LayerNorm vs RMSNorm for Fine-Tuning LLMs in 2026

LayerNorm computes both mean and variance for each token, then applies learned scale and bias parameters. RMSNorm drops the mean-subtraction step entirely and uses only a scale parameter, cutting the learnable parameters in half—from 2d to just d, where d is your model width. That simplification…