COMPANY / LIVE INTELLIGENCE

Nvidia

The company is no longer just a chip supplier. Track the full stack across compute, networking, systems, software and the customers financing the AI buildout.

CEOJensen Huang
TICKERNVDA
COREAccelerated computing
WATCHDemand + execution
PRIMARY DOCUMENTS / SEC EDGAR

Latest NVDA filings.

Investor-relevant reports are shown first, followed by the company’s other recent official submissions.

10-QQuarterly financial reportFiled 2026-05-20 · Period 2026-04-26SEC ↗10-QQuarterly financial reportFiled 2025-11-19 · Period 2025-10-26SEC ↗10-KAnnual financial reportFiled 2026-02-25 · Period 2026-01-25SEC ↗8-KMaterial company eventFiled 2026-07-02 · Period 2026-06-28SEC ↗8-KMaterial company eventFiled 2026-06-30 · Period 2026-06-24SEC ↗8-KMaterial company eventFiled 2026-06-18 · Period 2026-06-15SEC ↗DEF 14AProxy and shareholder meetingFiled 2026-05-12 · Period 2026-06-24SEC ↗SCHEDULE 13GOfficial SEC filingFiled 2026-07-20SEC ↗
EARNINGS / QUARTERLY TRACKER

Nvidia, quarter by quarter.

Results, guidance and earnings coverage are grouped only when the source headline identifies the reporting period.

NIVEGU SIGNAL

The moat is a system, not a single chip.

Nvidia combines processors, networking, systems and a mature software ecosystem. That breadth strengthens demand—but also turns every product transition, supply constraint and customer budget into a high-stakes execution test.

OPPORTUNITY

AI training, inference, enterprise deployment, robotics and accelerated scientific computing can expand the addressable market beyond hyperscale data centers.

RISK

Large customers can build alternatives, regulators can restrict markets, competitors can narrow performance gaps and infrastructure returns can disappoint.

PLATFORM MAP

One stack.
Five engines.

01

COMPUTE

GPU architectures and accelerated-computing platforms

02

SYSTEMS

DGX and integrated AI infrastructure

03

NETWORKING

High-speed interconnects that join large computing clusters

04

SOFTWARE

CUDA, libraries and enterprise AI software

05

EDGE

Gaming, workstations, robotics and automotive platforms

COMPANY TIMELINE

From graphics to infrastructure

1993

Nvidia is founded.

1999

The GeForce product line helps define the modern consumer GPU market.

2006

CUDA opens the GPU to general-purpose parallel computing.

2020s

Data-center AI shifts Nvidia from component vendor toward full-stack infrastructure provider.

NOW

Blackwell deployment, inference economics, power availability and customer returns shape the next phase.

AI-ASSISTED FRAMEWORK / EDITOR REVIEWED

Four ways to read Nvidia

BEGINNER

A company that makes specialized computing systems for graphics, artificial intelligence and other demanding workloads.

INVESTOR

A high-expectation infrastructure leader whose premium depends on sustained demand, platform adoption and clean product execution.

BUSINESS

A full-stack strategy connecting hardware, networking and software so customers buy a platform rather than an interchangeable part.

GLOBAL

A strategic supplier positioned inside trade policy, energy constraints, sovereign AI programs and advanced-manufacturing supply chains.

FAQ

Questions, answered.

What does Nvidia actually sell?

Nvidia sells accelerated-computing platforms: GPUs, networking, systems and software used across data centers, gaming, professional visualization and automotive markets.

Why is CUDA important?

CUDA is Nvidia’s programming platform and software ecosystem. It helps developers run accelerated workloads on Nvidia hardware and raises the cost of switching to a different stack.

What is the central investment risk?

Expectations are unusually high. Customer concentration, supply dependence, export controls, competition and slower infrastructure spending can make results and valuation sensitive to any execution gap.