GEKKO "Memory allocation failed"

I'm trying to use GEKKO to solve quite a large optimization problem locally (with remote=False).

When running the code, I get the error:

Error: At line 463 of file custom.f90
Traceback: not available, compile with -ftrace=frame or -ftrace=full
Operating system error: Not enough memory resources are available to process this command.

Memory allocation failed

So that hints that the operating system doesn't let GEKKO use enough memory.

However, I'm using a 32GB RAM machine, with nearly 25 GB free, while the model probably don't even need 10GB.

I've tried using m.options.MAX_MEMORY = 10, but this doesn't seem to matter.

Any thoughts on how to allow it to allocate more memory?

Here is some (simplified) code that triggers this error:

from gekko import GEKKO

quantiles = [(x+1)*.01 for x in range(300)]

#Initialize Model
m = GEKKO(remote=False)
#Set global options
m.options.IMODE = 3 #steady state optimization    
m.options.SOLVER=3
m.options.MAX_ITER=100000
m.options.MAX_MEMORY = 10
m.options.REDUCE=10

#initialize variables
Est_array = m.Array(m.Var,(2, 16),value=1,lb=0,ub=48)
P_ij_t = m.Array(m.Var,(4, 16, 300), lb=0, ub=1)   
Exp_ij_t = m.Array(m.Var,(4, 16, 300),value=1,lb=-36,ub=36)   
C_t = m.Array(m.Var,300,lb=0,ub=5) 

#Equations
for h in range(16): 
    for q in range(300):
        m.Equation(m.sum([P_ij_t[i,h,q] for i in range(3)]) == 1)

for (q,t) in enumerate(quantiles):
    m.Equation(C_t[q] == (  m.sum([P_ij_t[i+2,h,q]*(Est_array[i,h]-t)**2 for i in range(2) for h in range(16)]) + \
                            m.sum([P_ij_t[i,h,q]*(Est_array[1-i,15-h]-t)**2 for i in range(2) for h in range(16)]) 
    )  
    )
   
#Objective
m.Minimize(C_t[0])

#Solve simulation
#m.open_folder() 
m.solve()

#Results
print('C = ' + str(C_t[0].value[0]))

---

(All of the m.options.* parameters are things that I tried to get the solver to run, but none seem to help with the memory allocation problem).

from GEKKO "Memory allocation failed"