benchopt/benchopt

A framework for reproducible, comparable benchmarks

68
/ 100
Established

This tool helps machine learning researchers and practitioners rigorously compare different optimization algorithms or machine learning models. You provide the problem definition, datasets, and various solution methods, and it outputs reproducible performance metrics and plots. It is used by those who need to evaluate and select the best algorithm for a specific machine learning task, ensuring fairness and transparency in comparisons.

294 stars. Available on PyPI.

Use this if you need to objectively benchmark and compare the performance of multiple machine learning algorithms or optimization solvers across different datasets and programming languages.

Not ideal if you are looking for a tool to develop or train individual machine learning models rather than comparing existing ones.

machine-learning-research algorithm-benchmarking optimization-solver-comparison reproducible-science data-science-workflow
Maintenance 10 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 23 / 25

How are scores calculated?

Stars

294

Forks

66

Language

Python

License

BSD-3-Clause

Last pushed

Mar 12, 2026

Commits (30d)

0

Dependencies

13

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