jina-reranker-v3.5: Faster Listwise Reranking with Hybrid Attention and Self-Distillation
Today we release jina-reranker-v3.5, a 0.6B-parameter listwise reranker that keeps the last but not late interaction of jina-reranker-v3 and makes it faster and far more capable on the data enterprises actually search. It reaches 63.20 nDCG@10 on BEIR, ahead of Qwen3-Reranker-4B with roughly 7× fewer parameters, and it reranks up to 1.56× faster than v3 on long documents. Its biggest jump is on semi-structured retrieval: +9.6 nDCG@10 over v3 on field-constrained records.