Background: Robotic-assisted surgery (RAS) potentially reduces workload and shortens the surgical learning curve compared to conventional laparoscopy (CL). The present study aimed to compare robotic-assisted cholecystectomy (RAC) to laparoscopic cholecystectomy (LC) in the initial learning phase for novices. Methods: In a randomized crossover study, medical students (n = 40) in their clinical years performed both LC and RAC on a cadaveric porcine model. After standardized instructions and basic skill training, group 1 started with RAC and then performed LC, while group 2 started with LC and then performed RAC. The primary endpoint was surgical performance measured with Objective Structured Assessment of Technical Skills (OSATS) score, secondary endpoints included operating time, complications (liver damage, gallbladder perforations, vessel damage), force applied to tissue, and subjective workload assessment. Results: Surgical performance was better for RAC than for LC for total OSATS (RAC = 77.4 ± 7.9 vs. LC = 73.8 ± 9.4; p = 0.025, global OSATS (RAC = 27.2 ± 1.0 vs. LC = 26.5 ± 1.6; p = 0.012, and task specific OSATS score (RAC = 50.5 ± 7.5 vs. LC = 47.1 ± 8.5; p = 0.037). There were less complications with RAC than with LC (10 (25.6%) vs. 26 (65.0%), p = 0.006) but no difference in operating times (RAC = 77.0 ± 15.3 vs. LC = 75.5 ± 15.3 min; p = 0.517). Force applied to tissue was similar. Students found RAC less physical demanding and less frustrating than LC. Conclusions: Novices performed their first cholecystectomies with better performance and less complications with RAS than with CL, while operating time showed no differences. Students perceived less subjective workload for RAS than for CL. Unlike our expectations, the lack of haptic feedback on the robotic system did not lead to higher force application during RAC than LC and did not increase tissue damage. These results show potential advantages for RAS over CL for surgical novices while performing their first RAC and LC using an ex vivo cadaveric porcine model. Registration number: researchregistry6029 Graphic abstract: [Figure not available: see fulltext.].