2026
Bridging the Gap Between Promise and Performance for FP4 Quantization
Vage Egiazarian, Roberto L. Castro, Denis Kuznedelev, Andrei Panferov, Saleh Ashkboos, Eldar Kurtic +5
ICLR 2026poster
The recent hardware-accelerated microscaling 4-bit floating-point formats such as MXFP4 and NVFP4, supported on NVIDIA and AMD GPUs, promise to revolutionize large language model (LLM) inference. Yet, their practical benefits remain unproven. We present the first comprehensive study of MXFP4 and NV…