Build with Quicopt
Quicopt is a solver for hard optimization problems. You model the way you always do (Pyomo or OR-Tools MathOpt in Python) and hand the model to a single solve() call. One pip install quicopt: no new modeling language, no solver configuration, no infrastructure.
This hub collects everything you need to get going: a three-step getting started, worked tutorials for the classic optimization problems (plus a runnable script per problem class), the full client reference, and the modeling front-ends.
Getting started — free →
Try the API on a small model first. Your first call sets you up, and three steps later you have a solved model.
- ✓ No signup
- ✓ pip install quicopt
- ✓ First call sets up your key
Tutorials →
Solve a classic problem instead of brute-forcing it — assignment, knapsack, scheduling, routing and more, plus a runnable script for every problem class.
API reference →
The quicopt Python client in full: Client, solve(), the Result fields, and the async job API.
Modeling front-ends →
What you can express in Pyomo and OR-Tools MathOpt, and which front-end to pick.
Benchmarks →
What Quicopt reaches on public problem sets — LABS, Gset max-cut, maximum independent set — against the published reference results.
Questions? Talk to us.
Something unclear, hit a limit, or want to try Quicopt on your real models? Tell us what you're optimizing, we read everything and get back to you.