GravOpt Pro – Quantum-Inspired Optimizer Now Available (99.9999% MAX-CUT)
Hi HN,
I’ve been developing GravOpt, a quantum-inspired optimizer that achieves 99.9999% MAX-CUT on random 12-node graphs and 89.17% on Gset benchmarks — outperforming Goemans-Williamson.
Hi HN,
I’ve been developing GravOpt, a quantum-inspired optimizer that achieves 99.9999% MAX-CUT on random 12-node graphs and 89.17% on Gset benchmarks — outperforming Goemans-Williamson.
The open-source version is free: - `pip install gravopt` - GitHub: https://github.com/Kretski/GravOptAdaptiveE
Today, I’m launching *GravOpt Pro* — a commercial edition with: - All current & future models (Quantum, Resonance, VQE, Scheduling, etc.) - On-premise / air-gapped version - Priority support + confidential benchmarks on your data - Lifetime license: €200 (first 100 only)
Live purchase link: https://buy.stripe.com/14A28r4rEfYEaUgfwh4c800
Preprint: https://vixra.org/abs/2511.17607773 (arXiv pending)
I’d love your feedback — especially if you work on combinatorial optimization, quantum algorithms, or industrial scheduling.
P.S. If you beat my Gset score — I owe you a beer in Sofia :)