Evaluation

Benchmark

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In Short

A standardized test suite designed to measure specific capabilities of AI systems, enabling comparison across models and versions.

Benchmarks provide consistent measurement frameworks for AI capabilities. While valuable for comparison, they have limitations—agents can overfit to benchmarks without generalizing.

Common Benchmarks

  • MMLU: Measures multitask language understanding
  • HumanEval: Tests code generation capabilities
  • MATH: Evaluates mathematical reasoning
  • AgentBench: Assesses agent task completion

Limitations

  • Teaching to the test (benchmark overfitting)
  • May not reflect real-world performance
  • Static benchmarks become outdated
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