The difference in the learning rate would come from the loss reduction.
The second approach uses a sum to reduce the loss and would thus create larger loss values and with it larger gradients. To let this approach converge you would use a lower learning rate.
On the other hand, the first approach uses the default mean reduction, will create smaller loss values and also smaller gradients, so that you might need to use a larger learning rate.