AI benchmark: complete definition in AI for SMEs

An AI benchmark is a comparative evaluation of AI systems on a standardized test set, to measure their relative performance: accuracy, source fidelity, format compliance, speed, cost. Benchmarks can be public (reference test sets from research) or private (your own use cases and your own data) — the latter are the most relevant for business decisions.

What it changes for an SME

The private benchmark is the tool that turns a model choice into a quantified decision:

• comparing several models on your real use cases: "GPT-4o answers correctly 92% of my 50 support questions, Claude 96%, Mistral 81%";
• measuring cost: for the same request volume, one option costs 40% less;
• verifying after migration that the new model broke nothing: rerun the benchmark regularly.

Best practice

A good private benchmark uses 20 to 50 real cases, including edge cases and trap cases (hallucinations to detect). It is replayed at every model or prompt change. In fractional AI leadership, we set up this test set from the first project and reuse it afterward.