AudioTETRIS is a training-free, two-stage framework for compressing audio tokens in Large Audio Language Models (LALMs) without losing performance. It uses the audio encoder's representation geometry as an acoustic prior to compute a per-token fused score, which drives progressive top-$k$ token selection. This results in near-uncompressed performance using only 25% of audio tokens.