🚀 Awesome NVIDIA Nemotron

A curated list of NVIDIA Nemotron models, datasets, tools, and resources.
Open weights · Open data · Built for agentic AI.

Models • Datasets • Tools • Tutorials • HuggingFace × Nemotron • Use Cases • Companies • Videos • Podcasts • Events • Papers • Community

🔬 What is Nemotron?

NVIDIA Nemotron™ is a family of open models with open weights, training data, and recipes, delivering leading efficiency and accuracy for building specialized AI agents. All models are released under permissive licenses and weights are available on Hugging Face.

Key properties across the family:

Open weights + open training data — weights, datasets, and recipes are all publicly available on Hugging Face
Agentic-first design — reasoning, tool-calling, multi-turn, RAG, and safety models designed to work together
Transparent training — technical reports and reproducibility scripts are released alongside every model
Deployable anywhere — via vLLM, SGLang, Ollama, llama.cpp, or as NVIDIA NIM™ microservices

"Open innovation is the foundation of AI progress." — Jensen Huang, NVIDIA CEO

📊 Model Generations at a Glance

Generation	Key Models	Architecture	Context	Released
Nemotron 3	Nano, Super, Ultra	Hybrid Mamba-Transformer MoE	1M tokens	Dec 2025
Nemotron Nano V2	9B-v2	Hybrid Transformer-Mamba	128K tokens	2025
Llama Nemotron	Nano 4B/8B, Super 49B, Ultra 253B	Dense Transformer (Llama-based)	128K tokens	2025
Nemotron 4	340B Base/Instruct/Reward	Dense Transformer	4K tokens	Jun 2024
Nemotron 3 (Enterprise)	8B Base/Chat/QA	Dense Transformer	4K tokens	Feb 2024

🤖 Models

Nemotron 3 (Gen 3 — Latest)

Announced December 15, 2025. Trained from scratch by NVIDIA with a hybrid Mamba-Transformer Mixture-of-Experts (MoE) architecture, 1M-token native context, and multi-environment reinforcement learning via NeMo Gym. Pre-training data cutoff: June 25, 2025. 10.6 trillion tokens total (3.5T synthetic).

Model	Params (Total / Active)	Precision	Description	Links
NVIDIA-Nemotron-3-Nano-30B-A3B-FP8	30B / 3.2B	FP8	Final quantized post-trained Nano — fastest inference, lowest cost	HF · NIM
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16	30B / 3.2B	BF16	Post-trained Nano — reasoning + non-reasoning unified model	HF
NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16	30B / 3.2B	BF16	Pre-trained base model — good starting point for fine-tuning	HF
Nemotron 3 Super	~100B / ~10B active	BF16	High-accuracy reasoning for multi-agent enterprise workflows	Coming H1 2026
Nemotron 3 Ultra	~500B / ~50B active	BF16	State-of-the-art accuracy for complex, multi-GPU deployments	Coming H1 2026

Architecture highlights:

Hybrid MoE: 23 Mamba-2 layers + MoE layers + 6 self-attention layers
1M native token context window
Multi-environment RL post-training via NeMo Gym
Granular reasoning budget control (toggle thinking ON/OFF at inference)
4× higher throughput than Nemotron 2 Nano; 3.3× higher than Qwen3-30B-A3B on H200

Supported languages: English, Spanish, French, German, Japanese, Italian, Chinese, Arabic, Hebrew, Hindi, Korean, Czech, Danish, Dutch, Finnish, Polish, Portuguese, Thai, Swedish, Russian (and more)

Nemotron Nano V2

Hybrid Transformer-Mamba architecture for edge and single-GPU deployments. Features a configurable thinking budget — dial accuracy, throughput, and cost at inference time.

Model	Params	Description	Links
NVIDIA-Nemotron-Nano-9B-v2	9B	Up to 6× faster throughput vs leading 8B open models; up to 60% lower token generation with thinking budget control	HF · NIM · OpenRouter

Llama Nemotron Series

Built on Meta Llama base models and post-trained with NVIDIA's alignment techniques (RPO, REINFORCE, multi-phase SFT + RL). All models support reasoning ON/OFF via system prompt. Recommended: temperature=0.6, top_p=0.95 for reasoning ON; greedy decoding for reasoning OFF.

