QNNPACK directly competes with the CPU backend of TensorFlow Lite and the gemmlowp library. The Caffe2 backend of PyTorch 1.0 integrates QNNPACK, and directly competes with TensorFlow Lite. QNNPACK targets only mobile CPUs, but Caffe2 integrates other backends for non-CPU targets, e.g. Apple's MPSCNN library for iPhone GPUs, Qualcomm's Snapdragon NPE for Qualcomm GPUs and DSPs, ARM ComputeLibrary for Android GPUs. Not sure what you mean by TensorFlow Cores: NVIDIA has TensorCores and TensorRT, and Google has Tensor Processing Units (TPU), but neither of these technologies are for mobile.