The Glossy Kitchen consists mostly of rough metal objects, lit indirectly through tiny spherical light sources. This scene is the toughest to render with unidirectional path tracing among all our scenes. Radiance-based path guiding dramatically improves upon unidirectional path tracing. PPG [Müller et al. 2017] and our NPG-Radiance perform on-par at equal sample counts, whereas the GMMs by Vorba et al.  can not complete the rendering process because of numerical instabilities. Due to the glossy materials, incorporating the full product of the BSDF and incident illumination yields further large improvements (NPG-Product). In this scene, one-blob encoding the inputs to our neural networks is particularly important, as shown by the weak performance of NPG-Product with scalar input. Primary-sample-space path-sampling techniques offer little to no benefit over unidirectional path tracing with our NPS slightly outperforming PSSPS [Guo et al. 2018] with an equal number of samples.