PyTorch 2.14 Release Blog – PyTorch

PyTorch 2.14 ships with 2,995 commits from 487 contributors, headlined by NVGEMM (CuTeDSL-generated CUTLASS kernels with epilogue fusion for Inductor), a new nccl2 distributed backend ported from torchcomms with fault-tolerant process-group reconfiguration and one-sided RMA windows, and native linear algebra on Apple Silicon (SVD, eigh, QR, Cholesky). Compiler additions include torch.switch for multi-way branching, CUDA-graph-capturable torch.while_loop, and declarative dynamic shapes via @dynamic_spec shared across compile, export, and make_fx. Platform support expands with ROCm 7.14, Intel XPU native graph capture, Rubin (sm_107) targeting, and experimental torch.compile support for complex-valued tensors. Python 3.15 (including free-threaded 3.15t) gets eager-mode wheels, but torch.compile is not yet supported under 3.15 and raises a RuntimeError if invoked. TorchVision 0.29 is now ABI stable against future torch versions, decoupling its release cadence from PyTorch's.

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