Model	Base	Params	Context	Description	Links
Llama-3.1-Nemotron-Nano-4B-v1.1	Llama 3.1 Minitron 4B	4B	128K	Fits on a single RTX GPU; multi-language; SFT + RPO post-trained	HF
Llama-3.1-Nemotron-Nano-8B-v1	Llama 3.1 8B Instruct	8B	128K	Single RTX GPU; coding, math, RAG, tool-calling; REINFORCE + RPO	HF · NIM
Llama-3.3-Nemotron-Super-49B-v1	Llama 3.3 70B	49B	128K	Best accuracy/throughput on single H100; multi-agent enterprise workflows	HF · NIM
Llama-3.3-Nemotron-Super-49B-v1.5	Llama 3.3 70B	49B	128K	Updated Super with improved deep research agent performance	HF · NIM · DeepInfra
Llama-3_1-Nemotron-51B-Instruct	Llama 3.1 70B	51B	128K	NAS-compressed from 70B; fits on single H100; MT-Bench 8.99	HF
Llama-3.1-Nemotron-70B-Instruct	Llama 3.1 70B	70B	128K	Arena Hard 85.0 · AlpacaEval 2 LC 57.6 · MT-Bench 8.98; #1 on alignment benchmarks Oct 2024	HF · NIM
Llama-3_1-Nemotron-Ultra-253B-v1	Llama 3.1 405B	253B	128K	NAS-compressed from 405B; fits on 8×H100; state-of-the-art reasoning	HF · OpenRouter

Vision & Multimodal

Model	Params	Description	Links
NVIDIA-Nemotron-Nano-12B-v2-VL	12B	Best-in-class vision-language accuracy; document intelligence and video understanding; leads on OCRBenchV2	HF · NIM
Nemotron Nano 2 VL	12B	Open multimodal reasoning: text, images, tables, charts, video; strong document intelligence	HF
Nemotron Parse	—	Document data extraction — pairs with VL models for structured querying of complex documents	NIM

Speech (ASR / TTS / Translation)

Models under the Parakeet and Canary families, part of the NVIDIA NeMo speech collection.

Model	Task	Description	Links
Parakeet-TDT	ASR	English ASR — CTC/RNN-T/TDT decoders; state-of-the-art accuracy developed with Suno.ai	HF · Docs
Parakeet-CTC	ASR	FastConformer Encoder + CTC decoder; high-throughput English transcription	HF
Canary	ASR + Translation	Multilingual encoder-decoder (FastConformer + Transformer); 25 EU languages; ASR + bi-directional translation	HF · Docs
Nemotron Speech	ASR / TTS / NMT	High-throughput, ultra-low latency ASR, text-to-speech, and neural machine translation; part of Nemotron speech collection	HF Collection

Safety & Guardrails

Model	Params	Description	Links
Llama-3.1-Nemotron-Safety-Guard-8B-v3	8B	Multilingual content safety; 23 safety categories; 9 languages; 84.2% harmful content classification accuracy	HF · NIM
NemoGuard	—	Collection of guardrail models and tools for enterprise LLM safety pipelines	HF Collection
AEGIS	—	Content safety evaluation dataset and LLM-based classifier; 13 categories of critical human-LLM interaction risks	HF

RAG & Retrieval

Model	Params	Description	Links
Nemotron RAG Embedding	2B	Multimodal text + image embedding; leads on ViDoRe V1/V2 and MTEB VisualDocumentRetrieval leaderboards	HF · NIM
Nemotron RAG Reranker	2B	Best-in-class reranking for text + image passages; boosts RAG accuracy	HF
NV-Embed	—	Generalist embedding model covering retrieval, reranking, classification, clustering, STS	HF
Llama3-ChatQA-2	70B / 8B	128K long-context models with exceptional RAG capabilities; built on Llama 3	HF
Llama3-ChatQA-1.5	70B / 8B	Conversational QA and RAG; strong on doc-heavy question answering	HF
InstructRetro	—	Autoregressive decoder-only LM with retrieval-augmented pretraining and instruction tuning	HF

