PyTorch 2.15 於 2026 年 10 月正式發布，整合 3,117 次提交、583 位貢獻者，並在分散式訓練、NVGEMM、Apple Silicon 及加速器平臺上進行多項更新。
PyTorch 2.15 以多項分散式與硬體加速最佳化，提升大模型訓練與推論效率，對開發者即時可用。
PyTorch 2.15 is here, with 3,117 commits from 583 contributors and updates across distributed training, NVGEMM, Apple Silicon, and accelerator platform support.
The release makes the rewritten NCCL backend the default and adds one-sided transports with a NIXL backend. FSDP2 and pipelining gain finer memory and communication control. It also brings faster 4-bit (NVFP4) LLM decoding on NVIDIA Blackwell GPUs, FP8 and faster decode on Apple Silicon, and broader platform support.
On Thursday, November 5, at 11 AM PST, join Tristan Rice (@rice_fry), Natalia Gimelshein, Huy Do, and Jane Xu (@janeyx99) (@Meta) for a live PyTorch 2.15 Q&A, moderated by Chris Gottbrath (Gottbrath Tech). The speakers will share an overview of the release and answer community questions about PyTorch and the new capabilities in this release.
🔗 Read the release blog and register for the live Q&A: https://t.co/PAsbeCXk0C