Unverified50% confidenceBenchmarkExact time
According to Logic42's Q3 2026 customer audit benchmark, pure vector search (RAG) has an average query latency of 180 milliseconds, 1200 tokens per query, a cost of $18 per 10,000 queries, and 41% relational accuracy.
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/16/2026
First Seen
Valid until: 10/30/2026
Sources
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Related Claims
UnverifiedTraditional vector RAG generally achieves an accuracy rate of 68%–72% in complex multi-hop query scenarios.69% similarUnverifiedVector RAG has long hovered around 40% accuracy on relational queries.68% similarUnverifiedAWS's 2024 case study with Lettria showed that layering graph-based retrieval on top of vector RAG improved answer precision by up to 35% in finance, healthcare, aviation and legal use cases.68% similarUnverified超低输入价格对RAG场景有利，因为典型RAG查询可能注入5000-20000个token的检索结果而输出仅有200-500个token67% similarUnverifiedA third-party test classifying 1,000 emails found the judgment model took 15.6 seconds at a cost of 1.77, while the large model took 48.9 seconds at a cost of 2.07—approximately 15% lower cost but roughly three times faster.65% similar
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