NVIDIA's quarterly revenue by market segment - Our World in Data

Source: original

What you should know about this indicator

NVIDIA's quarterly revenue by market segment

NVIDIA

NVIDIA's self-reported quarterly revenue across its main market segments, in US dollars. This data is not adjusted for inflation.

Source

NVIDIA Corporation (2026) – with major processing by Our World in Data

Last updated

June 8, 2026

Next expected update

September 2026

Unit

US dollars

More Data on Artificial Intelligence

Sources and processing

This data is based on the following sources

NVIDIA Corporation – NVIDIA Quarterly Revenue by Market Segment

Quarterly revenue data for NVIDIA Corporation, broken down by market segment and reported in millions of US dollars per fiscal quarter.

NVIDIA's fiscal year is a 52/53-week period ending on the last Sunday in January. Each fiscal quarter is named after the fiscal year in which it ends, so fiscal year 2026 covers ~Feb 2025 to Jan 2026, and its quarters end on the last Sunday of April, July, October, and January respectively.

Retrieved on

June 8, 2026

Retrieved from

https://investor.nvidia.com/financial-info/financial-reports/default.aspx

Citation

This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.

NVIDIA Corporation - Quarterly Revenue Trends by Market Platform (2014-2026)

Quarterly revenue data for NVIDIA Corporation, broken down by market segment and reported in millions of US dollars per fiscal quarter.

NVIDIA's fiscal year is a 52/53-week period ending on the last Sunday in January. Each fiscal quarter is named after the fiscal year in which it ends, so fiscal year 2026 covers ~Feb 2025 to Jan 2026, and its quarters end on the last Sunday of April, July, October, and January respectively.

Retrieved on

June 8, 2026

Retrieved from

https://investor.nvidia.com/financial-info/financial-reports/default.aspx

Citation

This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.

NVIDIA Corporation - Quarterly Revenue Trends by Market Platform (2014-2026)

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Notes on our processing step for this indicator

NVIDIA publishes its quarterly revenue split by market segment. We combine all of its historical disclosures (covering fiscal years 2016 through 2027) into a single time series with two main categories — "Data centers and AI" and "Gaming, devices, automotive" — alongside the overall total.

In the first quarter of fiscal 2027 (the quarter ending April 26, 2026), NVIDIA changed the structure of these disclosures. Until Q4 FY26 (the quarter ending January 25, 2026), NVIDIA reported five market segments: "Data Center", "Gaming", "Professional Visualization", "Auto", and "OEM & Other". From Q1 FY27 onward, it reports just two segments — "Data Center" (further broken down into "Hyperscale" and "AI Clouds, Industrial & Enterprise") and "Edge Computing". Reconciling the eight quarters that appear in both presentations confirms that NVIDIA's new "Edge Computing" segment equals the sum of the previous categories labeled as "Gaming", "Professional Visualization", "Auto", and "OEM & Other".

To keep the time series consistent over the full period, we sum the four older non-data-center segments ("Gaming", "Professional Visualization", "Auto", and "OEM & Other") into a single bucket for quarters before Q1 FY27, and we use NVIDIA's combined value from Q1 FY27 onward. We label this bucket "Gaming, devices, automotive" rather than NVIDIA's own term ("Edge Computing") to more plainly describe what's in it. Data center revenue is taken as reported in both presentations.

Each data point is dated by NVIDIA's reported fiscal-quarter end — the last Sunday of April, July, October, or January (for example, Q4 FY26 is dated January 25, 2026).

Reuse this work

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: NVIDIA's quarterly revenue by market segment”, part of the following publication: Charlie Giattino, Edouard Mathieu, Veronika Samborska, and Max Roser (2023) - “Artificial Intelligence”. Data adapted from NVIDIA Corporation. Retrieved from https://archive.ourworldindata.org/20260609-081329/grapher/nvidia-quarterly-revenue-segment.html [online resource] (archived on June 9, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

NVIDIA Corporation (2026) – with major processing by Our World in Data

Full citation

NVIDIA Corporation (2026) – with major processing by Our World in Data. “NVIDIA's quarterly revenue by market segment – NVIDIA” [dataset]. NVIDIA Corporation, “NVIDIA Quarterly Revenue by Market Segment” [original data]. Retrieved June 11, 2026 from https://archive.ourworldindata.org/20260609-081329/grapher/nvidia-quarterly-revenue-segment.html (archived on June 9, 2026).

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Download full dataIncludes all entities and time points#### Download displayed dataIncludes only the entities and time points currently visible in the chart

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Download full data, including all entities and time points

Download only the currently selected data visible in the chart

Data URL (CSV format)

https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.csv?v=1&csvType=full&useColumnShortNames=false

Metadata URL (JSON format)

https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets

=IMPORTDATA("https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.csv?v=1&csvType=full&useColumnShortNames=false")

Python with Pandas

import pandas as pd import requests

Fetch the data.

df = pd.read_csv("https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

Fetch the metadata

metadata = requests.get("https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()

R

library(jsonlite)

Fetch the data

df <- read.csv("https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.csv?v=1&csvType=full&useColumnShortNames=false")

Fetch the metadata

metadata <- fromJSON("https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.metadata.json?v=1&csvType=full&useColumnShortNames=false")

Stata

import delimited "https://ourworldindata.org/grapher/nvidia-quarterly-revenue-segment.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear