SemiAnalysis tests Amazon Trainium3's native PyTorch training stack and Neuron Explorer profiler

SemiAnalysis's engineering team tested Trainium3 racks on the TorchTitan and TorchNeuron stack and found the native PyTorch experience a major improvement over the old PyTorch/XLA approach, though bugs and long compile times remain. Training Qwen3-32B on 16 Trainium2 chips reached 14,156 tokens per second at 30.47% MFU in compiled mode, a 1.28x gain over eager mode, while the gpt-oss 20B recipe took 27 minutes and 17 seconds to compile. The team also rated Neuron Explorer as the industry's leading profiler, ahead of Nvidia's and AMD's tools, and reported Trainium3 passed 89 of 96 FlexAttention test cases.