mxbai-rerank-base-v2
mxbai-rerank-base-v2 is a state-of-the-art open-source reranking model from the Mixedbread rerank family, offering an excellent balance between size and performance. This reinforcement-learning enhanced model excels at boosting search results across 100+ languages, handling long contexts, and supporting various use cases from code search to function-call reranking.
Model Description
mxbai-rerank-base-v2 is part of the second-generation Mixedbread rerank model family, a set of state-of-the-art reranking models that are fully open-source under the Apache 2.0 license. This 0.5B-parameter model provides an excellent balance of size, speed, and performance, making it ideal for most reranking applications.
The v2 models represent a significant advancement over the first generation, featuring:
- Reinforcement learning training - Using GRPO (Guided Reinforcement Prompt Optimization) for enhanced performance
- Multilingual capabilities - Supporting 100+ languages for global applications
- Extended context handling - Processing up to 8K tokens (32K-compatible) for comprehensive document analysis
- Complex query reasoning - Improved understanding of nuanced search intent
- Versatile applications - Excelling at code search, SQL ranking, and function-call reranking for multi-tool agents
On benchmarks, mxbai-rerank-base-v2 achieves exceptional results with an NDCG@10 score of 55.57 on BEIR average, 28.56 on Mr.TyDi multilingual datasets, 83.70 on Chinese datasets, and 31.73 on code search tasks. It delivers this performance with impressive speed, processing queries up to 8x faster than comparable solutions.
When used in combination with a keyword-based search engine such as Elasticsearch, OpenSearch, or Solr, the rerank model can be added to the end of an existing search workflow. This allows users to incorporate semantic relevance into their keyword-based search system without changing the existing infrastructure - an easy, low-complexity method of improving search results with just one line of code.
Compare with other models
| Model | Context Window | Input Price (/1M tokens) |
|---|---|---|
| mxbai rerank base v2 | 8K / 32K | $0.00 |
| mxbai rerank large v2 | 8K / 32K | $0.00 |
| mxbai rerank large v1 | 512 | $0.00 |
| mxbai rerank base v1 | 512 | $0.00 |
| mxbai rerank xsmall v1 | 512 | $0.00 |
Example
Last updated: May 6, 2025