#DeepSearcher

The benchmark suggests a practical routing rule: swap general-purpose LLM calls for Jev only on narrow, high-frequency decisions like stopping checks, and keep dedicated rerankers like Voyage rerank-3 for re-ranking. Teams running RAG pipelines can use the latency and cost figures to decide where Jev cuts spend without hurting recall. Full results are on Milvus's blog.

Milvus@milvusioSource

The benchmarks show where cheap small models can replace larger ones in RAG pipelines: stopping decisions and relationship filtering see large latency and cost savings with matched recall. Engineers building retrieval systems can use the published code to pick where to route between Jev, GPT-5-mini and Voyage rerank-3. The evaluation includes Chinese-language queries, useful for teams serving bilingual users.

Milvus@milvusioSource