SearchSearch thousands of GPU-optimized Containers, pretrained Models, SDKs, and Helm charts—ready to accelerate AI, digital twins, and HPC from cloud to edge.
NVIDIA AI Enterprise
NVIDIA AI Enterprise
14
13
9
2
  • NVIDIA NIM
    NVIDIA NIM
    9
  • NIM Container GPUs
    NIM Container GPUs
  • Use Case
    Use Case
    23
    12
    11
    8
    7
    4
    4
    2
    1
    1
    1
    1
    1
    1
    1
    1
    1
  • NVIDIA Platform
    NVIDIA Platform
    12
    11
    8
    8
    8
    5
    4
    4
    3
    3
    2
    2
    1
    1
    1
  • Industry
    Industry
    19
    16
    15
    11
    9
    7
    5
    5
    2
    2
    2
    1
    1
    1
    1
    1
  • Solution
    Solution
    397
    270
    258
    238
    176
    169
    112
    111
    103
    55
    49
    46
    40
    16
    16
    14
    12
    11
    11
    9
    8
    4
    3
    3
    2
    1
    1
  • Publisher
    Publisher
    43
  • Policy
    Policy
    2
  • Displaying 46 results
    Docker containers distributed as part of the TAO Toolkit package
    Container
    NVIDIA Developer Program
    The Llama 3.2 Vision instruction-tuned models are optimized for visual recognition, image reasoning, captioning, and answering general questions about an image.
    Container
    Build a Video Search and Summarization Agent Ingest massive volumes of live or archived videos and extract insights for summarization and interactive Q&A
    Container
    Alert Inspector UI container for the VSS event reviewer usecase
    Container
    Alert Bridge Container for the VSS event reviewer deployment
    Container
    Video Storage Toolkit (VST) is microservice for efficient management of cameras and videos
    Container
    Course environment for the Deep Learning Institute (DLI) course, "Getting Started with AI on Jetson Nano".
    Container
    NVIDIA Developer Program
    It transmits uncompressed video (SMPTE ST 2110-20) and PCM audio (SMPTE ST 2110-30) stream per speaker as an input source for the NVIDIA Active Speaker Detection NIM.
    Container
    NVIDIA
    NVIDIA
    DLPP
    DLPP is a family of lightweight deep-learning networks trained for video post-processing. The model's introduction can be found at https://blogs.nvidia.com/blog/rtx-video-super-resolution/. To the public, it is also known as RTX VSR.
    Model
    NVIDIA AI Enterprise
    TAO Production Branch October 2025 (PB 25h2) offers a 9-month lifecycle for API stability, with monthly patches for high and critical software vulnerabilities. This release includes Government Ready images for regulated environments.
    Container
    Base Container for building VSS engine from source
    Container
    DeepStream based perception service that takes in streaming video data and performs object detection and tracking
    Container
    Generate time-series insights for the physical spaces based on perception metadata.
    Container
    Blueprint for the Video Search and Summarization Agent
    Helm Chart
    RT-DETR object detection model for 2D warehouse applications
    Model
    Container for AI Analytics API service
    Container
    AI Inference Service for using VLM (visual language model) on streaming video for greater contextual understanding and natural language interaction
    Container
    The CV UI is a sample application used for configuring  Nvidia CV Event Detector Microservice
    Container
    Provides natural language interfaces for performing video summarization
    Container
    This image contains pre-built binaries to run different Isaac ROS applications on the Nova Orin Developer Kit.
    Container
    Nvidia Sample CV Event Detector Microservice for detecting events for VSS Event Reviewer workflow.
    Container
    This image contains pre-built binaries to run different Isaac ROS applications on the Nova Carter robot.
    Container
    AI Inference service to perform zero-shot (open vocabulary) object detection of any objects on streaming video data
    Container
    PyNVVideoCodec (Python NVIDIA Video Codec) is a set of python APIs for hardware accelerated video decoding and encoding.
    Resource