Matryoshka Matches Standard Model Performance with Flexible Width/Depth
nthngdy · x · 2026-08-19
The performance of the Matryoshka suite is on par with a standard suite trained on the same data, and consistently improves over an iso-FLOPs suite. In this design, each submodel feeds its output to another layer stack corresponding to the next submodel. Unlike past work, this design lets each submodel have adjustable width and depth, providing a large design space for memory and compute footprints.
Related event: Matryoshka LM Suites: Nested Training Cuts Compute by 36%(8 posts)→
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