Jina ColBERT v2

Overview

Jina ColBERT v2 is a state-of-the-art multilingual information retrieval model that combines the power of ColBERT's late interaction mechanism with extensive language support and modern embedding techniques.

Features

• Multilingual Support: Works with 89 languages with strong performance across major global languages
• Late Interaction: Token-level embeddings with late interaction for improved relevance
• Long Context: 8192 token input context window for processing lengthy documents
• Matryoshka Embeddings: Flexible embedding dimensions (128, 96, or 64) for efficiency-precision tradeoffs
• High Performance: 6.5% improvement over original ColBERT-v2 on English tasks
• Storage Efficiency: Reduced dimensions from 128 to 64 with only 1.5% performance decrease
• BEIR Benchmark: Average score of 0.521 across 14 BEIR benchmarks

Performance Characteristics

• Using 64-dimensional embeddings cuts storage requirements in half
• Minimal performance degradation with dimension reduction
• Significant cost savings in production deployments
• Excellent cross-lingual performance

Use Cases

• Multilingual semantic search
• Cross-lingual information retrieval
• Document ranking and reranking
• Question answering systems
• Enterprise search applications

Integration

Works with vector databases like Weaviate and can be accessed via Jina AI's embedding API or deployed locally using Hugging Face models.

Pricing

Available through Jina AI's API with usage-based pricing. Open-source weights available for self-hosting.