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PyTorch/Meta blog reveals Jagged Flash Attention built with TLX (Triton Low-level Extensions) on NVIDIA Blackwell B200, using ~3.2K lines of Triton code—3x less than FlashAttention-4—while outperforming FA4 by ~13% forward and ~50% backward on jagged attention shapes used in Meta's Generative Ads Model.