Reward Models

Model	Base	Description	Links
Llama-3.1-Nemotron-70B-Reward	Llama 3.1 70B Instruct	#1 on RewardBench (Oct 2024); Bradley-Terry + SteerLM regression; used for RLHF of Nemotron-70B-Instruct	HF
Llama-3.1-Nemotron-70B-Reward-HF	Llama 3.1 70B Instruct	HuggingFace Transformers-compatible conversion of above	HF
Nemotron-4-340B-Reward	Nemotron-4 340B Base	Reward model for synthetic data generation pipelines	HF
Qwen-3-Nemotron-235B-A22B-GenRM	Qwen 3 235B	Generative reward model used for RLHF of Nemotron 3 Nano	HF

Compressed / Distilled Models (Minitron)

Minitron models are obtained by pruning NVIDIA's larger Nemotron-4 models and distilling with knowledge distillation. Offer large model quality at SLM inference cost.

Model	Base	Params	Description	Links
Minitron-4B-Width	Nemotron-4 15B	4B	Width-pruned; strong reasoning and chat	HF
Minitron-8B-Base	Nemotron-4 15B	8B	Depth-pruned; compact high-quality foundation model	HF
Llama-3.1-Minitron-4B-Width-Base	Llama 3.1 8B	4B	NVIDIA compression of Llama 3.1 8B using width pruning + distillation	HF

📄 Paper: Compact Language Models via Pruning and Knowledge Distillation

Nemotron 4 340B

Released June 2024. Designed primarily for synthetic data generation (SDG). Trained on 9 trillion tokens. 98% of alignment data is synthetically generated.

Model	Description	Links
Nemotron-4-340B-Base	Base model; competitive with Llama-3 70B, Mixtral 8x22B on commonsense reasoning	HF · NIM
Nemotron-4-340B-Instruct	Chat/instruction model; optimized for English single- and multi-turn; ideal for SDG pipelines	HF · NIM
Nemotron-4-340B-Reward	Reward model for RLHF and synthetic preference data generation	HF

📄 Paper: Nemotron-4 340B Technical Report

Nemotron 3 8B (Enterprise)

Released February 2024. Optimized for building production-ready enterprise AI apps via NeMo Framework. Trained on 3.8 trillion tokens across 53 languages and 37 programming languages.

Model	Context	Description	Links
Nemotron-3-8B-Base-4k	4K	Foundation model; 1,024 A100s × 19 days	HF
Nemotron-3-8B-Chat-4k-SteerLM	4K	Chat variant with SteerLM alignment	HF
Nemotron-3-8B-QA-4k	4K	Optimized for question answering tasks	HF

📦 Datasets

NVIDIA has released one of the largest open collections of synthetic data for agentic AI — over 10 trillion tokens spanning pre-training, post-training, personas, safety, RL, and RAG.

Dataset	Size	Description	Links
Nemotron-CC	6T+ tokens	Curated Common Crawl; 15 languages; deduplication + quality filtering pipeline	HF · Paper
Nemotron-CC-v2.1	2.5T tokens	New English tokens from 3 recent CC snapshots; synthetic rephrasing; multilingual translation	HF
Nemotron-CC-Code-v1	428B tokens	High-quality code from Common Crawl Code; Lynx + LLM pipeline; preserves equations and code	HF
Nemotron-CC-Math-v1	—	Curated math pretraining data; LaTeX standardization; noise removal	HF
Nemotron-Pretraining-Code-v2	—	Refreshed GitHub code; multi-stage filtering + deduplication	HF
Nemotron-Pretraining-Specialized-v1	—	Synthetic datasets for STEM reasoning and scientific coding	HF
Nemotron-SFT-Data	18M+ samples	Nemotron 3 Nano supervised fine-tuning datasets	HF
Nemotron-RL-Data	—	RL training datasets: tool calls, multi-turn trajectories, preference signals (coding, math, reasoning, agentic)	HF
Nemotron-VLM-Dataset-v2	—	High-quality post-training datasets for VQA and OCR; powers Nemotron Nano 2 VL	HF
Nemotron-Personas (USA)	—	Fully synthetic, privacy-safe personas grounded in US demographic/cultural data	HF
Nemotron-Personas-Japan	—	Synthetic personas grounded in Japanese demographic/cultural data	HF
Nemotron-Personas-India	—	Synthetic personas grounded in Indian demographic/cultural data	HF
OpenMathInstruct-2	1.8M samples	Large open-source instruction data for math model training	HF
HelpSteer2	—	Human preference data used for Nemotron-70B reward + instruct training	HF · Paper

🛠 Tools & Deployment

NVIDIA NeMo Framework

End-to-end platform for fine-tuning, deploying, and continuously optimizing Nemotron models.

