arxiv
PublishedJune 17, 2026 at 4:00 AM
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Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models
Publisher summary· verbatim
arXiv:2606.18114v1 Announce Type: cross Abstract: State Space Models (SSMs) such as Mamba-2 offer linear-time inference but their memory footprint limits edge deployment. Prior ternary SSM work (Slender-Mamba) trains from scratch on 150B tokens; we show a pretrained checkpoint suffices, reducing the
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Originally published on arxiv ↗