jina-embeddings-v3
Frontier multilingual text embedding model with 570M parameters and 8192 token-length, featuring task-specific LoRA adapters and outperforming OpenAI and Cohere embeddings on MTEB benchmark.
About this tool
Overview
jina-embeddings-v3 is a frontier multilingual text embedding model with 570M parameters and 8192 token-length, outperforming the latest proprietary embeddings from OpenAI and Cohere on MTEB.
Key Features
- 570M Parameters: Balanced size for performance and efficiency
- Long Context: Supports up to 8192 tokens
- Task-Specific LoRA Adapters: Includes adapters for query-document retrieval, clustering, classification, and text matching
- Matryoshka Embeddings: Flexible dimension truncation (32, 64, 128, 256, 512, 768, 1024) without significant performance loss
- Multilingual: Supports 89 languages with strong multilingual performance
Performance
- Outperforms OpenAI and Cohere embeddings on English tasks
- Superior performance compared to multilingual-e5-large-instruct across all multilingual tasks
- Better results than e5-mistral-7b-instruct, which has 12x more parameters
Technical Details
- Default output dimension: 1024
- Supports dimension reduction to 32-768 with Matryoshka approach
- Available on Hugging Face: jinaai/jina-embeddings-v3
- Integration with Elastic Inference Service
Use Cases
- Semantic search
- Document retrieval
- Clustering
- Classification
- Text matching
- Cross-lingual search
Availability
- Hugging Face Hub
- Jina AI API
- Elastic Inference Service
- LlamaIndex integration
Pricing
Available through Jina AI's API with both free tier and commercial plans.
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Information
Websitejina.ai
PublishedMar 14, 2026
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