# modded-nanoRT leaderboard sets new speed record for Relational Transformers

Digest AI · Research · published 2026-10-22T04:00:00Z

Canonical: https://digestai.news/story/modded-nanort-leaderboard-sets-new-speed-record-for-relational-transfo

## Summary

modded-nanoRT is a new leaderboard for relational transformers that measures wall‑clock time to reach a quality target. The benchmark uses a 45‑minute learning curve and ranks six candidates. The recipe reaches the target in 305.63 seconds on one NVIDIA H200, 8.11x faster than the reference implementation, and wins 13 of 15 pairs outside the development database.

The leaderboard is open and uses typed trilinear attention, Muon and SIGReg. The authors will release the benchmark, its frozen artifacts and record runs. The code is available at https://github.com/kunumi/nanoRT.

## Key points

- modded‑nanoRT ranks relational transformer models by wall‑clock time to a quality target
- the recipe reaches the target in 305.63 seconds on one NVIDIA H200, 8.11x faster than reference
- it wins 13 of 15 pairs outside the development database

## Why it matters

A faster, open benchmark for relational transformers lowers the barrier to entry for researchers and may accelerate progress in relational AI.

## Sources

1. [Speedrunning Relational Foundation Model Pretraining](https://arxiv.org/abs/2610.28855) (arXiv cs.AI, 2026-10-22, primary source)

## Cite

Digest AI, "modded-nanoRT leaderboard sets new speed record for Relational Transformers", 22 October 2026, https://digestai.news/story/modded-nanort-leaderboard-sets-new-speed-record-for-relational-transfo

---

Written by Digest AI's editorial model from the linked sources; the sources are the record. Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse
JSON: https://digestai.news/story/modded-nanort-leaderboard-sets-new-speed-record-for-relational-transfo.json