JaxMARL is a multi-agent reinforcement learning library that combines ease of use with GPU accelerated performance. It supports common multi-agent reinforcement learning environments and popular benchmark algorithms. The goal is to provide a comprehensive library for evaluating multi-agent reinforcement learning methods and comparing them with related benchmarks. It also introduces SMAX, a simplified version of the popular StarCraft Multi-Agent Challenge environment, which does not require running the StarCraft II game engine.