Jina Reranker v2 Base Multilingual
Jina Reranker v2 Base Multilingual is a 278M-parameter cross-encoder from Jina AI with a 1024-token context, trained on 100+ languages plus code and structured data (function-calling JSON, SQL). It is roughly 6x faster than bge-reranker-v2-m3 at comparable nDCG@10 on multilingual MIRACL but is gated under CC-BY-NC-4.0 for non-commercial use only.
The fastest credible multilingual reranker, with the unusual addition of code and tool-call training data. The CC-BY-NC license eliminates it from any commercial product — use bge-reranker-v2-m3 instead unless you're prototyping or paying Jina for their API.
Overview
Jina Reranker v2 Base Multilingual is a 278M-parameter cross-encoder from Jina AI with a 1024-token context, trained on 100+ languages plus code and structured data (function-calling JSON, SQL). It is roughly 6x faster than bge-reranker-v2-m3 at comparable nDCG@10 on multilingual MIRACL but is gated under CC-BY-NC-4.0 for non-commercial use only.
Strengths
- 278M params — ~6x throughput vs. bge-reranker-v2-m3 at similar multilingual quality
- Trained on code retrieval, function-calling, and tabular data — not just prose
- Multilingual 100+ languages with strong MIRACL nDCG@10 (~68)
- Flash Attention 2 enabled, ONNX export shipped in repo
Weaknesses
- CC-BY-NC-4.0 license — commercial deployment requires Jina API contract
- 1024-token context vs. bge-v2-m3's 8192 — long passages need pre-truncation
- Custom code path (trust_remote_code=True) required for the cross-encoder head
- No fully open training data documentation — license risk for downstream fine-tuning
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 0.2 GB | 1 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of Jina Reranker v2 Base Multilingual.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run Jina Reranker v2 Base Multilingual?
Can I use Jina Reranker v2 Base Multilingual commercially?
What's the context length of Jina Reranker v2 Base Multilingual?
Source: huggingface.co/jinaai/jina-reranker-v2-base-multilingual
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify Jina Reranker v2 Base Multilingual runs on your specific hardware before committing money.