Deploy NVIDIA Nemotron Speech ASR Model on Novita AI GPU Instance

Real-time speech recognition demands more than accuracy—it requires consistent low latency without burning through GPU cycles.

NVIDIA Nemotron Speech ASR model solves latency drift and redundant compute with its cache-aware streaming architecture. This eliminates the need for buffered inference, delivering stable, sub-100ms latency (24ms median time-to-first-token) and up to 3x more throughput on your GPU.

This guide shows you how to deploy NVIDIA Nemotron Speech ASR on Novita AI GPU instances using our pre-configured template. Build production-grade voice applications without infrastructure complexity.

What is NVIDIA Nemotron Speech ASR?

NVIDIA Nemotron Speech ASR is a streaming automatic speech recognition model designed for real-time applications with minimal latency.

Traditional ASR systems rely on buffered audio chunks, creating latency drift and inefficient GPU usage. Nemotron Speech ASR uses cache-aware streaming to process audio continuously without buffering delays.

NVIDIA Nemotron Speech ASR specifications:

• Architecture: Cache-aware streaming ASR with Conformer-CTC
• Latency performance: Sub-100ms end-to-end processing
• Time-to-first-token: 24ms median latency
• Throughput improvement: Up to 3x vs. buffered inference
• Language support: English (0.6B parameter variant)
• Model size: 600M parameters optimized for streaming

The cache-aware streaming architecture eliminates latency drift and redundant compute, making NVIDIA Nemotron Speech ASR ideal for live transcription, voice assistants, call center analytics, and interactive AI applications.

What is NVIDIA NeMo Framework?

NVIDIA NeMo Framework is a scalable, cloud-native generative AI framework for researchers and PyTorch developers.

NeMo Framework supports development across multiple AI domains:

• Large Language Models (LLMs)
• Multimodal Models (MMs)
• Automatic Speech Recognition (ASR)
• Text-to-Speech (TTS)
• Computer Vision (CV)

The framework helps you create, customize, and deploy generative AI models efficiently by leveraging existing code and pre-trained model checkpoints.

NVIDIA Nemotron Speech ASR is built on NeMo Framework, providing production-ready ASR capabilities with minimal setup.

For complete technical documentation, see the NeMo Framework User Guide.

Why Deploy Nemotron Speech ASR on Novita AI?

Novita AI GPU instances provide optimized infrastructure for deploying NVIDIA Nemotron Speech ASR at scale:

Fast deployment: Launch GPU instances in seconds with pre-configured NeMo templates. No manual environment setup required.

Cost-effective pricing: Pay-per-second billing with no long-term contracts or minimum commitments. Scale up or down based on demand.

Pre-configured templates: NeMo Framework and dependencies come pre-installed. Start running Nemotron Speech ASR immediately.

Global infrastructure: Low-latency GPU access across multiple regions for worldwide deployment.

Developer tools: Real-time monitoring, SSH access, and straightforward template deployment from the Novita AI library.

Whether you’re prototyping a voice assistant or scaling a production transcription pipeline, Novita AI handles GPU infrastructure so you can focus on building ASR applications.

Prerequisites for Deployment

Before deploying NVIDIA Nemotron Speech ASR, ensure you have:

• Novita AI account with sufficient credits (sign up here)
• Audio test files in WAV format for model validation
• Basic SSH knowledge for instance access and configuration
• GPU requirements understanding for your specific workload

No prior NeMo Framework experience required—the Novita AI template handles initial setup.

Deploy Nemotron Speech ASR: Step-by-Step Guide

Step 1: Access Novita AI Console

Log in to your Novita AI account and navigate to the GPU interface.

Select Get Started to access the deployment management dashboard.

Step 2: Select Nemotron Speech ASR Template

Locate Nemotron Speech ASR in the template repository and click to begin installation.

Direct template access: https://novita.ai/templates-library/108969

The template includes pre-configured NeMo Framework settings and optimized parameters for Nemotron Speech ASR deployment.

Step 3: Configure GPU Instance Settings

Configure your GPU instance parameters:

• Memory allocation: Based on expected concurrent audio streams
• Storage requirements: Sufficient space for model files and audio processing
• Network settings: Configure for your geographic region
• GPU selection: Choose based on throughput requirements

Click Deploy to proceed with your configuration.

Step 4: Review Configuration and Deploy

Review your instance configuration summary:

• GPU type and quantity
• Memory and storage allocation
• Network region
• Estimated costs

Verify all settings and click Deploy to start instance creation.

