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  • 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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  • Displaying 64 results
    NVIDIA
    NVIDIA
    PyTorch
    PyTorch is a GPU accelerated tensor computational framework. Functionality can be extended with common Python libraries such as NumPy and SciPy. Automatic differentiation is done with a tape-based system at the functional and neural network layer levels.
    Container
    NVIDIA
    NVIDIA
    NeMo Framework Megatron Backend
    NVIDIA NeMo™ framework Megatron backend supports pre-training, post-training, and reinforcement learning of LLMs and multi-modal generative AI models with state-of-the-art data processing, model training techniques, and flexible deployment options.
    Container
    NVIDIA
    NVIDIA
    vLLM
    vLLM is a fast and easy-to-use library for LLM inference and serving. The NVIDIA vLLM NGC Container is optimized for GPU acceleration, and contains a validated set of libraries that enable and optimize GPU performance.
    Container
    NVIDIA
    NVIDIA
    Llama-3.3-nemotron-super-49b-v1.5
    This container houses the Llama-3.3-Nemotron-Super-49B-v1.5, which is a significantly upgraded version of Llama-3.3-Nemotron-Super-49B-v1 and is a large language model (LLM) which is a derivative of Meta Llama-3.3-70B-Instruct
    Container
    NVIDIA
    NVIDIA
    Kaldi
    Kaldi is an open-source software framework for speech processing.
    Container
    NVIDIA
    NVIDIA
    Riva Skills Quick Start
    Scripts and utilities for getting started with Riva Speech Skills
    Resource
    NVIDIA
    NVIDIA
    SGLang
    SGLang is a fast serving framework for large language models and vision language models. The NVIDIA SGLang NGC Container is optimized for GPU acceleration, and contains a validated set of libraries that enable and optimize GPU performance.
    Container
    NVIDIA AI Enterprise
    NVIDIA
    NVIDIA
    Llama-3.3-nemotron-super-49b-v1.5-PB-25h2
    This container houses the **Llama-3.3-Nemotron-Super-49B-v1.5 PB 25h2**, which is a significantly upgraded version of Llama-3.3-Nemotron-Super-49B-v1 and is a large language model (LLM) which is a derivative of Meta Llama-3.3-70B-Instruct
    Container
    NVIDIA
    NVIDIA
    Nemotron-Content-Safety-Reasoning-4B (Experimental)
    Nemotron Content Safety Reasoning 4B is a Large Language Model (LLM) classifier designed to function as a dynamic and adaptable guardrail for content safety and dialogue moderation (topic-following).
    Container
    Xiaomi
    Mimo-V2-Flash (Experimental)
    This container houses the model MiMo-V2-Flash.
    Container
    NVIDIA
    NVIDIA
    Nemotron-3-Ultra-550B-A55B
    Nemotron-3-Ultra-550B-A55B NIM container packages NVIDIA's large language model featuring a hybrid Latent Mixture-of-Experts (LatentMoE) architecture with Multi-Token Prediction (MTP) layers.
    Container
    OpenAI
    GPT-OSS-120b-Turbo
    The GPT-OSS-120b-Turbo NIM container packages OpenAI's GPT-OSS-120b large language model, a sparse Mixture of Experts (MoE) architecture with 120B total parameters and 5.1B active parameters, as an NVIDIA NIM microservice.
    Container
    NVIDIA
    NVIDIA
    BERT for TensorFlow Jupyter Notebook
    Jupyter Notebook example for Question Answering with BERT for TensorFlow
    Resource
    NVIDIA
    NVIDIA
    Fine-Tune and Optimize BERT
    Jupyter Notebooks for BERT Pre-training, Fine-Tuning and Inference profiling and optimization via TensorFlow, AMP, XLA, DLProf, TF-TRT and Triton.
    Container
    NVIDIA
    NVIDIA
    DLI NLP Course - Base Environment with NeMo
    Base environment used in the NVIDIA NeMo projects of the NVIDIA Deep Learning Institute (DLI) course, "Building Transformer-Based Natural Language Processing Applications". This container also includes a "Next Steps" project.
    Container
    NVIDIA Corporation
    NVIDIA Corporation
    AI-Q Blueprint
    AI-Q Blueprint Helm Chart
    Helm Chart
    NVIDIA
    NVIDIA
    DLI Conversational AI Course - Base Environment
    Base environment of the NVIDIA Deep Learning Institute (DLI) course, "Building Conversational AI Applications". This container also includes a "Next Steps" project.
    Container
    NVIDIA NeMo Microservices
    NVIDIA
    NVIDIA
    deplot
    NVIDIA NIM for GPU accelerated Deplot inference through OpenAI compatible APIs
    Container
    University of Florida Health
    GatorTron-OG
    GatorTron-OG is a Megatron BERT model trained on pre-trained on de-identified clinical notes from the University of Florida Health System.
    Model
    NVIDIA
    NVIDIA
    BERT on Google Cloud AI Platform
    Fine-tune a pre-trained BERT model with the SQuAD dataset, optimize for inference using TensorRT and deploy with Triton Inference Server on Google Cloud AI Platform using Custom Containers
    Resource
    NVIDIA
    NVIDIA
    BioMegatron345mUncased
    Megatron pretrained on uncased biomedical dataset PubMed with 345 million parameters.
    Model
    NVIDIA
    NVIDIA
    Question Answering Notebook
    End to End workflow for question answering starting with training in TAO Toolkit and deployment using Riva.
    Resource
    NVIDIA
    NVIDIA
    BERT+SQuAD TF Finetuning Notebook
    NVIDIA's BERT leverages mixed precision arithmetic and Tensor Cores on A100, V100 and T4 GPUs for faster training while maintaining target accuracy. This notebook demonstrates BERT Question Answering Fine-Tuning with Mixed Precision on SQuaD 2.0 Dataset.
    Resource
    NVIDIA
    NVIDIA
    Text Classification Notebook
    End to End sample workflow for Text Classification starting with training in TAO Toolkit and deployment using Riva.
    Resource

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