@willdepue: great paper, don’t buy the width mixing (i think fixed width probably better) and feel like they should be able to get …
Summary
The paper introduces Matryoshka Language Model Suites, which nests multiple model sizes (500M, 1.5B, 3B) into a single architecture for joint training, allowing smaller models to benefit from distillation with the largest model.
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Cached at: 08/22/26, 03:24 AM
great paper, don’t buy the width mixing (i think fixed width probably better) and feel like they should be able to get CE wins here for the small model that they’re not getting. really cool!
alphaXiv (@askalphaxiv): “Matryoshka Language Model Suites”
Instead of training every model size separately, this paper nests 500M, 1.5B, and 3B models inside one architecture and trains them together.
The smaller models are standalone checkpoints, get near-free distillation from the largest model, and
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