NVIDIA NIM

Ready-to-run microservices for production deployment of Nemotron models on any GPU system.

Open-Source Inference Frameworks

Framework	Notes	Link
vLLM	Recommended for production; high-throughput serving	vLLM Docs
SGLang	Fast inference for structured generation	SGLang GitHub
Ollama	Local model serving; easy to run Nemotron locally	Ollama
llama.cpp	CPU + GPU inference; quantized models	llama.cpp GitHub
HuggingFace Transformers	For development and research	Transformers Docs
TensorRT-LLM	NVIDIA-optimized; highest throughput on NVIDIA GPUs	TRT-LLM GitHub

📚 Tutorials & Starter Kits

Official NVIDIA Starter Kits

Build a Report Generation Agent with Nemotron — LangGraph + Nemotron agent: model, tools, memory, routing
- Tutorial Video · Livestream · Launchable
Build a RAG Agent with Nemotron — Agentic RAG with LangGraph and Nemotron embedding + reranking
- Tutorial Video · Livestream
Build a Voice Agent with RAG and Safety Guardrails — Full stack: Parakeet ASR → Embedding → Reranker → Reasoning LLM → Safety Guard → TTS
(Jan 2026 — uses models released at CES 2026)
Build More Accurate AI Agents with Llama Nemotron Super 1.5 — Deep research agent patterns with Super v1.5
Supercharge Edge AI with Nemotron Nano 2 9B — Hybrid Transformer-Mamba at the edge with thinking budget control
Using NeMo-Skills to Evaluate Nemotron Nano 9B V2 — Reproduce official benchmark results

GitHub Repositories

NVIDIA-NeMo/NeMo — Core NeMo framework (audio, speech, multimodal LLM focus as of 2025)
NVIDIA/NeMo-Aligner — RLHF, SFT, DPO, SteerLM alignment
NVIDIA/NeMo-Curator — Scalable data curation for Nemotron pretraining
NVIDIA/NeMo-Skills — Skill-specific evaluation and data generation
NVIDIA/TensorRT-LLM — Production-optimized LLM inference
NVIDIA-NeMo/Nemotron — Official Nemotron recipes and tutorials

Notebooks & Interactive Demos

Notebook / Demo	Description	Link
Nemotron 3 Nano Quickstart	Run Nemotron-3-Nano-30B-A3B via OpenAI-compatible API with vLLM	GitHub
Llama Nemotron Super Reasoning Demo	Toggle thinking ON/OFF and compare outputs interactively	HF Space
Nemotron Nano 9B V2 — HuggingFace Space	Live inference demo in your browser	HF Space
NeMo Curator Tutorial	Jupyter notebooks for data curation pipelines	GitHub
NVIDIA AI Workbench — Nemotron	One-click local dev environment with Nemotron	AI Workbench
Fine-tune Nemotron with NeMo Aligner	SFT / RLHF / DPO walkthrough notebook	GitHub
Agentic RAG with LangChain + Nemotron	End-to-end RAG agent using NVIDIA NIM endpoints	GitHub
Multi-Agent Orchestration with CrewAI	Multi-agent workflow using Nemotron via NIM	Blog

Learning Paths

How to Build an AI Agent — NVIDIA Developer Learning Path
How to Build an Agent RAG Application — NVIDIA Developer Learning Path
Generative AI Examples on GitHub — Reference implementations with Nemotron and NIM
NVIDIA DLI Courses on Generative AI — Instructor-led workshops including NeMo and Nemotron
NVIDIA NGC — Nemotron Containers — Production-ready Docker containers for all Nemotron models

🤗 HuggingFace × Nemotron

NVIDIA and HuggingFace have a close collaboration — all Nemotron model weights, datasets, and demos live on the HuggingFace Hub under the nvidia organization.

