Benchmarked against open-source optimisation
The same 10-year open-pit scenario, the same variables, constraints and assumptions, given to Google OR-Tools and to Cognomine. Here is what came back.
| Metric | Google OR-Tools | Cognomine | Cognomine advantage |
|---|---|---|---|
| Discounted NPV | $1,667M | $1,940M | +$273M (~16%) |
| Equipment capital | $254M | $104.5M | $149.5M lower (~59% less) |
| Peak fleet | 5 diggers / 41 trucks | 2 diggers / 17 trucks | Fewer than half the diggers; 24 fewer trucks |
| Time to produce the plan | 12 h+ ¹ | ~25 seconds ² | More than 1,700x faster ¹ |
- The OR-Tools run was stopped unconverged after 12 hours. The speed multiple is a lower bound.
- Solver-to-solver comparison. OR-Tools is a CPU-only solver; Cognomine ran on cloud GPUs, the hardware it is built for.
- Both runs used an identical scenario: the same variable count, constraint sets and assumption sets.
- Cognomine produces high-quality feasible plans.
What the numbers mean
On this scenario, Cognomine found a plan worth $273M more in discounted NPV than the OR-Tools result, while cutting equipment capital by $149.5M. The gain comes from better sequencing: the plan reaches similar production with a much smaller peak fleet.
Where OR-Tools was stopped after 12 hours without converging, Cognomine returned its plan in around 25 seconds. That difference changes how planning works. Instead of committing to one run, a planner can test dozens of assumptions in an afternoon.
Benchmark results come from a single test scenario and outcomes depend on your deposit, constraints and assumptions. The comparison uses an open-source baseline because it is reproducible and free of licensing restrictions.