What Are NVIDIA NIM and NeMo?
By Karthick Selvam · Published · Updated
NIM and NeMo are parts of NVIDIA's software stack for generative AI: NIM for serving models, NeMo for building and customising them.
NVIDIA NIM
NIM microservices are prebuilt, optimised containers that serve AI models (LLMs, embedding, re-ranking, speech, vision and more) behind standard APIs. LLM NIMs expose OpenAI-compatible endpoints, which makes them easy to plug into existing applications. Models can be tried through NVIDIA's API catalog; production self-hosting is licensed through NVIDIA AI Enterprise.
NVIDIA NeMo
NeMo covers tools for the model lifecycle: the NeMo framework for training and customising models, NeMo microservices for tasks such as customisation and evaluation, and NeMo Guardrails, an open-source toolkit for adding safety and topic controls to LLM apps.
How they fit together
A typical pattern is to customise or select a model with NeMo, serve it with NIM, and build RAG or agent applications on top.
Frequently asked questions
Do I need NVIDIA GPUs to use NIM?
Self-hosted NIM containers run on NVIDIA GPUs; the hosted API catalog can be used for prototyping without your own GPUs.
Related programmes
- GPU Programming with CUDA
- Accelerated Data Science with NVIDIA RAPIDS
- Building and Serving LLM Apps with NVIDIA NIM & NeMo
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NVIDIA & GPU Computing guides
What Is CUDA?
CUDA is NVIDIA's parallel computing platform and programming model for running general-purpose code on NVIDIA GPUs.
What Is NVIDIA RAPIDS?
RAPIDS is a suite of open-source libraries from NVIDIA for GPU-accelerated data science and analytics.
TensorRT, TensorRT-LLM and Triton Explained
Three NVIDIA technologies for fast, scalable AI inference.