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NeMo-Export-Deploy

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NeMo Export-Deploy

Type: Library Tags: NVIDIA, NeMo, export, deploy, TensorRT-LLM, vLLM, Triton, Ray Serve, inference, LLM, multimodal Related: NVIDIA-NeMo, NeMo-AutoModel, NeMo-Megatron-Bridge, NeMo-Run, NeMo-Customizer, NeMo-Evaluator, NVIDIA-NIM, TensorRT-LLM, Triton-Inference-Server, vLLM, TensorRT, NVIDIA-AI-Enterprise Sources: https://docs.nvidia.com/nemo/export-deploy/latest/index.html, https://docs.nvidia.com/nemo/export-deploy/latest/apidocs/nemo_export/nemo_export.html, https://docs.nvidia.com/nemo-framework/user-guide/latest/overview.html Last Updated: 2026-04-29

Summary

NeMo Export-Deploy is NVIDIA’s NeMo library for exporting and deploying NeMo and Hugging Face models into production inference environments. Current NVIDIA docs describe export paths to TensorRT-LLM, vLLM, TensorRT/ONNX-style targets where applicable, deployment through NVIDIA Triton Inference Server or Ray Serve, quantized model export, multi-GPU and distributed inference, and multi-instance deployment patterns.

Detail

Purpose

Training and customization are only useful if the resulting model can be served reliably. NeMo Export-Deploy provides the handoff from NeMo/Hugging Face checkpoints to optimized serving runtimes so teams can move models from training workflows into inference systems.

Current scope

  • Export and deploy LLMs and multimodal models from NeMo, NeMo-AutoModel, NeMo-Megatron-Bridge, Megatron-LM, and Hugging Face formats.
  • Export paths for TensorRT-LLM and vLLM, with deployment examples through Triton-Inference-Server and Ray Serve.
  • Support for quantized model export, including FP8-oriented flows in current docs.
  • Multi-GPU, distributed inference, and multi-instance deployment guidance.
  • API surfaces under nemo_export and nemo_deploy.

NVIDIA context

Export-Deploy sits between NVIDIA-NeMo training/customization and production inference surfaces such as NVIDIA-NIM, TensorRT-LLM, Triton-Inference-Server, and vLLM. It is a durable NVIDIA-authored topic because it has a separate docs tree, package identity, and deployment role.

Connections

  • NVIDIA-NeMo - parent suite for training, customization, and deployment.
  • NeMo-AutoModel - Hugging Face-compatible checkpoints can be exported and deployed.
  • NeMo-Megatron-Bridge - Megatron Bridge checkpoints are a documented export/deploy path.
  • NeMo-Run - experiment execution layer before deployment handoff.
  • NeMo-Customizer and NeMo-Evaluator - model adaptation and evaluation happen before production deployment.
  • NVIDIA-NIM - higher-level model microservice product layer adjacent to NeMo deployment workflows.
  • TensorRT-LLM - optimized LLM export and inference backend.
  • Triton-Inference-Server - production serving target for exported models.
  • vLLM - supported inference backend for deployable LLM paths.
  • TensorRT - broader NVIDIA inference compiler/runtime family.
  • NVIDIA-AI-Enterprise - enterprise support context for production NeMo deployment.

Source Excerpts

  • NVIDIA docs describe Export-Deploy as tools and APIs for exporting and deploying NeMo and Hugging Face models.
  • Current docs list TensorRT-LLM, vLLM, Triton Inference Server, and Ray Serve as deployment paths.

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