Evals: How Do You Know Which AI Model to Trust?

The AI model at the top of a leaderboard may not be the best model for your system.

Because the leaderboard is not testing your system.

In Episode 21 of System Prompt, Peter and Val break down AI evals: what benchmarks measure, why the harness matters, and how to test models against the work you actually expect them to do.

Peter walks through a custom eval across more than 20 local and open models covering tool calling, extraction, instruction following, and real-world coding tasks.

The results were surprising. Smaller models matched or beat much larger ones. Turning reasoning on sometimes made performance worse.

The bigger lesson: an eval measures more than the model. Quantization, runtime, token budgets, reasoning settings, parsers, and timeouts can all affect the result.

WHAT WE DISCUSS

• What AI evals actually measure

• Why leaderboards only tell part of the story

• How the ha