WaveGlow is a flow-based generative network that synthesizes speech from mel-spectrograms without autoregression. It combines insights from Glow and WaveNet into a single PyTorch network trained via maximum likelihood. The model achieves 1200 kHz audio generation speed on NVIDIA V100 GPUs and delivers audio quality comparable to the best publicly available WaveNet implementations.