most citedNVIDIA Nemotron 3: Efficient and Open Intelligence

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CL20251 cited

NVIDIA Nemotron 3: Efficient and Open Intelligence

NVIDIA, :, Aaron Blakeman +356

We introduce the Nemotron 3 family of models - Nano, Super, and Ultra. These models deliver strong agentic, reasoning, and conversational capabilities. The Nemotron 3 family uses a…

cs.CL2025

Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aaron Blakeman +311

We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. Nemotron 3 Nano was pretrained on 25 trillion text tokens, including more than 3 t…

cs.LG2025

NVIDIA Nemotron Nano V2 VL

NVIDIA, :, Amala Sanjay Deshmukh +121

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 reaso…

cs.CL2025

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model

NVIDIA, :, Aarti Basant +214

We introduce Nemotron-Nano-9B-v2, a hybrid Mamba-Transformer language model designed to increase throughput for reasoning workloads while achieving state-of-the-art accuracy compar…

cs.CL2025

CultureGuard: Towards Culturally-Aware Dataset and Guard Model for Multilingual Safety Applications

Raviraj Joshi, Rakesh Paul, Kanishk Singla +8

The increasing use of Large Language Models (LLMs) in agentic applications highlights the need for robust safety guard models. While content safety in English is well-studied, non-…

cs.CL2025

Llama-Nemotron: Efficient Reasoning Models

Akhiad Bercovich, Itay Levy, Izik Golan +132

We introduce the Llama-Nemotron series of models, an open family of heterogeneous reasoning models that deliver exceptional reasoning capabilities, inference efficiency, and an ope…