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NVIDIA NeMo Framework User Guide

NVIDIA NeMo Framework User Guide

Table of Contents

NeMo Framework

Overview
Install NeMo Framework
Performance
Why NeMo Framework?

Releases

Software Component Versions
Changelog
Known Issues

Getting Started

Quickstart with NeMo-Run
Quickstart with NeMo 2.0 API
Tutorials

Developer Guides

Migration Guide
Feature Guide
Best Practices
Performance Tuning Guide

Training and Customization

Long Context Training
- Context Parallelism
Optimal Configuration with Auto Configurator
Parameter-Efficient Fine-tuning (PEFT)
- Supported PEFT Methods
- A Comparison of Performant and Canonical LoRA Variants
Sequence Packing
Resiliency
Continual Training
Custom Datasets
- Pre-Training Data Module
- Fine-Tuning Data Module

Model Optimization

Quantization
Pruning
Distillation
Speculative Decoding

Models

Large Language Models
- Baichuan 2
- ChatGLM 3
- DeepSeek V2
- DeepSeek V3
- Gemma
- Gemma 2
- GPT-OSS
- Hyena
- Llama 3
- Llama Nemotron
- Mamba 2
- Mixtral
- Nemotron
- Phi 3
- Qwen2/2.5
- Qwen3
- Starcoder
- Starcoder 2
- T5
- BERT
Vision Language Models
Speech AI Models
Diffusion Models
- Flux
- Diffusion Training Framework
Embedding Models
Reranker Models
- Llama Reranker

Library Documentation

Overview
NeMo
NeMo AutoModel
NeMo Curator
NeMo Eval
NeMo Export and Deploy
NeMo Megatron Bridge
NeMo RL
NeMo Run

Performance

Performance#

You can find the performance summary for NeMo 25.09 container here.

Performance Numbers for Previous NeMo Container Releases#

Performance Summary Archive

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Performance Numbers for Previous NeMo Container Releases

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Last updated on Dec 15, 2025.