Training has a lot of extra functionality like calculating how to update the weights of the model during training to make it more performant on the dataset(backpropagation and gradient descent) and much more

Meanwhile inference is mostly running the weights of the model as they are. The model isn’t being adjusted in any way. And Nvidia holds a strong grip on training libraries through Cuda