Free-for-all test set for QP solvers
July 23, 2026 · View on GitHub
This repository contains quadratic programs (QPs) in a format suitable for qpbenchmark. It is free-for-all, open to problems from all fields, hard and easy. Here are the reports produced by the benchmarking tool:
The methodology and limitations of the benchmark are described in the qpbenchmark readme.
Installation
The recommended process is to install the benchmark and all solvers using pixi:
pixi install
It is also possible to install the benchmark from PyPI.
Usage
Run the test set as follows:
pixi run free_for_all # full test set
pixi run free_for_all_dense # dense subset
The outcome, written to the results/ directory, is a standardized report comparing all available solvers against the different benchmark metrics. You can check out and post your own results in the Results forum.
Contributing
Do you have quadratic programs to share? Join the benchmark by submitting it to this test set: open a PR (preferred), or complete the submission form:
You can also contribute by running the benchmark on your machine and posting your results to the Results forum.
Problems
Here are all problems in this test set:
| Problem name | Source and details |
|---|---|
CONT-* | Maros-Meszaros test set |
DOCSLS | From this issue |
GNAR* | Proposed in #2 and #3, details in this paper |
ICULS* | Proposed in #1 |
LIPMWALK* | Proposed in #3, details in this paper |
QUADCMPC* | Proposed in mpc_qpbenchmark#1, details in this thesis |
WHLIPBAL* | Proposed in #4, details in this paper |
These problems have been contributed by:
- @paLeziart: QUADCMPC
- @stephane-caron: LIPMWALK, WHLIPBAL
Citation
This test set is run using qpbenchmark. If you use it in your works, you can refer to it using this citation.
See also
Related test sets that may be relevant to your use cases:
- Maros-Meszaros test set: a standard test set with problems designed to be difficult.
- Model predictive control: model predictive control problems arising e.g. in robotics.