Model reference · open weights
jina-reranker is an open-weight embedding model from jinaai, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
jina-reranker-v3: Listwise Document Reranker for SOTA Multilingual Retrieval Blog | API | AWS | Azure | GCP | Arxiv | Successor: v3.5 [!IMPORTANT] Prefer jina-reranker-v3.5 for new projects — it is a drop-in upgrade with stronger domain / multilingual / structured rankings and faster listwise inference. Same API; switch the model id from jinaai/jina-reranker-v3 to jinaai/jina-reranker-v3.5. [!TIP] GGUF with quantizations and MLX versions are now available. jina-reranker-v3 is a 0.6B parameter multilingual document reranker with 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, 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. Usage Local Inference Use transformers for local inference: Installation: Load the model: Rank documents: API Reference: Returns: List of dicts with keys: - document: Original document text - relevancescore: Float score (higher = more relevant) - index: Position in input documents list - embedding: Document embedding (if returnembeddings=True) Example with options: API Use Jina AI's Reranker API for the fastest integration: Response format: Citation If you find jina-reranker-v3 useful in your research, please cite our technical report: License jina-reranker-v3 is listed on AWS & Azure. If you need to use it beyond those platforms or on-premises within your company, note that the model is licensed under CC BY-NC 4.0. For commercial usage inquiries, feel free to contact us.
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | jinaai |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 597M |
| Context | 128k tokens |
| Variants | 2 |
| Runs with | transformers |
| Based on | Qwen/Qwen3-0.6B |
| Released | 2025-09-18 |
| Popularity | 806k downloads / month |
| Likes | 143 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
Using it via the API
Once AxForge deploys jina-reranker for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (jina-reranker below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"jina-reranker","input":"text to embed"}'
Licence
The weights are open but cc-by-nc-4.0 needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗
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