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A free, GPU-accelerated Texas Hold'em GTO solver in C++/CUDA

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I built this mostly because I love the intersection of game AI, high-performance computing, and poker.I’d love for anyone interested in game theory or CUDA optimization to tear it apart, test the accuracy, and give me feedback. Happy to answer any questions about the algorithms, the transition from CPU to GPU, or poker AI in general!

HN · launched Jul 7, 2026 · 5 upvotes (top 89%) · 0 views

Niche: mathematical solvers and optimization engines · 80 launches, 2 in the last 7 days · Explore this niche →

Category and tags

  • Horizontal
  • Analytics & BI
  • Prosumer
  • Not AI
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

No Writing a high-performance GPU-accelerated Game Theory Optimal poker solver requires advanced knowledge of algorithmic game theory (CFR/CFR+), memory layout optimization, and low-level CUDA programming.

What it would actually take: The system relies on C++ and CUDA to implement Counterfactual Regret Minimization (CFR+) over imperfect-information extensive-form game trees. The hard part is fitting massive subgame trees into limited GPU VRAM using custom compression/abstraction algorithms and maximizing SIMT warp efficiency across millions of branches. Deep specialized research expertise in computational game theory and GPU systems programming is mandatory.

Discussion

3 comments analyzed.

Feature requests: Support for other card games beyond the current one, More technical documentation on how the GPU implementation works

Competitors

Other products that read as similar to this one : 541 launches clear the similarity bar, closest 8 shown.

Attention rank: #497 of 542 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 251 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.