ContainersNVIDIADeepSeek-R1NVIDIALlama-3.1-Nemotron-70B-InstructNVIDIAPyTorch
CollectionsNVIDIAOmniverse Kit (FB)NVIDIADeepStream SDKNVIDIAOmniverse Kit App Streaming
ModelsNVIDIAStyleGAN3 pretrained modelsNVIDIAPeopleNetNVIDIATrafficCamNet
ResourcesNVIDIARiva Skills Quick Start
Helm ChartsNVIDIAGPU OperatorNVIDIANVIDIA NIM Operator
SearchSearch thousands of GPU-optimized Containers, pretrained Models, SDKs, and Helm charts—ready to accelerate AI, digital twins, and HPC from cloud to edge.
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NVIDIA NIM
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NIM Container GPUs
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Displaying 22 results
NVIDIA Developer Program
NVIDIA
NVIDIA
CodeLlama-70B-Instruct
NVIDIA NIM for GPU accelerated CodeLlama-70B inference through OpenAI compatible APIs
Container
NVIDIA
NVIDIA
CUDA Deep Learning
CUDA is a parallel computing platform and programming model that enhances computing performance using NVIDIA GPUs. CUDA Deep Learning integrates networking and GPU-accelerated libraries like cuDNN, cuTensor, NCCL, HPC-x, and the CUDA Toolkit.
Container
NVIDIA
NVIDIA
NVIDIA HPC SDK
The NVIDIA HPC SDK is a comprehensive suite of compilers, libraries and tools essential to maximizing developer productivity and the performance and portability of HPC applications.
Container
NVIDIA
NVIDIA
NVIDIA cuQuantum Appliance
The NVIDIA cuQuantum Appliance is a highly performant multi-GPU multi-node solution for quantum circuit simulation.
Container
NVIDIA
NVIDIA
Aerial CUDA-Accelerated RAN
An SDK (Software Development Kit) for building commercial-grade, AI-native, 3GPP, and O-RAN compliant 5G/6G gNB software on NVIDIA-accelerated computing platforms.
Container
NVIDIA
NVIDIA
CUDA-Q
With a unified and open programming model, CUDA Quantum is a first-of-its-kind, open-source platform for integrated quantum-classical programming
Container
NVIDIA
NVIDIA
MLflow Triton Plugin
The MLflow Triton plugin is for deploying your models from MLflow to Triton Inference Server.
Container
NVIDIA
NVIDIA
PyNvVideoCodec
PyNvVideoCodec is NVIDIA’s Python based video codec library for hardware accelerated video encode and decode on NVIDIA GPUs.
Resource
NVIDIA
NVIDIA
UCS Tools Release
Contains public release for UCS Tools. Documentation at https://docs.nvidia.com/ucf/
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Windows (FB)
Toolkit for building native Omniverse applications and microservices.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit Extensions Registry (FB)
Snapshot of Kit Extensions registry for Air Gap.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Linux (FB)
Toolkit for building native Omniverse applications and microservices.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit Extensions Registry (PB 25h2)
Snapshot of Kit Extensions registry for Air Gap.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Windows (PB 25h2)
Toolkit for building native Omniverse applications and microservices.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Linux (PB 25h2)
Toolkit for building native Omniverse applications and microservices.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Windows (PB 26h1)
Toolkit for building native Omniverse applications and microservices.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit Extensions Registry (PB 26h1)
Snapshot of Kit Extensions registry for Air Gap.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Linux (PB 26h1)
Toolkit for building native Omniverse applications and microservices.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Linux ARM (PB 25h2)
Toolkit for building native Omniverse applications and microservices.
Resource
NVIDIA AI Enterprise
NVIDIA
NVIDIA
Kit SDK Air Gap Linux ARM (PB 26h1)
Toolkit for building native Omniverse applications and microservices.
Resource
Collection
NVIDIA
NVIDIA
Getting Started
Collections are use-case based curated content available in one easy-to-use package for for various applications including speech, intelligent video analytics, recommendations, and more.
2
Collection
NVIDIA
NVIDIA
NeMo Microservices
This collection contains NeMo microservices that provide a comprehensive suite of features to build an end-to-end platform for fine-tuning, evaluating, and serving large language models (LLMs) on your Kubernetes cluster.
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