Global air quality forecasting enables the study of global scale impacts of air pollutants such as long-range transport, the impact on human health and environmental degradation in remote and under-served regions, and the intersection of air quality and climate impacts. This paper will focus on the recent development of the global version of GEM-MACH, which is the operational forecasting model for Environment and Climate Change Canada. We will discuss the model with respect to its use as a global forecasting tool, a regulatory tool and a tool for scientific research. The model’s performance for a 6-year period will be assessed against satellite data, ozonesonde data and ground-based observations, as well as compared against other global air quality forecast models. Its suitability to provide chemical lateral boundary conditions for the regional model are also discussed.