Jina Embeddings

Jina Embeddings is a family of open-source embedding models from Jina AI — notable for supporting very long input contexts and for the company's broader open-source AI ecosystem (Jina, Finetuner, DocArray, Jina CLIP). The jina-embeddings-v2-base-en model supports 8K-token input contexts (longer than most contemporary embedders at release). The jina-embeddings-v3 model further extends this to 8192 tokens with strong multilingual support across 89 languages and uses Matryoshka Representation Learning for variable-dimension outputs. Performance on MTEB benchmark places Jina embeddings competitive with the strongest open-source options. Available under Apache 2.0 license with weights on Hugging Face. Jina also produces multimodal variants (Jina CLIP) and code-specialized embeddings. Real-world deployments include long-document retrieval (entire research papers or legal contracts in one embedding), multilingual enterprise search, code search, and any application requiring long-context embedding without aggressive chunking. AI governance, AI compliance, and AI risk management programs deploy Jina Embeddings for long-document retrieval supporting responsible AI through efficient long-context embedding in enterprise AI environments.

Centralpoint Routes to Jina Embeddings for Long-Context Retrieval: Oxcyon's Centralpoint AI Governance Platform powers long-document retrieval with Jina embeddings alongside OpenAI, Cohere, Voyage, BGE, and other models. Centralpoint meters every call, keeps prompts and skills on-prem, and embeds long-context chatbots into your portals via one JavaScript line.


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