Cryptococcus neoformans is an environmental yeast that primarily affects immunocompromised individuals, causing respiratory infections and life-threatening meningoencephalitis. Treatment is complicated by limited antifungal options, with concerns such as adverse effects, dose-limiting toxicity, blood-brain barrier permeability, and resistance development, emphasizing the critical need to optimize and expand current treatment options against invasive cryptococcosis. Galleria mellonella larvae have been introduced as an ethical intermediate for in vivo testing, bridging the gap between in vitro antifungal screening and mouse studies. However, current infection readouts in G. mellonella are indirect, insensitive, or invasive, which hampers the full potential of the model. To address the absence of a reliable non-invasive method for tracking infection, we longitudinally quantified the cryptococcal burden in G. mellonella using bioluminescence imaging (BLI). After infection with firefly luciferase-expressing C. neoformans, the resulting bioluminescence signal was quantitatively validated using colony-forming unit analysis. Longitudinal comparison of BLI to health and survival analysis revealed increased sensitivity of BLI in discriminating cryptococcal burden during early infection. Furthermore, BLI improved the detection of treatment efficacy using first-line antifungals, thereby benchmarking this model for antifungal testing. In conclusion, we introduced BLI as a real-time, quantitative readout of cryptococcal burden in G. mellonella over time, enabling more sensitive and reliable antifungal screening.