NVIDIA NeMo is a scalable, cloud-native framework that lets researchers and enterprises create custom generative-AI systems anywhere—from laptops to multi-GPU clusters.
Its core toolkit (built on PyTorch) provides:
- Model development: ready-made modules and checkpoints for LLMs, ASR, TTS, CV, and multimodal tasks.
- Large-scale training: tensor/pipeline parallelism, FSDP, mixed precision, FlashAttention, and other performance optimizations.
- Data curation & guardrailing: NeMo Curator for web-scale preprocessing and NeMo Guardrails for policy-driven safety.
- Deployment: optimized inference runtimes and NIM micro-services that integrate with Triton and the wider NVIDIA DGX stack.
Originally introduced in 2019 as a speech/NLP “Neural Modules” toolkit, NeMo has evolved into a full-stack platform capable of training trillion-parameter models such as Nemotron-4 and delivering production-grade generative-AI APIs.
