Training a ResNet-50 on ImageNet for 100 epochs takes 4.2 hours on PyTorch 2.4, 5.1 hours on TensorFlow 2.18, and 3.8 hours on JAX 0.5 – but raw speed is only 1/10th of the story for production teams.

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Key Insights

JAX 0.5 delivers 12% faster 100-epoch training than PyTorch 2.4 on NVIDIA A100 GPUs for CNN workloads

TensorFlow 2.18 reduces inference latency by 18% vs PyTorch 2.4 for mobile-optimized TFLite exports

PyTorch 2.4’s torch.compile reduces epoch time by 34% over eager mode, closing the gap with JAX

JAX 0.5 will overtake PyTorch in research adoption by Q3 2026 per current GitHub commit trends

Methodology

All benchmarks were run on a node with 1x NVIDIA…