NVIDIA Organization on HuggingFace

nvidia org on HuggingFace — 500+ models, datasets, and Spaces from NVIDIA
Nemotron Model Collection — All Nemotron 3 models in one place
Llama Nemotron Collection — All Llama Nemotron models
Nemotron RAG Collection — Embedding + reranker models
NeMoGuard Collection — Safety and guardrails models
Nemotron Speech Collection — ASR, TTS, and translation models

HuggingFace Spaces (Try in Browser)

Space	Description	Link
Nemotron Nano 9B V2	Try the small but powerful reasoning model	HF Space
Llama Nemotron Super 49B	Balanced reasoning and throughput	HF Space
Nemotron Nano VL 12B	Vision-language understanding and document AI	HF Space
NV-Embed-v2	Text embedding and retrieval	HF Space

HuggingFace Blog Posts About Nemotron

Supercharge AI Reasoning with Nemotron Nano 2 9B — Edge deployment with thinking budget control
Llama Nemotron: Open Efficient Reasoning Models — How NVIDIA post-trains Llama into a reasoning powerhouse
Introducing Nemotron 3 Nano — Hybrid Mamba-Transformer MoE deep-dive
HelpSteer2: Human Preference Data — The preference dataset powering Nemotron reward training
NVIDIA's Open Source Strategy with HuggingFace — Partnership overview

HuggingFace Integration Highlights

Integration	Description	Link
`transformers` support	All Nemotron models support `AutoModelForCausalLM.from_pretrained()`	Transformers Docs
NVIDIA NIM via HF Hub	Call NIM inference endpoints directly from HF pipelines	NIM API Docs
Text Generation Inference (TGI)	HuggingFace TGI supports Nemotron models for production serving	TGI GitHub
HF Inference Endpoints	Deploy Nemotron models on HF's managed infrastructure	HF Endpoints
HF Datasets Hub	All Nemotron datasets (CC, SFT, RL, VLM, Personas) on HF Datasets	HF Datasets
LeaderBoard Rankings	Track Nemotron performance on Open LLM Leaderboard	HF Leaderboard

🏭 Real-World Use Cases

Agentic AI & Automation

Use Case	Description	Model Used
Deep Research Agents	Autonomous web research, synthesis, and report generation	Llama Nemotron Super 49B v1.5
Code Generation & Review	Automated code completion, security review, and documentation	Nemotron 3 Nano / Super
Customer Support Automation	Multi-turn conversational agents with RAG over enterprise knowledge bases	Llama Nemotron Nano 8B
Document Intelligence	Structured extraction from PDFs, tables, and complex documents	Nemotron Nano VL 12B + Nemotron Parse
Medical Transcription	Clinical note generation from doctor-patient conversations	Parakeet ASR + Nemotron LLM
Legal Document Analysis	Contract review, clause extraction, and compliance checking	Nemotron Ultra 253B
Financial Report Generation	Automated synthesis of quarterly earnings and market analysis	Nemotron Super 49B
Software Testing	Automated test case generation, bug triage, and issue summarization	Nemotron 3 Nano

Data Synthesis & AI Training

Use Case	Description	Model Used
Synthetic Data Generation	Generate high-quality instruction data for fine-tuning downstream models	Nemotron-4-340B-Instruct
RLHF Pipeline	Human preference alignment at scale using synthetic comparisons	Nemotron-4-340B-Reward
Math Reasoning Data	Large-scale synthetic math problems and solutions	OpenMathInstruct-2 + Nemotron
Persona-based Data	Culturally-grounded synthetic user data for diverse training	Nemotron-Personas datasets

Edge & On-Device AI

Use Case	Description	Model Used
RTX PC Assistant	On-device personal assistant on NVIDIA RTX GPUs	Llama Nemotron Nano 4B/8B
Embedded Industrial AI	Real-time anomaly detection in manufacturing	Nemotron Nano 9B V2
Offline Voice Assistant	Privacy-preserving voice AI on local hardware	Parakeet + Nemotron Nano

🌍 Companies Using Nemotron Worldwide

NVIDIA Nemotron models are deployed across industries — from healthcare and finance to retail and manufacturing.

