Pareto front or ngmi. Releasing jina-reranker-v3.5: our latest 0.6B listwise reranker that takes v3's last-but-not-late interaction, makes it faster, and makes it actually good at the data enterprises search. 63.20 nDCG@10 on BEIR, beating Qwen3-Reranker-4B at ~7× fewer params.
- Most don't know (1) how easy it is to invert embedding vectors back into sentences, (2) this is a perfect task text diffusion models. Here's a 78M parameter model and live demo that recovers 80% of tokens from Qwen3-Embedding and EmbeddingGemma vectors. Works even on multilingual

