NV-Embed-v2 is NVIDIA's high-performance embedding model, ranking at the top of MTEB benchmarks. Optimized for retrieval tasks with 4096 token long context support, it's the ideal choice for enterprise RAG and search applications.
Core Features
- MTEB #1: Top MTEB leaderboard ranking
- Long Context: 4096 tokens support
- Retrieval Optimized: Designed for RAG
- Fast Inference: GPU-accelerated
- Open Source: Model weights available
Performance
- MTEB Average: 69.3 score (Rank #1)
- Retrieval: Industry-leading nDCG@10
- Classification: High accuracy
- Semantic Similarity: Precise matching
Use Cases
- RAG system document embedding
- Enterprise semantic search
- Q&A system retrieval
- Document similarity computation
- Knowledge graph construction
Deployment
- NVIDIA API: Cloud API
- Local: GPU inference
- Optimization: TensorRT acceleration
Summary
NV-Embed-v2, with top MTEB performance, is the best embedding model for retrieval tasks. Long context and open-source nature make it ideal for enterprise RAG applications.
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