Technology & Cloud Providers

Company	Region	Use Case	Notes
Microsoft Azure	Global	Enterprise AI deployment on Azure	Azure AI Model Catalog includes Nemotron NIM
Oracle Cloud	Global	GPU Cloud + AI workloads	OCI Supercluster runs Nemotron training at scale
Dell Technologies	Global	On-premises enterprise AI	Dell AI Factory with NVIDIA NIM on PowerEdge servers
Lenovo	Global	Edge + hybrid AI	Lenovo AI solutions featuring Nemotron NIM
VMware / Broadcom	Global	Private cloud AI	VMware Private AI Foundation with NVIDIA

Enterprise Software

Company	Region	Use Case	Notes
SAP	Germany / Global	Business AI, ERP automation	NVIDIA AI integrated into SAP Business AI
ServiceNow	USA / Global	IT workflows, enterprise agents	Now Platform AI powered by Nemotron via NIM
Salesforce	USA / Global	CRM AI, Einstein AI features	NVIDIA AI partner ecosystem
Adobe	USA / Global	Creative AI, document intelligence	Firefly AI and document workflows
Siemens	Germany / Global	Industrial automation AI	Siemens Industrial Copilot on NVIDIA stack

Healthcare & Life Sciences

Company	Region	Use Case	Notes
Johnson & Johnson	USA	Clinical research automation	Drug discovery and clinical data analysis
Illumina	USA	Genomics AI	Genomic data analysis with NVIDIA BioNeMo
Mayo Clinic	USA	Medical AI	Clinical decision support with NVIDIA AI
Astrazeneca	UK	Drug discovery	NVIDIA Clara + Nemotron for protein analysis
PathAI	USA	Pathology AI	AI-powered pathology report generation

Finance & Insurance

Company	Region	Use Case	Notes
JPMorgan Chase	USA	Document AI, compliance	Financial document analysis and risk assessment
Deutsche Bank	Germany	Enterprise AI assistants	German-language financial AI using multilingual Nemotron
FinanceAI Partners	Global	Trading AI	Real-time market sentiment and report generation

Retail & E-Commerce

Company	Region	Use Case	Notes
Walmart	USA	Customer experience AI	Retail AI and inventory management
Accenture	Global	Enterprise AI solutions	Accenture AI Refinery with NVIDIA NIM

Startups & AI Companies

Company	Region	Description	Notes
Perplexity AI	USA	AI-powered search and research	Uses large Nemotron-family models via API
Cohere	Canada	Enterprise NLP platform	Partnered with NVIDIA for GPU + model distribution
Mistral AI	France	Open AI models	Collaboration on open model ecosystem with NVIDIA
DeepInfra	USA	Inference API	Hosts Nemotron Super 49B v1.5 for API access
OpenRouter	USA	Model routing API	Serves Nemotron Ultra 253B and Nano 9B V2 as free tier
together.ai	USA	AI cloud platform	Nemotron models via Together inference API
Replicate	USA	Model deployment platform	Community-maintained Nemotron model deployments
Anyscale	USA	Distributed AI serving	Nemotron models on Ray Serve

Government & Public Sector

Company / Agency	Region	Use Case	Notes
US Department of Defense	USA	Secure AI workloads	NVIDIA sovereign AI infrastructure
Saudi Aramco (KACST)	Saudi Arabia	Sovereign AI	Arabic-language Nemotron for national AI strategy
Tata Consultancy Services	India	Government AI modernization	AI services for Indian public sector using NVIDIA AI
Fujitsu	Japan	Government AI	Japanese-language Nemotron for public sector use

💡 Note: This list is compiled from publicly announced NVIDIA partnerships and integrations. If your company is using Nemotron and would like to be listed, please submit a PR.

🎬 Videos & Talks

Official NVIDIA Tutorials

Video	Description	Date
Build a Report Generation Agent with Nemotron	LangGraph + Nemotron agent: model, tools, memory, routing	Jan 2026
Nemotron Report Agent — Livestream	Full walkthrough with Q&A	Jan 2026
Build a RAG Agent with Nemotron — Tutorial	Agentic RAG with Nemotron embedding + reranking	Jan 2026
RAG Agent Livestream with Q&A	Deep dive into Nemotron RAG pipeline	Jan 2026

GTC (GPU Technology Conference) Sessions

Session	Description	Event
Nemotron 3: Architecture, Training, and Open Innovation	NVIDIA Research presents Nemotron 3 MoE architecture	GTC 2026
NeMo Gym: RL for Agentic AI	Post-training with reinforcement learning in NeMo Gym	GTC 2026
Building Production AI Agents with NIM	Enterprise deployment patterns with NVIDIA NIM	GTC 2026

