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A 4-bit quantization of NVIDIA's TwoTower block-diffusion LM (Nemotron-Labs-TwoTower-30B-A3B-Base) that compresses both towers into ~38 GB, enabling single-GPU inference at slow speeds (~2-4 tok/s).
This paper compares xLSTM, Mamba-2, and Gated DeltaNet on complex sequence modeling tasks and finds xLSTM superior due to its enhanced state tracking and memory dynamics, validated on synthetic length-generalization tasks.