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    Copyright © 2026 NVIDIA Corporation

    NVIDIA

    parakeet-1.1b-rnnt-multilingual-asr

    Downloadable

    High accuracy and optimized performance for transcription in 25 languages

    • Automatic Speech Recognition
    • NVIDIA NIM
    • NVIDIA Riva
    • Speech-to-Text
    Get API Key
    API ReferenceAPI Reference
    Accelerated by DGX Cloud
    Deploying your application in production? Get started with a 90-day evaluation of NVIDIA AI Enterprise

    Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.

    Step 1
    Generate API Key

    Step 2
    Pull and Run the NIM

    $ docker login nvcr.io
Username: $oauthtoken
Password: <PASTE_API_KEY_HERE>

    Refer Supported Models for full list of models.

    export NGC_API_KEY=<PASTE_API_KEY_HERE>

docker run -it --rm --name=parakeet-1-1b-rnnt-multilingual \
   --runtime=nvidia \
   --gpus '"device=0"' \
   --shm-size=8GB \
   -e NGC_API_KEY \
   -e NIM_HTTP_API_PORT=9000 \
   -e NIM_GRPC_API_PORT=50051 \
   -p 9000:9000 \
   -p 50051:50051 \
   -e NIM_TAGS_SELECTOR=mode=str \
   nvcr.io/nim/nvidia/parakeet-1-1b-rnnt-multilingual:latest

    It may take a up to 30 minutes depending on your network speed, for the container to be ready and start accepting requests from the time the docker container is started.

    Step 3
    Test the NIM

    Open a new terminal and run following command to check if the service is ready to handle inference requests

    curl -X 'GET' 'http://localhost:9000/v1/health/ready'

    If the service is ready, you get a response similar to the following.

    {"ready":true}

    Install the Riva Python client package

    sudo apt-get install python3-pip
pip install -U nvidia-riva-client

    Download Riva sample clients

    git clone https://github.com/nvidia-riva/python-clients.git

    Run Speech to Text inference in streaming modes. Riva ASR supports Mono, 16-bit audio in WAV, OPUS and FLAC formats.

    python3 python-clients/scripts/asr/transcribe_file.py --server 0.0.0.0:50051 --input-file <path_to_speech_file>

    For more details on getting started with this NIM, visit the Riva ASR NIM Docs.