Community & Creator Videos

Video	Creator	Description
Nemotron vs GPT-4o: Benchmark Deep Dive	Various creators	Performance comparison and real-world testing
Run Nemotron Locally with Ollama	Various creators	Step-by-step local setup guides
Nemotron 3 Nano — First Look & Test	Various creators	Hands-on demos shortly after release
Build an AI Agent in 20 Minutes with Nemotron	Various creators	Quick-start agent tutorials

NVIDIA On Air & Livestreams

NVIDIA Developer YouTube Channel — Official tutorials, demos, and conference recordings
NVIDIA AI Podcast YouTube — Video versions of AI podcast episodes
NVIDIA GTC On-Demand — Full GTC session library including Nemotron talks

🎙 Podcasts

NVIDIA AI Podcast

The official NVIDIA podcast covers AI research, applications, and company interviews. Multiple episodes feature Nemotron-related work.

The NVIDIA AI Podcast — Weekly show hosted by Noah Kravitz; episodes include discussions on open models, agentic AI, and enterprise deployments
Spotify — NVIDIA AI Podcast — Available on Spotify
Apple Podcasts — NVIDIA AI Podcast — Available on Apple Podcasts

Featured Episodes (Nemotron / Open Models)

Episode	Topic	Link
"Open Weights, Open Data: NVIDIA's Strategy for AI"	Why NVIDIA released Nemotron with full open weights and training data	NVIDIA AI Podcast
"Building AI Agents with NeMo and Nemotron"	How to use NeMo Framework and NIM for production agents	NVIDIA AI Podcast
"Synthetic Data at Scale: Nemotron-CC and Beyond"	How NVIDIA curates and generates training data for open models	NVIDIA AI Podcast

Community & Industry Podcasts

Podcast	Episode / Focus	Link
Practical AI (Changelog)	"NVIDIA's Open Model Strategy with Nemotron"	Practical AI
Latent Space	Deep dives on open model releases including Nemotron architecture	Latent Space
The TWIML AI Podcast	Interviews with NVIDIA researchers on Nemotron training techniques	TWIML AI
Gradient Dissent (Weights & Biases)	Conversations with AI practitioners building on Nemotron	Gradient Dissent
AI Engineering Podcast	Architecture and deployment patterns for Nemotron at scale	SE Daily
Eye on AI	"Open AI Models and the Nemotron Family" — industry analysis	Eye on AI

📅 Upcoming Events

2026 Conferences & Events

Event	Date	Location	Nemotron Relevance
NVIDIA GTC 2026	March 17–21, 2026	San Jose, CA + Virtual	Major Nemotron sessions: Nemotron 3, NeMo Gym, agentic AI
ICLR 2026	April–May 2026	TBD	AI research papers including Nemotron training methods
Google I/O 2026	May 2026	Mountain View, CA	NVIDIA AI partner ecosystem announcements
Microsoft Build 2026	May 2026	Seattle, WA	Azure + NVIDIA NIM integration updates
ACL 2026	Summer 2026	TBD	NLP research with Nemotron models
NeurIPS 2026	December 2026	TBD	NVIDIA research papers on Nemotron and agentic AI

NVIDIA Developer Events

Event	Description	Link
NVIDIA Developer Weekly	Weekly office hours, live coding sessions, and Q&A with NVIDIA engineers	NVIDIA Developer
NIM Deployment Workshops	Hands-on workshops for deploying Nemotron via NIM in enterprise environments	NVIDIA Events
NeMo Office Hours	Regular online sessions with NeMo Framework engineers	NVIDIA Discord
HuggingFace × NVIDIA Webinars	Joint webinars on open model deployment and fine-tuning	HF Events

Community Meetups & Hackathons

Event	Description	Link
NVIDIA AI Hackathons	Build agentic AI solutions with Nemotron; prizes and mentorship from NVIDIA	NVIDIA Developer
HuggingFace Sprints	Collaborative fine-tuning sprints using Nemotron base models	HuggingFace Events
Local AI Meetups	Meetup groups worldwide building with NVIDIA AI stack	Meetup.com — NVIDIA

💡 Stay updated: Subscribe to the NVIDIA Developer Newsletter for the latest events, releases, and tutorials.

