The MXFP8 Transpose Dilemma and NVIDIA's Workaround
dejavucoder · x · 2026-08-04
A developer discussed the underlying computational challenges when using the mxfp8 quantization format. Because the scaling factor applies to blocks of 32 consecutive values, standard tensor transpose operations become non-trivial (requiring dequantization, transposing, and re-quantization).
To solve this performance bottleneck, NVIDIA adopted a workaround: keeping a transposed and normal copy of the high-precision input to handle these operations directly, bypassing the complex quantization state transitions.
Related event: Analyzing MXFP8 Quantization Transpose Challenges and Memory Optimization(2 posts)→
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