osqp/osqp

Health v2 · maintenance only

Adoption not part of the score

2177 stars · 414 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OSQP is a C library for solving convex quadratic programs using an ADMM-based operator splitting method, with interfaces to Python, Julia, Matlab, R, Rust, and more. It is library-free, embeddable, warm-startable, and can detect primal/dual infeasibility.

Use cases

• solve convex quadratic programs with linear constraints
• model predictive control for robotics and control systems
• solve lasso and SVM optimization problems
• portfolio optimization
• embed a QP solver in embedded C code
• solve parametrized QPs efficiently with warm starting

When to choose

• you need a fast, robust QP solver with no external dependencies
• you need embeddable C code for real-time or embedded control
• your problems are convex QPs and you want warm-starting for repeated solves
• you need infeasibility detection in a first-order QP solver

When to avoid

• your problem is non-convex or not a quadratic program
• you need extremely high-accuracy solutions where interior-point solvers are better
• you need mixed-integer optimization

Facets

library · maturity stable

math machine-learning sdk mathematics machine-learning robotics fintech cross-platform python cpp rust jvm embedded quadratic-programming convex-optimization admm model-predictive-control numerical-optimization solver embeddable-c-code sparse-linear-algebra algorithms gpu

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