Background: Minimally invasive surgery evolves continuously with novel tools complementing standard laparoscopic instruments (SLI). Articulating laparoscopic instruments (ALI) provide enhanced dexterity resembling robotic systems while remaining more affordable and accessible. However, comparative data on their learning curve and performance are limited. This study investigated ALI training and performance in a controlled simulator setting. Methods: Fifty-three medical students participated. After baseline measurement, all participants underwent the same modified Fundamentals of Laparoscopic Surgery (FLS) training curriculum but were randomized in either using ALI or SLI. Learning curves were tracked for the Peg transfer and suture and knot tasks until a predefined proficiency level was reached. All participants then completed final assessments using both instrument types. The primary endpoint was peak force; secondary endpoints included instrument motion metrics, task time, error rate, and SURG-TLX workload scores. Results: The ALI group demonstrated a slower learning curve in the Peg transfer task compared to the SLI group based on task time (p < 0.001), peak force (p = 0.02), and path length (p < 0.001). In the final assessment, peak force was comparable between groups (Peg: p = 0.17; Suture: p = 0.28), while ALI use resulted in greater path length (Peg: p < 0.001; Suture: p = 0.01) and longer task time (p < 0.001). Error rates and SURG-TLX scores did not differ. In the crossover assessment, prior ALI training resulted in comparable results for SLI for most parameters, including peak force (Peg: p = 0.97, suture: p = 0.05), instrument speed (Peg: p = 0.13, suture: p = 0.27) or error rate (Peg: p = 0.06; suture: p = 0.21). Conclusion: Although ALI require a longer learning curve, training with these instruments transfers effectively to standard laparoscopic skills. Their robotic-like motion and accessibility support incorporating ALI into surgical education.