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Research questionHow can FP4 attention exploit Blackwell tensor cores when softmax overhead dominates?Shrinking attention matrix products to FP4 does not guarantee faster execution when softmax conversion and on-chip dependencies become the bottleneck. Causal training also requires quantization choices that preserve usable gradients.
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Latest papersRecent research connected to this question, newest first.Hardware-Aware FP4 FlashAttention-4The evidence covers noncausal inference and causal attention training on Blackwell hardware, including a single-GPU 8-billion-parameter update and matched distributed training. Reported speedups are measured on an NVIDIA GB200; all tested MXFP4 probability/value training trajectories diverged.research paper · Sep 3, 2026
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