NVIDIA

The latest open, multimodal generation models for world generation and reasoning for Physical AI.

Collection of datasets used in the post-training phase of Nemotron Nano v3.

Collection of RL verifiable data for NeMo Gym

A collection of generative models quantized and optimized for inference with Model Optimizer.

Framework of PyTorch composable modules for developing physics guided machine learning training pipelines. https://github.com/NVIDIA/physicsnemo

3D-Informed World-Consistent Video Generation with Precise Camera Control

Collection of open, commercial-grade datasets for physical AI developers

Eagle is a family of frontier vision-language models with data-centric strategies. The model supports both HD image and long-context video input.

A family of frontier-class multimodal large language models (LLMs) that achieve state-of-the-art results on vision-language tasks and text-only tasks.

NeMo Parakeet ASR Models attain strong speech recognition accuracy while being efficient for inference. Available in CTC and RNN-Transducer variants.

The Nemotron 3 8B Family of models is optimized for building production-ready generative AI applications for the enterprise.

A family of compressed models obtained via pruning and knowledge distillation

Large scale pre-training datasets used in the Nemotron family of models.

Open, Production-ready Enterprise Models

Large scale pre-training datasets used in the Nemotron family of models.

A collection of speculative decoding modules created using Model Optimizer.

NVIDIA Clara Models for Biology

Ultra-efficient reasoning model! SOTA Accuracy / CoT Length trade-offs

Reasoning data for supervised finetuning of LLMs to advance data distillation for competitive coding

NV-Embed is a generalist embedding model encompassing retrieval, reranking, classification, clustering, STS tasks.

BigVGAN is a universal neural vocoder that generates audio waveform using mel spectrogram as input.

Enabling 4k resolution for VLMs, CVPR 2025, https://nvlabs.github.io/PS3/