BigCodeBench — AI Glossary

Reference details

Related terms

• LiveCodeBench
• Pass@k
• Code Generation

Example: The library versions are part of the test

Tasks require real calls into third-party libraries rather than self-contained algorithms, which is what makes them resemble actual development work. It also makes the environment a variable in the measurement: a model writing correct code against one version of a data or plotting library can fail the same unit test after a minor release changes a default or renames an argument. The result is a property of the model *and* the pinned environment. Any comparison that does not fix the dependency set is comparing two different exams and calling them one.

Commonly confused with

This is not the same skill as competitive programming, and not the same as repository-level engineering. Library-call benchmarks test API knowledge and correct usage; competitive-programming sets test algorithms on self-contained problems; repository benchmarks test navigating and patching existing code. Models rank differently on all three.

When to use it

Reach for it when:

• Assessing practical Python ability against real libraries rather than puzzles
• Where your workload is data, scripting or glue code using common packages
• Alongside a repository-level benchmark, which tests a different capability

Reach for something else when:

• Comparing figures without the pinned dependency versions
• Generalising to other languages or ecosystems
• As a proxy for agentic engineering, which needs navigation and iteration

Primary source

• Zhuo et al., BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions (arXiv)

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