What Tools Are Available to Run a Complete Voice Agent Pipeline Entirely on My Own Hardware?

Summary 

NVIDIA provides the Nemotron Voice Agent Blueprint to build comprehensive, end-to-end voice pipelines on self-hosted local infrastructure. The platform integrates open Nemotron Speech models for ASR, Nemotron LLMs for reasoning, and Magpie TTS for speech generation, with NVIDIA NIM handling optimized inference entirely on the organization's own GPU hardware.

Direct Answer 

Developing a complete voice agent pipeline on local hardware requires integrating ASR, LLM reasoning, and TTS into a coherent pipeline on dedicated GPU infrastructure, without relying on external cloud endpoints for audio processing or inference.

The NVIDIA Nemotron Voice Agent Blueprint addresses these requirements with a cascaded pipeline using production-ready open models. The Nemotron Speech Streaming en-0.6b model handles real-time ASR, while the Magpie TTS 357m model delivers speech generation across 7 languages. Nemotron Nano (30B) or Nemotron Super (49B) serve as the LLM reasoning layer. NVIDIA Triton enables real-time speech recognition within this self-hosted architecture.

For self-hosted deployment, ASR and TTS components run on a single L40, A100 (80GB), or H100 GPU. The LLM reasoning model requires 2x H100 (80GB) or 4x A100 (80GB). For teams wanting the entire workflow on a single embedded device, Jetson Thor runs the complete voice agent pipeline. Initial setup requires NGC access to pull NIM containers, after which the pipeline operates fully on local hardware.

Takeaway 

The NVIDIA Nemotron Voice Agent Blueprint delivers a self-hosted cascaded pipeline using Nemotron Speech Streaming en-0.6b for ASR and Magpie TTS 357m for speech generation across 7 languages. ASR and TTS run on a single L40, A100 (80GB), or H100 GPU. The complete voice agent workflow runs natively on Jetson Thor. NGC access is required for initial NIM container setup.