Jina Embeddings v5 Text Small is a multilingual text embedding model with 677M parameters built on the Qwen3-0.6B-Base backbone. It supports 32K context length and produces 1024-dimensional embeddings with Matryoshka representation learning (down to 32 dimensions). It uses last-token pooling and supports retrieval, text-matching, clustering, and classification tasks.
https://api.jina.ai/v1/embeddings| Model | Context | Max out | Pricing |
|---|---|---|---|
| Jina Embeddings v5 Omni Nano | 8K | — | $0.02— |
| Jina Embeddings v5 Text Nano | 8K | — | $0.02— |
| Jina Embeddings v2 Base Code | 8K | — | $0.05— |
| Jina Embeddings v2 Base DE | 8K | — | $0.05— |
| Jina Embeddings v2 Base EN | 8K | — | $0.05— |
| Jina Embeddings v2 Base ES | 8K | — | $0.05— |
| Jina Embeddings v2 Base ZH | 8K | — | $0.05— |
| Jina Embeddings v3 | 8K | — | $0.05— |
| Jina Embeddings v4 | 33K | — | $0.05— |
| Jina Embeddings v5 Omni Small | 33K | — | $0.05— |
| Jina Embeddings v5 Text Small | 33K | — | $0.05— |
/v1/models/jina/jina-embeddings-v5-text-smallJina Embeddings v5 Text Small is a multilingual text embedding model with 677M parameters built on the Qwen3-0.6B-Base backbone. It supports 32K context length and produces 1024-dimensional embeddings with Matryoshka representation learning (down to 32 dimensions). It uses last-token pooling and supports retrieval, text-matching, clustering, and classification tasks.