sbi provides tools for performing likelihood-free Bayesian parameter inference when explicit likelihood functions are unavailable. The package implements neural posterior estimation, neural likelihood estimation, and related simulation-based inference methods using PyTorch as its computational backbone. It offers both low-level interfaces for researchers and high-level APIs for practitioners to estimate posterior distributions over simulator parameters from observed data.