As a developer Neural Aimbot , I tested aptitude and spent $20 to evaluate its RCS and AI features. Unfortunately, I found no real benefit.
Here's why:
FPS Drops: Aptitude causes FPS drops, which is a critical flaw.
DirectML Over TensorRT: The developer chose DirectML but skipped TensorRT—a missed optimization opportunity.
Limited FOV: The 160 FOV limit is too restrictive; 250+ should be the standard.
FPS Misalignment: Neural and game FPS should match for better performance. Neural FPS below 100 leads to poor aiming.
RCS Flaws: The RCS doesn’t control the entire recoil pattern; it’s inconsistent and feels clunky. A better implementation would pull the aim downward smoothly throughout the spray.
In summary, Neural Aimbot needs significant improvements to justify its cost.
To be fair, Aptitude has a couple of advantages:
DirectML works out of the box, without needing TensorRT/CUDA (3GB+ downloads).
It supports AMD GPUs and has fewer setup requirements.
However, PUBG itself isn’t ideal for Neural Aimbots—it lacks center-locked crosshairs and heavily taxes the GPU.
Tested on: RTX 3070 Ti + Ryzen 7 5800X3D.
