If the goal of gradient descent is to find global minimum for cost, why is that we are picking up the value at the end of iterations? What if one of the earlier iteration has a minimum value?

Below is what is found as the last value of b and w at cost 6.7560

alpha = 0.01 b=100.011567727362 w=199.99285075131766

cost 6.745014662580395e-06

Where is one of the earlier iterations, I found the below values

alpha = 0.01 b=100.08531003189917 w=199.947275500705

cost 0.00036684872861835616

I know the b and w values are almost the same, but theoritcally, they are not exactly minimum. What am I missing here?