Benchmark and Engineering Assessment
How to measure the capabilities of AI Coding models? From Benchmark to real engineering evaluation
Core Issues
Why is it that a model with a high public Benchmark score is not necessarily better in real projects? How should teams build their own assessment sets?
Article structure
- Disclose the value and limitations of Benchmark
- Model capabilities, Agent capabilities and tool chain capabilities
- Construct representative evaluation sets from real tasks
- Success rate, quality, cost and manual intervention indicators
- Model upgrade and capability regression testing
Completion criteria
Readers are able to define a set of representative tasks, scoring rules, and model selection processes for their teams.