section titled “By Context Length”Short context (512 tokens):
BAAI/bge-reranker-base,BAAI/bge-reranker-largecross-encoder/ms-marco-MiniLM-L-*colbert-ir/colbertv2.0,mixedbread-ai/mxbai-colbert-large-v1
Medium context (1024 tokens):
jinaai/jina-reranker-v2-base-multilingual
Long context (8192 tokens):
BAAI/bge-reranker-v2-m3Alibaba-NLP/gte-reranker-modernbert-basemixedbread-ai/mxbai-rerank-base-v2,mixedbread-ai/mxbai-rerank-large-v2jinaai/jina-colbert-v2,lightonai/GTE-ModernColBERT-v1,lightonai/Reason-ModernColBERT
By Size
Section titled “By Size”Compact (fast inference):
cross-encoder/ms-marco-MiniLM-L-6-v2- smallest cross-encodermixedbread-ai/mxbai-edge-colbert-v0-32m- 32M parametersanswerdotai/answerai-colbert-small-v1- compact ColBERT
Large (higher capacity):
BAAI/bge-reranker-largemixedbread-ai/mxbai-rerank-large-v2mixedbread-ai/mxbai-colbert-large-v1lightonai/Reason-ModernColBERT- long context (8192), ModernBERT family
Benchmarking
Section titled “Benchmarking”The best reranker for your workload is the one that wins on your data. See Evals for how to measure quality and performance, and the retrieval-ablation example in the SIE repository for a complete benchmark comparing rerankers and retrieval strategies end to end:
cd examples/retrieval-ablationuv sync
# Validate config (no GPU needed)uv run python benchmark_ablation.py --dry-runWhat’s Next
Section titled “What’s Next”- Multi-vector reranking - ColBERT MaxSim scoring
- Full model catalog - all supported models