Comparative Analysis of RAG Performance: Evaluating OpenAI’s RAG Assistant vs. Google’s Vertex Search and Conversation

This article is the fifth in a series evaluating RAG systems using Tonic Validate, focusing specifically on OpenAI’s Rag Assistant and Google’s Vertex Search and Conversation. The evaluation tests retrieval capabilities by uploading 212 Paul Graham essays to both systems. Initial questions reveal differences in responses; Google Vertex is praised for its concise answer, while OpenAI provides a more detailed but less direct response. Overall, both systems perform reasonably well, though Google Vertex scores better in a direct answer similarity metric. OpenAI performs slightly better overall with a mean score of 3.47 compared to Vertex’s 3.3, although it faces limitations like slower response time and restrictions on file uploads. Vertex’s faster throughput makes it more viable for production, highlighting the trade-offs between accuracy and efficiency in using these RAG systems. Reader engagement is encouraged, with a call for user experiences and bonus incentives for sharing insights.

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