description: 'TinyMLPerf Olympics - the culmination of your TinyTorch journey! Build
  a comprehensive

  benchmarking suite using your profiler from Module 19, then compete on speed, memory,

  and efficiency. Benchmark the models you built throughout the course to see the
  impact

  of all your optimizations.

  '
difficulty: advanced
estimated_hours: 10-12
exports:
- tinytorch.benchmarking
learning_objectives:
- Build TinyMLPerf benchmark suite
- Implement fair performance comparison
- Create reproducible benchmarks
- Understand MLPerf methodology
name: Benchmarking
number: 20
prerequisites:
- Module 15: Profiling
- All optimization modules (16-19)
skills_developed:
- Benchmarking methodology
- Performance reporting
- Fair comparison techniques
- Competition optimization
type: project