Zeta is a library of modular building blocks for AI model development in PyTorch. It provides carefully optimized components including attention mechanisms (multi-query attention, flash attention, sigmoid attention), mixture of experts routing, feedforward networks, normalization layers, and other transformer architecture components. Developers can assemble state-of-the-art models by combining these pre-built, tested modules rather than implementing them from scratch.