One nice thing about Lite is that it's a lot easier to just include the operations you need (compared to TensorFlow 'classic'), there's fusion for common patterns, and the base interpreter is only 70KB. That covers a lot of the advantages of using XLA for mobile apps. In return you have the ability to load models separately from the code, and the ops are hand-optimized for ARM.
I'm still a fan of XLA, and I expect the two will grow closer over time, but I think Lite is better for a lot of scenarios on mobile.
I'm still a fan of XLA, and I expect the two will grow closer over time, but I think Lite is better for a lot of scenarios on mobile.