I misunderstood your question and thought batch_size=32 was chosen, because this setup outperforms other models.
Sure, you could try to split the 32 samples among the GPUs. If you encounter any problems, e.g. in the BatchNorm layers (since the sample size is now smaller), you could try to use NVIDIA’s apex SyncBatchNorm 83. Note that the default device (usually cuda:0) might use some more memory if you use nn.DataParallel.