jina-embeddings-v2-base-en
A second-generation long-context English encoder for text-retrieval baselines.
Deployment
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Academic Publications
arXiv October 30, 2023 Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long DocumentsDecember 17, 2024 • 12 minutes read Text Embeddings Fail to Capture Word Order and How to Fix It Text embedding models struggle with capturing subtle linguistic nuances like word order, directional relationships, temporal sequences, causal connections, comparisons, and negation. Understanding these challenges is key to improving model performance.October 25, 2024 • 19 minutes read Finding Optimal Breakpoints in Long Documents Using Small Language Models We trained three small language models to better segment long documents into chunks, and here are the key lessons we learned.October 15, 2024 • 9 minutes read Fact-Checking with New Grounding API in Jina Reader With the new g.jina.ai, you can easily ground statements to reduce LLM hallucinations or improve the integrity of human-written content.September 27, 2024 • 15 minutes read Migration From Jina Embeddings v2 to v3 We collected some tips to help you migrate from Jina Embeddings v2 to v3.September 18, 2024 • 10 minutes read Jina Embeddings v3: A Frontier Multilingual Embedding Model 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.
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- Released
- 2023-10-28
- Parameters
- 137M
- Context length
- 8K tokens
- Output dimensions
- 768
- Inputs
- text
- Languages
- en
- Outputs
- vector
- Availability
- api · huggingface · aws · azure · airgapped
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The catalog lists 768 output dimensions. Supported dimensions and input types depend on the model; check the request schema before switching a production index.
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Catalog checked on September 7, 2026. This is an independently prepared Chatsax guide to Jina models.