Step 5: Monitor Instance Creation

After initiating deployment, Novita AI automatically redirects you to the instance management page.

Your Nemotron Speech ASR instance creates in the background while you monitor progress.

Step 6: Track Download Progress

Monitor the NeMo Framework image download in real-time.

Instance status updates from Pulling to Running when deployment completes.

Click the arrow icon next to your instance name for detailed progress information.

Step 7: Verify Deployment Status

Click the Logs button to view instance startup logs.

Verify that NeMo services initialized correctly and Nemotron Speech ASR is ready for inference.

Install NeMo Framework Dependencies

Once your GPU instance is running, connect via SSH to install required dependencies.

Install System Dependencies and NeMo Toolkit

Run the following commands to set up your environment:

bash

apt-get update && apt-get install -y libsndfile1 ffmpeg 
pip install Cython packaging
pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[asr]

Dependency breakdown:

• libsndfile1: Audio file I/O library for WAV processing
• ffmpeg: Multimedia framework for audio conversion
• Cython: Performance optimization for Python code
• nemo_toolkit[asr]: NeMo Framework with ASR-specific modules

Installation completes in 5-10 minutes depending on network speed.

Run NVIDIA Nemotron Speech ASR Model

Download Nemotron Speech ASR Model

Download NVIDIA Nemotron Speech ASR from the official Hugging Face repository.

The model file format is .nemo and contains all necessary parameters for inference.

Use Official NeMo Inference Script

The NeMo Framework provides an optimized inference script for cache-aware streaming ASR.

Reference script: speech_to_text_cache_aware_streaming_infer.py

Run Nemotron Speech ASR Inference

Execute the following command to transcribe audio:

bash

python speech_to_text_cache_aware_streaming_infer.py \
    model_path=/yourPath/nemotron-speech-streaming-en-0.6b/nemotron-speech-streaming-en-0.6b.nemo \
    audio_file=/yourPath/audio.wav

Inference Parameters

Configure these parameters for your deployment:

• model_path: Full path to Nemotron Speech ASR .nemo model file
• audio_file: Path to input audio file (WAV format recommended)

Example Transcription Output

Successful inference produces output similar to:

bash

[NeMo I 2026-01-09 08:13:32 speech_to_text_cache_aware_streaming_infer:282] Final streaming transcriptions: ['The English forwarded to the French baskets of flowers of which they had made a plentiful provision to greet the arrival of the young princess. The French, in return, invited the English to a supper, which was to be given the next day.']

This confirms Nemotron Speech ASR successfully converted audio stream to text with cache-aware streaming architecture.

Nemotron Speech ASR Use Cases

Real-Time Live Transcription

Deploy NVIDIA Nemotron Speech ASR for live captioning systems in meetings, webinars, and broadcasts.

The sub-100ms latency ensures captions appear in real-time without noticeable delays.

Voice Assistant Applications

Build conversational AI agents with instant speech recognition for natural user interactions.

Cache-aware streaming eliminates buffering delays for responsive voice commands.

Call Center Analytics and Monitoring

Transcribe customer calls in real-time for sentiment analysis, compliance monitoring, and agent assistance.

High throughput (3x improvement) enables concurrent call processing without additional GPU resources.

Accessibility Solutions

Create assistive technologies for hearing-impaired users requiring low-latency live captions.

Stable latency performance ensures consistent accessibility across varying audio conditions.

Media Production and Content Creation

Automate subtitle generation for podcasts, videos, and live streams with high-accuracy English transcription.

Streaming architecture processes long-form content efficiently without memory constraints.

Conclusion

Deploying NVIDIA Nemotron Speech ASR on Novita AI GPU instances delivers production-ready speech recognition infrastructure in minutes, not hours.

The model’s cache-aware streaming architecture provides the stable sub-100ms latency and 3x GPU efficiency improvement your real-time applications demand. Novita AI’s pre-configured template eliminates complex NeMo Framework setup, letting you focus on building voice applications instead of managing infrastructure.

Whether you’re developing voice assistants, transcription services, call center analytics, or accessibility tools, this deployment combination removes traditional tradeoffs between latency, throughput, and operational complexity.

Start deploying Nemotron Speech ASR on Novita AI today with flexible pay-per-second GPU pricing and no upfront commitments.

Novita AI is a leading AI cloud platform that provides developers with easy-to-use APIs and affordable, reliable GPU infrastructure for building and scaling AI applications.