Building the Fastest RAG Stack using SambaNova

A new RAG application queries over 36 million vectors in under 15 milliseconds and generates responses at 430 tokens per second. It utilizes Llama Index for orchestration, Qdrant for vector storage with binary quantization, and SambaNova's RDUs for fast LLM inference. This system showcases the potential for highly efficient AI using specialized hardware and optimized software components.