nvidia

NVIDIA's Python API for defining LLMs and running them on NVIDIA GPUs with state-of-the-art inference optimizations.

NVIDIA's SDK for high-performance deep learning inference on NVIDIA GPUs — optimizes trained models for low-latency production deployment.

An open platform of world-foundation models, datasets, and tools for building physical-AI and robotics applications.

A real-time, full-duplex speech-to-speech conversational AI model that enables persona control through text-based role prompts and audio-based voice conditioning. Trained on synthetic and real conversations, it produces natural, low-latency spoken interactions with consistent personas.

NVIDIA's LLM vulnerability scanner — probes models for jailbreaks, prompt injection, data leaks, hallucinations, and toxicity at scale.

NVIDIA's foundation model for generalist humanoid robots (GR00T N1.7) — perception-to-action policy that transfers across body shapes and tasks.

KV-cache compression toolkit for LLMs — drop-in techniques to cut memory and extend context length.

NVIDIA's neural vocoder that synthesizes high-fidelity audio (speech, music, singing) from mel-spectrograms.

Open-source deep-learning framework for building and deploying AI weather and climate prediction workflows.

NVIDIA's security scanner for AI agent skills — detects vulnerabilities and malicious patterns.

Lightweight C++ LLM and VLM inference engine optimized for edge devices and physical AI.

Text normalization and inverse text normalization toolkit for ASR and TTS pipelines.

NVIDIA GEAR Lab's DreamGen initiative tackling the robotics data problem using world models for embodied AI training.

Collection of logits processors to customize LLM generation for specific tasks. Drop-in for vLLM, HF, TRT-LLM.