BigCodeBench
codingBigCodeBench evaluates practical code generation with 1,140 challenging tasks that require using libraries like NumPy, Pandas, and Matplotlib — going beyond simple algorithmic puzzles to test real-world software development.
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Models Tested
0.0
Average Score
0–100
Scale Range
1.1x
Weight
How It Works
Models must generate complete Python functions that use complex library APIs correctly. Each solution is tested against comprehensive unit tests. Tasks involve data processing, visualisation, file I/O, and multi-library integration.
Why It Matters
Real programming involves using libraries and frameworks, not just writing algorithms from scratch. BigCodeBench tests whether models can write the kind of code that developers actually write every day.
Limitations
Python-only. Library versions and API changes can affect results over time. Some tasks may be solvable through pattern matching of common library usage patterns.