NVIDIA
NVIDIA pioneered accelerated computing and now builds data-center-scale AI infrastructure: GPUs, systems, networking and a broad software stack for AI training and inference, scientific computing, data analytics, robotics, graphics, automotive and industrial digital twins. Its stated ambition is to transform the world's largest industries through accelerated computing and AI.
At a Glance
- Hyperscale and cloud computing
- Enterprise IT and AI developers
- Semiconductor and technology companies
- Gaming and PC OEMs
- +7 more
AI Tools by NVIDIA
(15)
NVIDIA Personal AI Router (PAIR)
Local Inference Router for LLMs
Megatron-LM
Large Scale Transformer Training
NVIDIA NeMo-Aligner
LLM Alignment Toolkit for NeMo
NVIDIA Triton Inference Server
Open Source AI Model Serving
NVIDIA cuVS
GPU Vector Search and Clustering
NVIDIA Agent Skills
Verified Skills for Coding Agents
TensorRT LLM
LLM Inference Optimization for NVIDIA GPUs
NeMo Data Designer
Python Synthetic Data Generator
garak
Open Source LLM Vulnerability Scanner
NVIDIA NeMo Guardrails
Open Source LLM Guardrails Toolkit
Discussions
SMNvidia Paid 86 Times Revenue for Hugging Face
Nvidia just spend $12.93 billion on Hugging Face, a company producing roughly $150 million in annualized revenue. The multiple is about 86 times revenue. It shifts depending on which number counts. Nvidia's SEC filing puts the price paid to Hugging Face shareholders at about $11.9 billion and reserv…
Latest News
NVIDIA announced plans with Oracle to expand Vera Rubin to multi-gigawatt scale and bring the Vera CPU to Oracle Cloud Infrastructure.
NVIDIA and Meta announced an expanded collaboration on Muse and the Muse family of models.
NVIDIA announced advances to the Isaac platform for general-purpose robotics, including a reference humanoid, frameworks, simulation pipelines and data.
Google Cloud and NVIDIA announced general availability of NVIDIA Vera Rubin infrastructure.
Products & Services
Data-center GPUs, systems and reference architectures for AI training, inference, high-performance computing and enterprise workloads.
GPU-accelerated computing platform with compilers, development tools, libraries, frameworks, SDKs and APIs.
Consumer gaming and creator graphics platforms combining programmable GPUs, real-time ray tracing and AI-powered rendering such as DLSS.
Integrated AI supercomputers and rack-scale infrastructure for model development, training and inference.
Market Position
NVIDIA is positioned as a full-stack accelerated-computing and AI-infrastructure company rather than only a chip vendor. Its competitive moat combines high-performance GPUs and networking with CUDA, optimized libraries, systems, developer tools and a large partner ecosystem. The principal competitive set includes AMD and Intel for GPUs and data-center accelerators, Broadcom and Marvell in networking/custom silicon, Qualcomm and Samsung in certain edge/accelerator markets, and increasingly hyperscalers' internally designed AI chips; NVIDIA's 2026 10-K also identifies Ambarella, Broadcom, Intel, Qualcomm, Renesas and Samsung among competitors in relevant markets.
Leadership
Founders
Jensen Huang
Founder, President and CEO since NVIDIA's inception. Before founding NVIDIA, he held roles at LSI Logic, including Director of Coreware, and was a microprocessor designer at Advanced Micro Devices (AMD).
Chris A. Malachowsky
NVIDIA co-founder and NVIDIA Fellow; he previously worked with Jensen Huang and Curtis Priem at Sun Microsystems and brought an electrical-engineering and systems/software background to the founding team.
Curtis Priem
NVIDIA co-founder and original chief technical architect; he previously worked at Sun Microsystems and was an engineer focused on graphics hardware.
Executive Team
Jensen Huang
Founder, President and CEO
Founded NVIDIA in 1993; previously worked at LSI Logic and AMD.
Chris A. Malachowsky
Founder and NVIDIA Fellow
Co-founder and long-time NVIDIA technical leader; previously worked at Sun Microsystems.
Board of Directors
Founding Story
Huang, Malachowsky and Priem founded NVIDIA on April 5, 1993, with the initial vision of bringing realistic 3D graphics to gaming and multimedia on personal computers. The founders saw the shift toward increasingly sophisticated computer chips and pursued a specialized graphics-processor company; that strategy later expanded into general-purpose GPU computing and AI.
Business Model
Revenue Model
NVIDIA primarily sells semiconductors, complete accelerated-computing systems, networking products and related software/support to hyperscalers, cloud providers, enterprises, OEMs, distributors and other customers. Revenue is mainly product and system sales, with software, subscriptions and enterprise support contributing to the broader platform model; CUDA and the software ecosystem increase adoption and switching costs.
Target Markets
- Hyperscale and cloud computing
- Enterprise IT and AI developers
- Semiconductor and technology companies
- Gaming and PC OEMs
- Professional visualization and media
- Automotive and autonomous mobility
- Large-language-model and generative-AI training and inference
- Cloud AI and hyperscale data centers
- Scientific computing, climate and weather modeling
- Gaming, graphics, rendering and content creation
- Data analytics and high-performance computing
- Industrial digital twins, engineering and manufacturing simulation
- Amazon Web Services
- Google Cloud
- Microsoft Azure
- Oracle Cloud Infrastructure