Jina Embeddings v3
Jina Embeddings v3 is a multilingual encoder for retrieval, classification and text similarity. Its Jina-XLM-RoBERTa design supports 8,192-token inputs and task-specific LoRA adapters.
How the model works
Five adapters cover retrieval queries, retrieval passages, separation, classification and text matching. Mean pooling creates vectors, and Matryoshka training permits dimensions from 32 to 1,024. Jina says it specifically tuned 30 languages, while the underlying model supports a broader language set. These are different claims and should not be treated as one coverage count.Jina Embeddings v3 model details
Use and access
The model card records a correction to vector truncation: truncating after normalization could produce non-normalized shortened vectors. Existing indexes can depend on the code revision used to generate them. Jina documents that revision for consistency. The model remains downloadable under CC BY-NC 4.0 and has API access, although newer v5 text models are available.Jina Embeddings v3 model detailsJina Embeddings v3 technical overview
Specifications & access
| Detail | Value and conditions |
|---|---|
| Launch date | |
| Access | API, Downloadable |
| Model identifiers | jina-embeddings-v3jinaai/jina-embeddings-v3jina-embeddings-v3-hf |
| Context window | 8,192 tokens Maximum input sequence in the model card; serving limits can be lower. Jina Embeddings v3 model details |
| Parameters | Approximately 570 millionJina Embeddings v3 model details |
| Embedding dimensions | 1,024; Matryoshka sizes down to 32Jina Embeddings v3 model details |
| Weight license | CC BY-NC 4.0Jina Embeddings v3 model details |
| Base model | Jina-XLM-RoBERTaJina Embeddings v3 model details |
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