NVIDIA Nemotron Nano V2 VL
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.
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NVIDIA
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Amala Sanjay Deshmukh
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Amala Sanjay Deshmukh
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Kateryna Chumachenko
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Kateryna Chumachenko
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Tuomas Rintamaki
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Matthieu Le
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Tyler Poon
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Danial Mohseni Taheri
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Ilia Karmanov
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Guilin Liu
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Jarno Seppanen
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Guo Chen
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Karan Sapra
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Zhiding Yu
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Adi Renduchintala
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Charles Wang
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Peter Jin
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Arushi Goel
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Mike Ranzinger
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Lukas Voegtle
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Philipp Fischer
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Timo Roman
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Wei Ping
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Boxin Wang
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Zhuolin Yang
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Zhuolin Yang
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Nayeon Lee
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Shaokun Zhang
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Fuxiao Liu
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Fuxiao Liu
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Zhiqi Li
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Di Zhang
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Di Zhang
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Greg Heinrich
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Hongxu
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Yin
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Song Han
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Pavlo Molchanov
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Pavlo Molchanov
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Parth Mannan
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Yao Xu
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Jane Polak Scowcroft
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Tom Balough
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Subhashree Radhakrishnan
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Paris Zhang
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Sean Cha
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Ratnesh Kumar
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Jesse Oliver
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Roger Waleffe
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Ameya Sunil Mahabaleshwarkar
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Bilal Kartal
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Pritam Gundecha
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Khanh Nguyen
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Alexandre Milesi
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Eugene Khvedchenia
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Padmavathy Subramanian
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Kedi Wu
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Annie Surla
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Chia-Chih Chen
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Hayden Wolff
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Matthew Feinberg
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Melissa Corpuz
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Eileen Long
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Farzan Memarian
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Benika Hall
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Xin-Yu Wang
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David Mosallanezhad
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Soumye Singhal
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Soumye Singhal
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Luis Vega
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Michael Evans
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Michael Evans
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Michael Lightstone
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Mostofa Patwary
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Jonathen Cohen
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Oleksii Kuchaiev
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Andrew Tao
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Bryan Catanzaro
NVIDIA Nemotron Nano V2 VL
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.
Nemotron Nano V2 VL, a hybrid Mamba-Transformer LLM, improves document and video understanding through enhanced architecture and token reduction techniques.
Mamba-Transformer token reduction techniques BF16 FP8 FP4