loading . . . Visualization of NVIDIA CuOpt Every second, businesses worldwide are making critical decisions. A logistics company decides which trucks to send where. A retailer figures out how to stock its shelves. An airline scrambles to reroute flights after a storm. These aren’t just routing choices — they’re high-stakes puzzles with millions of variables, and getting them wrong costs money and, sometimes, customers.
That’s changing.
NVIDIA today announced it will open-source cuOpt, an AI-powered decision optimization engine — making the powerful software free for developers to unlock real-time optimization at an unprecedented scale.
Optimization ecosystem leaders COPT, the Xpress team at FICO, HiGHS, IBM and SimpleRose are integrating or evaluating cuOpt, accelerating decision-making across industries.
Gurobi Optimization is evaluating and testing cuOpt solvers to refine first-order algorithms for next-level performance.
NVIDIA is working with the COIN-OR Foundation to make cuOpt open source, in what is widely regarded as the oldest and largest such repository for operations research software.
Meanwhile, a team of researchers at Arizona State University, Cornell Tech, Princeton University, University of Pavia and Zuse Institute of Berlin are exploring its capabilities, developing next-generation solvers and tackling complex optimization problems with exceptional speed.
With the technology, airlines can reconfigure flight schedules mid-air to prevent cascading delays, power grids can rebalance in real time to avoid blackouts and financial institutions can manage portfolios with up-to-the-moment risk analysis.
## **Faster Optimization, Smarter Decisions**
The best-known AI applications are all about predictions — whether forecasting weather or generating the next word in a sentence. But prediction is only half the challenge. The real power comes from acting on information in real time.
That’s where cuOpt comes in.
cuOpt dynamically evaluates billions of variables — inventory levels, factory output, shipping delays, fuel costs, risk factors and regulations — and delivers the best move in near real time.
As AI agents and large language model-driven simulations take on more decision-making tasks, the need for instant optimization has never been greater. cuOpt, powered by NVIDIA GPUs, accelerates these computations by orders of magnitude.
Unlike traditional optimization methods that navigate solution spaces sequentially or with limited parallelism, cuOpt taps into GPU acceleration to evaluate millions of possibilities simultaneously — finding optimal solutions exponentially faster for specific instances.
It doesn’t replace existing techniques — it enhances them. By working alongside traditional solvers, cuOpt rapidly identifies high-quality solutions, helping CPU-based models discard bad paths faster.
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## **Why Optimization Is So Hard — and How cuOpt Does It Better******
Every decision — where to send a truck, how to schedule workers and when to rebalance power grids — is a puzzle with an exponential number of possible answers.
To put this into perspective, the number of possible ways to schedule 100 nurses in a hospital for the next month is greater than the number of atoms in the observable universe.
Many traditional solvers search for solutions sequentially or with limited parallelism — like navigating a vast maze with a flashlight, one corridor at a time. cuOpt rewrites the rules by evaluating millions of possibilities intelligently, accelerating optimization exponentially.
For years, workforce scheduling, logistics routing and supply-chain planning all took hours — sometimes days — to compute.
NVIDIA cuOpt changes that — the numbers tell the story:
* Linear programming acceleration: 70x faster on average than a CPU-based PDLP solver on large-scale benchmarks, with a 10x to 3,000x speedup range.
* Mixed-integer programming (MIP): 60x faster MIP solves, as demonstrated by SimpleRose.
* Vehicle routing: 240x speedup in dynamic routing, enabling cost to serve insights and near time route adjustments, as demonstrated by Lyric.
Decisions that once took hours or days now take seconds.
## **Optimizing for a Better World**
Better optimization doesn’t just make businesses more efficient — it makes the world more sustainable, resilient and equitable.
Smarter decision-making leads to less waste. Energy grids can distribute power more efficiently, reducing blackouts and seamlessly integrating renewables like wind and solar. Supply chains can adjust dynamically to minimize excess inventory, cutting both costs and emissions.
Hospitals in underserved regions can allocate beds, doctors and medicine in real time, helping lifesaving treatments reach patients faster. Humanitarian aid groups responding to disasters can instantly recalculate the best way to distribute food, water and medicine, reducing delays in critical moments. And public transit systems can adjust dynamically to demand, reducing congestion and travel times for millions of people.
cuOpt isn’t just about more hardware — it’s about smarter search. Instead of going through every possibility, cuOpt intelligently navigates massive search spaces, focusing on constraint edges to converge faster. By using GPU acceleration, it evaluates multiple solutions in parallel, delivering real-time, high-efficiency optimization.
## **Industry Support — a New Era for Decision Intelligence**
Optimization leaders such as FICO, Gurobi Optimization, IBM and SimpleRose are among the companies who are exploring the benefits of GPU acceleration or evaluating the possibility of integrating cuOpt into their workflows and evaluating its potential, spanning industrial planning to supply chain management and scheduling.
## **Smarter Decisions, Stronger Systems, Better Outcomes**
cuOpt redefines optimization at scale.
For businesses, as described, it means AI-powered optimization can reconfigure schedules, route fleets and reallocate resources in real time — cutting costs and boosting agility.
For developers, it provides a high-performance AI toolkit that can solve decision problems up to 3,000x faster than CPU solvers in complex optimization challenges such as network data routing — optimizing the flow of video, voice, and web traffic to reduce congestion and improve efficiency — or electricity distribution, balancing supply and demand across power grids while minimizing losses and ensuring stable transmission.
For researchers, it’s an open playground for pushing AI-driven decision-making to new frontiers.
cuOpt will be released as open source and freely available for developers, researchers and enterprises later this year.
## **See cuOpt in Action**
Explore real-world applications of cuOpt at these NVIDIA GTC sessions:
* Revolutionize Supply Chain Analytics With AI and Accelerated Computing (Presented by EY)
* Turbocharge Prescriptive Analytics and Optimization With GPU Acceleration (Presented by Simple Rose)
* Advances on Decision Optimization
* Connect With Accelerated Optimization AI Experts
* Accelerating Portfolio Optimization
For enterprise production deployments, cuOpt is supported as part of the NVIDIA AI Enterprise software platform and can be deployed as an NVIDIA NIM microservice — making it easy to integrate, scale and deploy across cloud, on-premises and edge environments.
With its open-source release, developers will be able to easily access, modify and integrate the cuOpt source code into their own solutions.
_Learn more_ _about how companies are already transforming their operations with cuOpt and_ _sign up_ _to be notified when the open-source software is available._
_See_ _notice_ _regarding software product information._
Categories: Data Center | Robotics | Software
Tags: GTC 2025 | Industrial and Manufacturing | NVIDIA AI Enterprise | NVIDIA cuOpt | NVIDIA NIM | Open Source https://blogs.nvidia.com/blog/cuopt-open-source/
