NVIDIA Nemotron Nano V2 VL
NVIDIA Nemotron Nano V2 VL
November 6, 2025
著者: NVIDIA, Amala Sanjay Deshmukh, Kateryna Chumachenko, Tuomas Rintamaki, Matthieu Le, Tyler Poon, Danial Mohseni Taheri, Ilia Karmanov, Guilin Liu, Jarno Seppanen, Guo Chen, Karan Sapra, Zhiding Yu, Adi Renduchintala, Charles Wang, Peter Jin, Arushi Goel, Mike Ranzinger, Lukas Voegtle, Philipp Fischer, Timo Roman, Wei Ping, Boxin Wang, Zhuolin Yang, Nayeon Lee, Shaokun Zhang, Fuxiao Liu, Zhiqi Li, Di Zhang, Greg Heinrich, Hongxu, Yin, Song Han, Pavlo Molchanov, Parth Mannan, Yao Xu, Jane Polak Scowcroft, Tom Balough, Subhashree Radhakrishnan, Paris Zhang, Sean Cha, Ratnesh Kumar, Zaid Pervaiz Bhat, Jian Zhang, Darragh Hanley, Pritam Biswas, Jesse Oliver, Kevin Vasques, Roger Waleffe, Duncan Riach, Oluwatobi Olabiyi, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Pritam Gundecha, Khanh Nguyen, Alexandre Milesi, Eugene Khvedchenia, Ran Zilberstein, Ofri Masad, Natan Bagrov, Nave Assaf, Tomer Asida, Daniel Afrimi, Amit Zuker, Netanel Haber, Zhiyu Cheng, Jingyu, Xin, Di, Wu, Nik Spirin, Maryam Moosaei, Roman Ageev, Vanshil Atul Shah, Yuting Wu, Daniel Korzekwa, Unnikrishnan Kizhakkemadam Sreekumar, Wanli Jiang, Padmavathy Subramanian, Alejandra Rico, Sandip Bhaskar, Saeid Motiian, Kedi Wu, Annie Surla, Chia-Chih Chen, Hayden Wolff, Matthew Feinberg, Melissa Corpuz, Marek Wawrzos, Eileen Long, Aastha Jhunjhunwala, Paul Hendricks, Farzan Memarian, Benika Hall, Xin-Yu Wang, David Mosallanezhad, Soumye Singhal, Luis Vega, Katherine Cheung, Krzysztof Pawelec, Michael Evans, Katherine Luna, Jie Lou, Erick Galinkin, Akshay Hazare, Kaustubh Purandare, Ann Guan, Anna Warno, Chen Cui, Yoshi Suhara, Shibani Likhite, Seph Mard, Meredith Price, Laya Sleiman, Saori Kaji, Udi Karpas, Kari Briski, Joey Conway, Michael Lightstone, Jan Kautz, Mohammad Shoeybi, Mostofa Patwary, Jonathen Cohen, Oleksii Kuchaiev, Andrew Tao, Bryan Catanzaro
cs.AI
要旨
私たちは、実世界の文書理解・長尺動画理解・推論タスクに強みを持つNemotronビジョン言語シリーズの最新モデル「Nemotron Nano V2 VL」を紹介します。本モデルは、モデルアーキテクチャ・データセット・学習レシピの大幅な改良により、前身モデルであるLlama-3.1-Nemotron-Nano-VL-8Bを、あらゆる視覚・テキスト領域で凌駕する性能向上を実現しました。Nemotron Nano V2 VLは、ハイブリッドMamba-Transformer LLMであるNemotron Nano V2を基盤とし、革新的なトークン削減技術を組み合わせることで、長文書・長尺動画シナリオにおける高い推論スループットを達成しています。BF16、FP8、FP4形式のモデルチェックポイントを公開するとともに、データセットの大部分、学習レシピ、およびトレーニングコードを共有します。
English
We introduce Nemotron Nano V2 VL, the latest model of the Nemotron
vision-language series designed for strong real-world document understanding,
long video comprehension, and reasoning tasks. Nemotron Nano V2 VL delivers
significant improvements over our previous model,
Llama-3.1-Nemotron-Nano-VL-8B, across all vision and text domains through major
enhancements in model architecture, datasets, and training recipes. Nemotron
Nano V2 VL builds on Nemotron Nano V2, a hybrid Mamba-Transformer LLM, and
innovative token reduction techniques to achieve higher inference throughput in
long document and video scenarios. We are releasing model checkpoints in BF16,
FP8, and FP4 formats and sharing large parts of our datasets, recipes and
training code.