NVIDIA/cuopt
GPU accelerated decision optimization observed · 2026-09-03
Health v2 · maintenance only
82/100
- Activity 100
- Release rhythm 84
- Longevity 36
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 57
- age_days: 512
- days_rel: 27
- days_push: 0
- n_releases_24m: 4
Adoption not part of the score
1032 stars · 225 forks observed · 2026-09-03
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
NVIDIA cuOpt is a GPU-accelerated optimization engine for linear programming, quadratic programming, mixed integer programming, and vehicle routing problems, built on a C++ core with C, Python, CLI, and server APIs. It scales to problems with millions of variables and constraints and integrates with modeling languages like CVXPY, Pyomo, JuMP, AMPL, GAMS, and PuLP.
Use cases
- solve large-scale linear programming problems on GPU
- vehicle routing optimization for delivery fleets
- solve mixed integer programming problems fast
- accelerate CVXPY or Pyomo optimization workflows
- route planning for trucks with time windows and capacity constraints
- solve quadratic programming problems at scale
- deploy optimization solver as a self-hosted microservice
When to choose
- you need near real-time solutions for very large LP/QP/MIP problems
- you have NVIDIA GPUs and want GPU-accelerated operations research
- you need vehicle routing (TSP/VRP/PDP) with heterogeneous fleets and time windows
- you want to keep existing modeling-language workflows but speed up solving
When to avoid
- you have no NVIDIA GPU hardware
- you need proven optimality guarantees for MIP, which is still beta
- your problems are small enough that CPU solvers suffice
- you need QCQP/SOCP support outside CVXPY, which is limited
Facets
library · maturity active
math sdk cli gpu-computing logistics gpu-computing data-science performance python cpp cloud self-hosted optimization linear-programming vehicle-routing operations-research mixed-integer-programming cuda solver convex-optimization nvidia algorithms linux docker gpu
10 sources
- readme: https://github.com/NVIDIA/cuopt · fetched 2026-09-03 · b0cbf3a79d17
- homepage: https://docs.nvidia.com/cuopt/user-guide/latest/introduction.html · fetched 2026-08-29 · 4d34cc94b24f
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/install.html · fetched 2026-08-29 · c0a63b2ff96a
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/routing-features.html · fetched 2026-08-29 · 705ecf22eaab
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/convex-features.html · fetched 2026-08-29 · 19997b9a51b9
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/milp-features.html · fetched 2026-08-29 · 04f610d1845e
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/cuopt-c/quick-start.html · fetched 2026-08-29 · b184655a00c4
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/cuopt-python/quick-start.html · fetched 2026-08-29 · 9c28892fed6d
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/cuopt-server/quick-start.html · fetched 2026-08-29 · 567343ed076a
- site_page: https://docs.nvidia.com/cuopt/user-guide/latest/cuopt-server/csp-guides/csp-azure.html · fetched 2026-08-29 · 6964be623260
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| NVIDIA/cuopt | main | 82 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem