Stockfish uses alpha-beta pruning, transposition tables, handcrafted search heuristics, and an efficient NNUE evaluation network, making it extremely strong tactically and incredibly fast on CPU hardware. Leela Chess Zero (Lc0), inspired by AlphaZero, uses deep convolutional neural networks and Monte-Carlo Tree Search (MCTS), relying on a large GPU-accelerated neural network to guide which lines to explore. Stockfish calculates deeply and precisely, while Leela “understands” position patterns more intuitively, often producing quiet, strategic plans that emerge from its neural network’s training. Stockfish is faster on CPUs and best in concrete positions; Leela is GPU-heavy and often shines in long-term positional play. Their styles are complementary—like a classical calculator (Stockfish) vs a learned strategist (Leela).