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Nemotron-Cascade 2: Post-Training LLMs with Cascade RL, On-Policy Distillation (arxiv.org)
2 points by gmays 191 days ago | hide | past | pdf | discuss on HN

In plain words: A 30-billion-part model using just 3 billion, trained by practicing across many domains and copying the best teacher in each. It hit gold-medal level at the IMO, IOI, and ICPC with 20 times fewer parameters than the only other model that has.

Abstract · Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation

We introduce Nemotron-Cascade 2, an open 30B MoE model with 3B activated parameters that delivers best-in-class reasoning and strong agentic capabilities. Despite its compact size, its mathematical and coding reasoning performance approaches that of frontier open models. It is the second open-weight LLM, after DeepSeekV3.2-Speciale-671B-A37B, to achieve Gold Medal-level performance in the 2025 International Mathematical Olympiad (IMO), the International Olympiad in Informatics (IOI), and the ICPC World Finals, demonstrating remarkably high intelligence density with 20x fewer parameters. In contrast to Nemotron-Cascade 1, the key technical advancements are as follows. After SFT on a meticulously curated dataset, we substantially expand Cascade RL to cover a much broader spectrum of reasoning and agentic domains. Furthermore, we introduce multi-domain on-policy distillation from the strongest intermediate teacher models for each domain throughout the Cascade RL process, allowing us to efficiently recover benchmark regressions and sustain strong performance gains along the way. We release the collection of model checkpoint and training data.

Zhuolin Yang, Zihan Liu, Yang Chen, Wenliang Dai, Boxin Wang, Sheng-Chieh Lin, Chankyu Lee, Yangyi Chen, Dongfu Jiang, Jiafan He, Renjie Pi, Grace Lam, et al.
arXiv:2603.19220 · cs.CL, cs.AI, cs.LG · submitted Mar 19, 2026 · updated Mar 22, 2026
abstract · pdf · html · We release the model and data at https://huggingface.co/collections/nvidia/nemotron-cascade-2

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