Will Gurobi give sub-optimla solutions even the Gap is very small (<0.01%) for MINLP ?

I am running a model, MINLP, using Gurobi, and the Gurobi converges very fast and gives the solution.

However, I found a better solution using the distributed optimization algorithm (with sub-problem still solved by Gurobi).

Therefore I wonder whether Gurobi will give a solution for large-scale MINLP that is sub-optimal even when the Gap is very small  (<0.01%) .

Many thanks for your help and time.

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Academic license - for non-commercial use only - expires 2024-12-05
Gurobi Optimizer version 11.0.0 build v11.0.0rc2 (win64 - Windows 10.0 (19045.2))

CPU model: Intel(R) Core(TM) i5-10500 CPU @ 3.10GHz, instruction set [SSE2|AVX|AVX2]
Thread count: 6 physical cores, 12 logical processors, using up to 12 threads

Optimize a model with 11350 rows, 6312 columns and 23801 nonzeros
Model fingerprint: 0x339931c0
Model has 336 quadratic constraints
Variable types: 5808 continuous, 504 integer (504 binary)
Coefficient statistics:
  Matrix range     [9e-05, 1e+06]
  QMatrix range    [1e+00, 1e+00]
  Objective range  [4e-02, 2e+03]
  Bounds range     [1e+00, 1e+00]
  RHS range        [1e-05, 3e+05]
Presolve removed 7809 rows and 2261 columns
Presolve time: 0.11s
Presolved: 3541 rows, 4051 columns, 11231 nonzeros
Presolved model has 336 quadratic constraint(s)
Variable types: 3575 continuous, 476 integer (476 binary)

Root relaxation: objective 6.639598e+03, 967 iterations, 0.01 seconds (0.01 work units)

    Nodes    |    Current Node    |     Objective Bounds      |     Work
 Expl Unexpl |  Obj  Depth IntInf | Incumbent    BestBd   Gap | It/Node Time

     0     0 6639.59788    0   21          - 6639.59788      -     -    0s
     0     0 6648.74269    0   25          - 6648.74269      -     -    0s
     0     0 6648.74269    0   23          - 6648.74269      -     -    0s
     0     0 6654.09330    0   29          - 6654.09330      -     -    0s
     0     0 6654.13535    0   26          - 6654.13535      -     -    0s
     0     0 6658.33225    0   41          - 6658.33225      -     -    0s
     0     0 6658.96974    0   32          - 6658.96974      -     -    0s
     0     0 6661.29690    0   32          - 6661.29690      -     -    0s
     0     0 6661.42445    0   32          - 6661.42445      -     -    0s
     0     0 6662.50694    0   26          - 6662.50694      -     -    0s
     0     0 6662.59565    0   30          - 6662.59565      -     -    0s
     0     0 6663.13816    0   29          - 6663.13816      -     -    0s
     0     0 6663.15665    0   29          - 6663.15665      -     -    0s
     0     0 6663.41262    0   29          - 6663.41262      -     -    0s
     0     0 6663.41697    0   29          - 6663.41697      -     -    0s
     0     0 6663.48337    0   29          - 6663.48337      -     -    0s
     0     0 6663.48337    0    7          - 6663.48337      -     -    0s
H    0     0                    6664.0417149 6663.48337  0.01%     -    0s