JAXopt implements a collection of gradient-based optimization algorithms designed to run efficiently on GPU, TPU, and CPU. It leverages JAX’s vmap for automatic vectorization of multiple optimization problems and supports implicit differentiation for differentiating through optimization solutions. The library is primarily used for training deep learning models, bi-level optimization tasks, and research involving differentiable programming.