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Zilliz Open Sources Industry-First Bilingual "Semantic Highlighting" Model to Slash RAG Token Costs and Boost Accuracy
Zilliz's bilingual semantic model cuts token use and boosts answer quality in retrieval-augmented generation applications, aiding over 10,000 organizations globally.
- From Redwood City, Zilliz announced the open-source release of its Bilingual Semantic Highlighting Model on Jan. 31, 2026, making it available for download.
- Facing rising costs and accuracy issues, James Luan, VP of Engineering at Zilliz, said RAG systems face real limits in production, driving development to address oversized context windows and cross-lingual relevance.
- Built on MiniCPM-2B, the model supports billion-scale workloads with sub-10ms latency, according to Zilliz.
- For enterprises, Zilliz says the model helps engineering teams move from prototype to production without complex infrastructure, leveraging its over 10,000 organizations worldwide customer base.
- Introducing sentence-level relevance filtering, Zilliz reports that it significantly compresses prompt size and improves downstream response quality when sending prompts to large language models .
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Zilliz Open Sources Industry-First Bilingual "Semantic Highlighting" Model to Slash RAG Token Costs and Boost Accuracy
REDWOOD CITY, Calif., Jan. 30, 2026 /PRNewswire/ -- Zilliz, the company behind the leading open-source vector database Milvus, today announced the open-source release of its Bilingual Semantic Highlighting Model, an industry-first AI model designed to dramatically reduce token usage and…
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Leaning Left1Leaning Right0Center8Last UpdatedBias Distribution89% Center
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C 89%
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