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NVIDIA Nemotron 3: Efficient and Open Intelligence research paper by NVIDIA, 2025

NVIDIA · Architectures · Dec 24, 2025 · 60 citations · 44 upvotes · unverified

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What it shows

Nemotron 3 is a family of efficient models using a hybrid Mamba-Transformer architecture for strong agentic and reasoning capabilities.

By NVIDIA, Aaron Blakeman, Aaron Grattafiori and 355 more · arXiv 2512.20856 · PDF

UnverifiedSummarised by a model from the abstract; not yet checked by hand.

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Topic
ArchitecturesJun 12, 2017Attention Is All You NeedIntroduced the Transformer, the attention-only architecture behind nearly every large language model since.Google201k citations142 upvotesRead →ArchitecturesDec 1, 2023Mamba: Linear-Time Sequence Modeling with Selective State SpacesA selective state space model that scales linearly with sequence length and matches Transformers on language.Carnegie Mellon University10.2k citations152 upvotesRead →ArchitecturesSep 2, 2021CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and GenerationCodeT5, a unified encoder-decoder Transformer model, improves code understanding and generation by leveraging semantic information from identifiers and user comments.Salesforce2,633 citations3 upvotesRead →ArchitecturesUnverifiedMar 14, 2025VGGT: Visual Geometry Grounded TransformerVGGT, a feed-forward neural network, efficiently infers multiple 3D attributes from single or multiple views, outperforming alternatives and enhancing downstream tasks without post-processing.Meta2,132 citations40 upvotesRead →ArchitecturesUnverifiedJan 11, 2024DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language ModelsThe DeepSeekMoE architecture improves expert specialization in Mixture-of-Experts models by segmenting experts and isolating shared ones, achieving better performance and computational efficiency compared to GShard and other models.DeepSeek1,268 citations65 upvotesRead →ArchitecturesMay 13, 2023CodeT5+: Open Code Large Language Models for Code Understanding and GenerationCodeT5+, a family of flexible encoder-decoder LLMs initialized with frozen LLMs and trained with a mixture of pretraining objectives, achieves state-of-the-art performance across various code-related tasks.Salesforce836 citations7 upvotesRead →
About this paper
Venue
arXiv.org
Citations
60, 1 influential · Semantic Scholar
Upvotes
44 · Hugging Face
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

CitationsNov 9, 2026Citations rose from 59 to 60.
CitationsNov 2, 2026Citations rose from 48 to 59.
New summaryOct 26, 2026Nemotron 3 is a family of efficient models using a hybrid Mamba-Transformer architecture for strong agentic and reasoning capabilities.
TopicOct 26, 2026Moved from Inference and efficiency to Architectures.
CitationsOct 12, 2026Citations rose from 47 to 48.
CitationsOct 5, 2026Influential citations rose from 0 to 1.
CitationsOct 5, 2026Citations rose from 39 to 47.
CitationsSep 28, 2026Citations rose from 38 to 39.
CitationsSep 25, 2026A first count of 0 influential citations.
CitationsSep 25, 2026A first count of 38 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.