NVIDIA Corporation (NVDA): Canvas du modèle d'entreprise [Jan-2025 Mise à jour]

Dans le paysage rapide de la technologie en évolution, Nvidia Corporation est devenue une puissance transformatrice, révolutionnant l'informatique par le semi-conducteur révolutionnaire et les innovations de l'IA. Des humbles débuts à devenir un 1 billion de dollars La capitalisation boursière Titan, le modèle commercial stratégique de NVIDIA a systématiquement perturbé plusieurs industries - jeu, intelligence artificielle, computing cloud et véhicules autonomes - en repoussant constamment les limites des technologies de traitement graphique et d'accélération computationnelle. Cette plongée profonde dans le modèle de modèle commercial de Nvidia révèle le plan complexe derrière leur succès mondial extraordinaire, offrant des informations sans précédent sur la façon dont ce géant technologique continue de remodeler la frontière technologique.

NVIDIA Corporation (NVDA) - Modèle commercial: partenariats clés

Collaboration stratégique avec les grandes entreprises technologiques

Nvidia a établi des partenariats critiques avec les principaux géants de la technologie:

Partenaire	Détails de collaboration	Année initiée
Microsoft	Infrastructure Azure Cloud AI	2018
Google Cloud	Plate-forme d'IA et d'apprentissage automatique	2019
Services Web Amazon	Solutions informatiques accélérées par GPU	2016

Partenariats de fabrication de semi-conducteurs

Les partenariats critiques de fabrication de semi-conducteurs de Nvidia comprennent:

• TSMC (Taiwan Semiconductor Manufacturing Company): nœuds de processus 4 nm et 5 nm
• Samsung Electronics: processus de fabrication de puces avancées
• GlobalFoundries: fabrication spécialisée de semi-conducteurs

Recherche et partenariats académiques

Institution	Focus de recherche	Investissement
Mit	IA et recherche informatique	25 millions de dollars
Université de Stanford	Innovations d'apprentissage automatique	20 millions de dollars
Berkeley AI Research Lab	Algorithmes AI avancés	15 millions de dollars

Partenariats technologiques automobiles

Les collaborations de technologie de conduite autonomes de Nvidia:

• Mercedes-Benz: Intégration de la plate-forme AGX de lecteur
• Groupe Volkswagen: développement de véhicules autonomes
• Toyota: systèmes avancés d'assistance à la conduite
• Cruise (filiale GM): Technologie des véhicules autonomes

Partenariats écosystèmes logiciels et IA

Partenaire	Type de collaboration	Plate-forme
Chapeau rouge	Infrastructure d'IA d'entreprise	Ouvrir
Databricks	Plates-formes d'apprentissage automatique	Houle du lac
Visage étreint	Développement du modèle d'IA	Ai open source

NVIDIA Corporation (NVDA) - Modèle d'entreprise: Activités clés

Conception et développement de la puce semi-conducteurs

Dépenses de R&D en 2023: 10,37 milliards de dollars

Catégorie de conception de puces	Investissement annuel
Architecture GPU	4,2 milliards de dollars
Conception de l'accélérateur AI	3,8 milliards de dollars
Puces de centre de données	2,4 milliards de dollars

Fabrication avancée des accélérateurs GPU et IA

Partners de fabrication: TSMC (Taiwan Semiconductor Manufacturing Company)

• Technologie de processus 5nm
• Technologie de processus 4NM
• Techniques d'emballage avancées

Recherche et développement dans l'intelligence artificielle et l'apprentissage automatique

Focus de recherche sur l'IA	Investissement annuel
AI génératif	1,5 milliard de dollars
Systèmes autonomes	1,2 milliard de dollars
Algorithmes d'apprentissage automatique	900 millions de dollars

Plate-forme logicielle et développement de pilotes

Dépenses de développement logiciel: 1,6 milliard de dollars en 2023

• Plate-forme CUDA
• Bibliothèques CUDNN
• Optimiseur d'inférence Tensorrt
• NVIDIA AI Enterprise Software

Cloud Computing and Data Center Technology Innovation

Technologie du centre de données	Investissement annuel
Systèmes DGX	800 millions de dollars
Infrastructure de réseautage	600 millions de dollars
Services de cloud IA	400 millions de dollars

NVIDIA Corporation (NVDA) - Modèle d'entreprise: Ressources clés

Propriété intellectuelle et portefeuille de brevets

Depuis le quatrième trimestre 2023, Nvidia détient 26 144 brevets totaux dans le monde. Portefeuille de brevets évalué à environ 3,8 milliards de dollars.

Catégorie de brevet	Nombre de brevets
Technologie GPU	8,742
IA / Machine Learning	6,543
Conception de semi-conducteurs	5,621
Technologies de réseautage	3,987

Advanced Engineering and Research Talent

NVIDIA a employé 26 196 employés au total en janvier 2024, avec 22 410 dédiés aux rôles d'ingénierie et de recherche.