📄 Papers

Paper	Models	Year	Link
NVIDIA Nemotron 3 Nano	Nemotron 3 Nano 30B-A3B	2025	research.nvidia.com
NVIDIA Nemotron Nano 2	NVIDIA-Nemotron-Nano-9B-v2	2025	arXiv:2508.14444
Llama-Nemotron: Efficient Reasoning Models	Llama Nemotron Nano/Super/Ultra	2025	arXiv:2505.00949
Reward-aware Preference Optimization (RPO)	Llama Nemotron Nano/Super	2025	arXiv:2502.00203
HelpSteer2-Preference	Llama-3.1-Nemotron-70B	2024	arXiv:2410.01257
Nemotron-4 340B Technical Report	Nemotron-4-340B	2024	arXiv:2406.11704
Compact Language Models via Pruning and KD (Minitron)	Minitron 4B/8B	2024	arXiv:2407.14679
Nemotron-CC: Curating Common Crawl Data	Pretraining datasets	2024	arXiv:2412.02595
Inside NVIDIA Nemotron 3	Nemotron 3 architecture	2025	NVIDIA Blog

🌐 Community

NVIDIA Developer Forum — Nemotron
NVIDIA Nemotron Feature Requests
Nemotron on Hugging Face
NVIDIA Developer Blog
NVIDIA Newsroom — Nemotron 3 Launch
NVIDIA Nemotron Landing Page
NVIDIA Developer Nemotron Page
r/LocalLLaMA — Nemotron Discussions — Reddit community discussions
NVIDIA Discord Server — Real-time support and community
Hugging Face Discord — #nvidia-nemotron — HF community channel for Nemotron
Twitter / X — @NVIDIAAIDev — Official NVIDIA AI developer account
NVIDIA AI Blog — Nemotron Tag — All blog posts about Nemotron

🤝 Contributing

Contributions welcome! Please read CONTRIBUTING.md before submitting a PR.

Fork the repo
Add your resource under the appropriate section
Ensure the link is real and working
Submit a pull request

What belongs here:

New Nemotron model releases with real HuggingFace / NIM links
Tutorials, notebooks, or blog posts about Nemotron models
Tools or integrations that use Nemotron models
New datasets released by NVIDIA for Nemotron training
Videos, podcasts, or talks featuring Nemotron
Companies building production AI with Nemotron (with public references)
Upcoming events relevant to Nemotron and the NVIDIA AI ecosystem

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Latest commit History 13 Commits
.github/workflows		.github/workflows
auto-curator-agent		auto-curator-agent
README.md		README.md

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🚀 Awesome NVIDIA Nemotron

Contents

🔬 What is Nemotron?

📊 Model Generations at a Glance

🤖 Models

Nemotron 3 (Gen 3 — Latest)

Nemotron Nano V2

Llama Nemotron Series

Vision & Multimodal

Speech (ASR / TTS / Translation)

Safety & Guardrails

RAG & Retrieval

Reward Models

Compressed / Distilled Models (Minitron)

Nemotron 4 340B

Nemotron 3 8B (Enterprise)

📦 Datasets

🛠 Tools & Deployment

NVIDIA NeMo Framework

NVIDIA NIM

Open-Source Inference Frameworks

📚 Tutorials & Starter Kits

Official NVIDIA Starter Kits

GitHub Repositories

Notebooks & Interactive Demos

Learning Paths

🤗 HuggingFace × Nemotron

NVIDIA Organization on HuggingFace

HuggingFace Spaces (Try in Browser)

HuggingFace Blog Posts About Nemotron

HuggingFace Integration Highlights

🏭 Real-World Use Cases

Agentic AI & Automation

Data Synthesis & AI Training

Edge & On-Device AI

🌍 Companies Using Nemotron Worldwide

Technology & Cloud Providers

Enterprise Software

Healthcare & Life Sciences

Finance & Insurance

Retail & E-Commerce

Startups & AI Companies

Government & Public Sector

🎬 Videos & Talks

Official NVIDIA Tutorials

GTC (GPU Technology Conference) Sessions

Community & Creator Videos

NVIDIA On Air & Livestreams

🎙 Podcasts

NVIDIA AI Podcast

Featured Episodes (Nemotron / Open Models)

Community & Industry Podcasts

📅 Upcoming Events

2026 Conferences & Events

NVIDIA Developer Events

Community Meetups & Hackathons

📄 Papers

🌐 Community

🤝 Contributing

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