Diffusion models are currently one of the leading generative AI approaches for image generation. We point out the relation to stochastic quantisation and demonstrate the approach for scalar fields in two dimensions. We also apply the approach to data generated using complex Langevin dynamics and contrast score-based and energy-based diffusion models.