It is challenging to generate wireless channels for 5G/6G scenarios with sophisticated mobility patterns. Raytracing (RT) is one of the most adopted techniques, especially when 5G/6G millimeter frequency bands are considered. However, most ray tracers, such as Wireless InSite and Sionna's, provide limited support to mobility: only the radio transceivers move over time, while all other objects are held in fixed positions. The Raymobtime methodology was proposed to fill this gap. Raymobtime supports repositioning all mobile objects, which enables simulating advanced mobility patterns. When the Raymobtime methodology was first implemented, its RT was solely based on the commercial Wireless InSite ray tracer. This work expands Raymobtime software to also support the recent NVIDIA Sionna's ray tracer, which is open source and mostly written in Python. The preliminary results indicate that Sionna's brings a fast RT tool, but it still needs to be systematically validated against measured channels.