I benchmarked 7 LLMs on 100 identical prompts. The cost gap shocked me.
A developer has created an open-source framework to benchmark Large Language Models (LLMs) across five key metrics: accuracy, latency, cost, hallucination rate, and reasoning quality. The framework highlights a significant cost disparity between models like GPT-4o and Gemini 1.5 Flash, showing that while GPT-4o may be slightly more accurate, Gemini Flash is orders of magnitude cheaper for high-volume usage. The developer argues that traditional leaderboards focusing solely on accuracy are misleading for production applications, and users should instead benchmark models against their own data and use cases. AI
IMPACT Provides a practical framework for developers to select cost-effective LLMs based on real-world usage metrics beyond just accuracy.