Very small values of weights afftects inference time on board i500?

Hi everyone.
I have issue when working with Tflite model. My original Tensorflow model has 2 layers with very small weights (-1.3e-30, 1.3e-30) and when convert this model to Tflite, the quantization parameters for these layers like this: -1.3e-30 < scale (q - 128) < 1.3e-30. And the inference time of this Tflite model on board i500 is large, abnormal comparing with other model. I think the problem is with very small values, may be in board i500 is needed to be process underflow.

Could you give me any advice, please?