Background: The purpose of this study was to validate the eoSim, an affordable and mobile inanimate laparoscopic simulator with instrument tracking capabilities, regarding face, content and construct validity on complex suturing tasks. Methods: Participants recruited for this study were novices (no laparoscopic experience), target group for this training (surgical/gynaecologic/urologic residents, > 10 basic and < 20 advanced laparoscopic procedures) and experts (> 20 advanced laparoscopic procedures). Each participant performed the intracorporeal suturing exercise (Task 1), an upside down needle transfer (Task 2, developed for this study) and an anastomosis needle transfer (Task 3). Following, the participants completed a questionnaire regarding their demographics and opinion on the eoSim in terms of realism, didactic value and usability. Measured outcome parameters were time, distance, percentage of instrument tip off-screen, working area, speed, acceleration and smoothness. Results: In total, 104 participants completed the study, of which 60 novices, 31 residents and 13 experts. Face and content validity results showed a mean positive opinion on realism (3.9 Task 1, 3.6 Task 2 and 3.7 Task 3), didactic value (4.0, 3.4 and 3.7, respectively) and usability (4.2. 3.7 and 4.0, respectively). There were no significant differences in these outcomes between the specified expertise groups. Construct validity results showed significant differences between experts, target group or novices for Task 1 in terms of time (means 339, 607 and 1224 s, respectively, p < 0.001) and distance (means 8.1, 15.6 and 21.7 m, respectively, p < 0.001). Task 2 showed significant differences between groups regarding time (p < 0.001), distance (p 0.003), off-screen (p < 0.001) and working area (p < 0.001). Task 3 showed significant differences between groups, after subanalyses, on total number of stitches (p < 0.001), time per stitch (p < 0.001) and distance per stitch (p < 0.001). Conclusions: The results of this study indicate that the eoSim is a potential meaningful and valuable simulator in the training of suturing tasks.