What is the most efficient way to evaluate poker hands at scale?

The most efficient way to evaluate poker hands at scale is not to write logic that checks for straights and flushes at runtime. Instead, the industry standard for high-frequency trading (HFT) and real-money poker is pre-computed Lookup Tables (LUTs) combined with bitwise operations and SIMD (Single Instruction, Multiple Data) vectorization.

The goal is to reduce hand evaluation to a single CPU instruction or a few array lookups, achieving nanosecond-level latency. This allows the engine to evaluate millions of hands per second for Monte Carlo simulations, AI training, or real-time fairness checks.

1. The Core Architecture: Lookup Tables (LUTs)

The fundamental insight is that there are a finite number of 5-card combinations from a 52-card deck: $\binom{52}{5} = 2,598,960$.

For 7-card games (Hold'em/Omaha), it's $\binom{52}{7} = 133,784,560$.