Where AI Benchmarks Fall Short, and How To Evaluate Models Instead 

Enterprises face an overwhelming array of large language models (LLMs) from which to choose. With new releases like Meta’s Llama 3.3 alongside models like Google’s Gemma and Microsoft’s Phi, the choices have never been so varied. When you scratch below the surface, the choices also become complex.

For businesses looking to leverage LLMs, chatbots, and Agentic systems, the challenge is to evaluate which model aligns with their unique requirements, cutting through the noise of traditional benchmarks and superficial metrics.

The Flaws of…