Why You Need to Run LLM Benchmarks (AI Insight 4)

Description

Choosing an LLM without testing is like deploying code without QA. Benchmarks reveal how models perform for your specific goals: from speed and scale to bias and security. This is Part 4 of a 4-part series where Calvin Hendryx-Parker, CTO of Six Feet Up and AWS Hero, explains how to use benchmarks and leaderboards (like those from Hugging Face) to evaluate LLMs objectively. You’ll learn: - Which benchmarks measure accuracy, latency, and toxicity. - How to compare models for bias, security, and cost. - Why evaluation is key to strategic AI adoption and governance. ✨ Dive deeper: Calvin’s All Things Open talk, A Playbook for AI Adoption → https://sixfeetup.com/company/news/all-things-open-ai-a-playbook-for-ai-adoption 👉 Follow Calvin Hendryx-Parker, Six Feet Up CTO and AWS Hero, on LinkedIn for more insight: https://www.linkedin.com/in/calvinhp/ #LLM #AIBenchmarks #ModelEvaluation #AI #SoftwareDevelopment