Models

Diagonal-Tiled Mixed-Precision Attention for Efficient Low-Bit MXFP Inference

Diagonal-tiled mixed-precision floating-point (MXFP) attention reduces memory and compute overhead for low-bit LLM inference, enabling cheaper deployment of large models.

Tuesday, April 7, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline

Technical paper proposing diagonal-tiled mixed-precision attention (MXFP) for efficient low-bit LLM inference. Addresses the critical problem of reducing memory/compute requirements while maintaining model quality during deployment.

Read original at arXiv CS.LG (Machine Learning)

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