Llama-Nemotron: Efficient Reasoning Models
Authors: name: Akhiad Bercovich, name: Itay Levy, name: Izik Golan, name: Mohammad Dabbah, name: Ran El-Yaniv, name: Omri Puny, name: Ido Galil, name: Zach Moshe, name: Tomer Ronen, name: Najeeb Nabwani, name: Ido Shahaf, name: Oren Tropp, name: Ehud Karpas, name: Ran Zilberstein, name: Jiaqi Zeng, name: Soumye Singhal, name: Alexander Bukharin, name: Yian Zhang, name: Tugrul Konuk, name: Gerald Shen, name: Ameya Sunil Mahabaleshwarkar, name: Bilal Kartal, name: Yoshi Suhara, name: Olivier Delalleau, name: Zijia Chen, name: Zhilin Wang, name: David Mosallanezhad, name: Adi Renduchintala, name: Haifeng Qian, name: Dima Rekesh, name: Fei Jia, name: Somshubra Majumdar, name: Vahid Noroozi, name: Wasi Uddin Ahmad, name: Sean Narenthiran, name: Aleksander Ficek, name: Mehrzad Samadi, name: Jocelyn Huang, name: Siddhartha Jain, name: Igor Gitman, name: Ivan Moshkov, name: Wei Du, name: Shubham Toshniwal, name: George Armstrong, name: Branislav Kisacanin, name: Matvei Novikov, name: Daria Gitman, name: Evelina Bakhturina, name: Jane Polak Scowcroft, name: John Kamalu, name: Dan Su, name: Kezhi Kong, name: Markus Kliegl, name: Rabeeh Karimi, name: Ying Lin, name: Sanjeev Satheesh, name: Jupinder Parmar, name: Pritam Gundecha, name: Brandon Norick, name: Joseph Jennings, name: Shrimai Prabhumoye, name: Syeda Nahida Akter, name: Mostofa Patwary, name: Abhinav Khattar, name: Deepak Narayanan, name: Roger Waleffe, name: Jimmy Zhang, name: Bor-Yiing Su, name: Guyue Huang, name: Terry Kong, name: Parth Chadha, name: Sahil Jain, name: Christine Harvey, name: Elad Segal, name: Jining Huang, name: Sergey Kashirsky, name: Robert McQueen, name: Izzy Putterman, name: George Lam, name: Arun Venkatesan, name: Sherry Wu, name: Vinh Nguyen, name: Manoj Kilaru, name: Andrew Wang, name: Anna Warno, name: Abhilash Somasamudramath, name: Sandip Bhaskar, name: Maka Dong, name: Nave Assaf, name: Shahar Mor, name: Omer Ullman Argov, name: Scot Junkin, name: Oleksandr Romanenko, name: Pedro Larroy, name: Monika Katariya, name: Marco Rovinelli, name: Viji Balas, name: Nicholas Edelman, name: Anahita Bhiwandiwalla, name: Muthu Subramaniam, name: Smita Ithape, name: Karthik Ramamoorthy, name: Yuting Wu, name: Suguna Varshini Velury, name: Omri Almog, name: Joyjit Daw, name: Denys Fridman, name: Erick Galinkin, name: Michael Evans, name: Katherine Luna, name: Leon Derczynski, name: Nikki Pope, name: Eileen Long, name: Seth Schneider, name: Guillermo Siman, name: Tomasz Grzegorzek, name: Pablo Ribalta, name: Monika Katariya, name: Joey Conway, name: Trisha Saar, name: Ann Guan, name: Krzysztof Pawelec, name: Shyamala Prayaga, name: Oleksii Kuchaiev, name: Boris Ginsburg, name: Oluwatobi Olabiyi, name: Kari Briski, name: Jonathan Cohen, name: Bryan Catanzaro, name: Jonah Alben, name: Yonatan Geifman, name: Eric Chung

We introduce the Llama-Nemotron series of models, an open family of
heterogeneous reasoning models that deliver exceptional reasoning capabilities,
inference efficiency, and an open license for enterprise use. The family comes
in three sizes -- Nano (8B), Super (49B), and Ultra (253B) -- and performs
competitively with state-of-the-art reasoning models such as DeepSeek-R1 while
offering superior inference throughput and memory efficiency. In this report,
we discuss the training procedure for these models, which entails using neural
architecture search from Llama 3 models for accelerated inference, knowledge
distillation, and continued pretraining, followed by a reasoning-focused
post-training stage consisting of two main parts: supervised fine-tuning and
large scale reinforcement learning. Llama-Nemotron models are the first
open-source models to support a dynamic reasoning toggle, allowing users to
switch between standard chat and reasoning modes during inference. To further
support open research and facilitate model development, we provide the
following resources: 1. We release the Llama-Nemotron reasoning models --
LN-Nano, LN-Super, and LN-Ultra -- under the commercially permissive NVIDIA
Open Model License Agreement. 2. We release the complete post-training dataset:
Llama-Nemotron-Post-Training-Dataset. 3. We also release our training
codebases: NeMo, NeMo-Aligner, and Megatron-LM.