Jina: Jina Reranker V3
jina/jina-reranker-v3
jina-reranker-v3 is a 0.6B parameter multilingual document reranker introducing a novel last but not late interaction architecture. Unlike ColBERT's separate encoding with multi-vector matching, this model performs causal self-attention between query and documents within the same context window, enabling rich cross-document interactions before extracting contextual embeddings from the last token of each document. Built on Qwen3-0.6B with 28 transformer layers and a lightweight MLP projector (1024→512→256), it processes up to 64 documents simultaneously within 131K token context. The model achieves state-of-the-art BEIR performance with 61.94 nDCG-10 while being 10× smaller than generative listwise rerankers.
Model specifications
- Input
- text
- Output
- text
- Context
- 400 tokens
- Max output
- 10,000 tokens
- Input price
- $0.05 / 1M tokens
- Output price
- $0.05 / 1M tokens
- Released
- 2026-02-14
Capabilities
- Streaming
- Playground
Provider pricing, discounts and data privacy
Compare effective provider prices, published discounts, regions, retention policies, training use, compliance, and privacy links by service tier.
Standard service tier
1 available provider · tier input average $0.05 / 1M tokens · tier output average $0.05 / 1M tokens
Jina
Tier: Standard · Region: US
Pricing
- Input
- $0.05 / 1M tokens
- Output
- $0.05 / 1M tokens
No provider discount is currently published.
Data privacy and compliance
- Region
- US
- Zero data retention
- No
- Data retention
- Unknown retention
- Used for training
- Unknown
- Data collection
- Moderated
- No
- GDPR compliant
- No
- HIPAA compliant
- No
- SOC 2 certified
- No
- BYOK supported
- No
Privacy policy · Terms · Official website · Documentation · Status · Support
Frequently asked questions
- What is Jina: Jina Reranker V3?
- jina-reranker-v3 is a 0.6B parameter multilingual document reranker introducing a novel last but not late interaction architecture. Unlike ColBERT's separate encoding with multi-vector matching, this model performs causal self-attention between query and documents within the same context window, enabling rich cross-document interactions before extracting contextual embeddings from the last token of each document. Built on Qwen3-0.6B with 28 transformer layers and a lightweight MLP projector (1024→512→256), it processes up to 64 documents simultaneously within 131K token context. The model achieves state-of-the-art BEIR performance with 61.94 nDCG-10 while being 10× smaller than generative listwise rerankers.
- How much does Jina: Jina Reranker V3 cost?
- Input costs start at $0.05 / 1M tokens and output costs start at $0.05 / 1M tokens. Provider-level prices vary by service tier.
- What is the context length of Jina: Jina Reranker V3?
- Jina: Jina Reranker V3 supports a 400 token context window and up to 10,000 output tokens.
- What capabilities does Jina: Jina Reranker V3 support?
- Jina: Jina Reranker V3 supports Streaming, Playground.
- Which providers offer Jina: Jina Reranker V3?
- Jina: Jina Reranker V3 is available from Jina.
- How do providers handle data privacy for Jina: Jina Reranker V3?
- 1 of 1 providers report that customer data is not used for training, and 0 offer zero-data-retention routing. Retention, compliance, and privacy-policy links are listed per provider.