• Tapisseurs de doctorat: 3 412
• Titulaires de maîtrise: 8 765
• Titulaires de baccalauréat: 14 019

Capacités de conception de semi-conducteurs de pointe

L'infrastructure de conception de semi-conducteurs de NVIDIA prend en charge les processus avancés de fabrication de 4 nanomètres et de 5 nanomètres.

Capacité de conception	Spécification
Node de processus actuel	4nm / 5nm
Itérations de conception annuelles	3-4 versions d'architecture majeures
Centres de conception	7 emplacements mondiaux

Infrastructure de recherche et de développement

NVIDIA a investi 7,41 milliards de dollars en R&D au cours de l'exercice 2024, ce qui représente 24,7% des revenus totaux.

• Installations mondiales de R&D: 12 emplacements
• Budget de R&D annuel: 7,41 milliards de dollars
• Régers de recherche sur la recherche: IA, GPU, conduite autonome, informatique quantique

Ressources financières pour l'innovation

La force financière de Nvidia soutient l'innovation technologique continue.

Métrique financière	Valeur (Q4 2023)
Total et investissements totaux	25,8 milliards de dollars
Flux de trésorerie disponibles	5,6 milliards de dollars
Capitalisation boursière	1,87 billion de dollars

NVIDIA Corporation (NVDA) - Modèle d'entreprise: propositions de valeur

Solutions informatiques hautes performances pour les jeux et les marchés professionnels

Le GPU Nvidia GeForce RTX 4090 se vend à 1 599 $. Part de marché du GPU du jeu au T4 2023: 81% pour NVIDIA. Revenus de visualisation professionnelle au troisième trimestre 2023: 295 millions de dollars.

Gamme de produits	Segment de marché	Revenus (T1 2023)
Série GeForce RTX	Jeu	2,04 milliards de dollars
GPU professionnels quadro	Visualisation professionnelle	295 millions de dollars

Technologies accélérées de l'IA et de l'apprentissage automatique avancées

NVIDIA H100 AI Prix GPU: 30 000 $ à 40 000 $ par unité. Part de marché des puces AI en 2023: environ 95%.

• Plate-forme informatique parallèle CUDA
• Technologie de base du tenseur
• Systèmes de supercalculateur DGX AI

Technologies de traitement graphique innovantes

Dépenses de recherche et développement au cours de l'exercice 2024: 7,4 milliards de dollars. Portfolio de brevets technologiques graphiques: plus de 12 000 brevets actifs.

Écosystème complet des logiciels et du matériel

Composant écosystème	Description	Impact du marché
Plate-forme CUDA	Cadre informatique parallèle	Utilisé par 90% des chercheurs d'IA
bibliothèque CUDNN	Accélération du réseau neuronal profond	Norme dans le développement de l'IA

Solutions de pointe pour les véhicules et centres de données autonomes

NVIDIA Drive Platform Revenue en 2023: 1,2 milliard de dollars. Revenus du centre de données au troisième trimestre 2023: 4,28 milliards de dollars.

• Conduire une plate-forme AGX pour les véhicules autonomes
• CPU Grace pour l'informatique du centre de données
• DPU Bluefield pour l'informatique accélérée

NVIDIA Corporation (NVDA) - Modèle d'entreprise: Relations clients

Assistance technique et service client

NVIDIA fournit un support technique à plusieurs niveaux avec une couverture globale:

Niveau de soutien	Temps de réponse	Couverture
Assistance d'entreprise	Réponse de 4 heures	Global 24/7
Soutien professionnel	Réponse de 8 heures	Marchés majeurs
Support standard	Jour ouvrable suivant	Canaux en ligne

Engagement communautaire des développeurs

Nvidia entretient de vastes programmes de soutien aux développeurs:

• Programme de développeurs NVIDIA avec 2,5 millions de développeurs enregistrés
• Investissement annuel de 300 millions de dollars dans les ressources des développeurs
• 170+ forums techniques en ligne et plateformes communautaires

Mises à jour continues des produits et améliorations du micrologiciel

La stratégie de mise à jour de Nvidia comprend:

Type de mise à jour	Fréquence	Couverture
Mises à jour du pilote GPU	Mensuel	Toutes les gammes de produits
Correctifs de sécurité	Trimestriel	Solutions d'entreprise
Optimisations de performances	Semestriel	GPUS de jeux / professionnels

Assistance de conseil et de mise en œuvre au niveau de l'entreprise

Métriques de support d'entreprise:

• Équipe de support d'entreprise dédiée de plus de 1 200 spécialistes
• Valeur du contrat moyen: 2,5 millions de dollars par client d'entreprise
• Support pour 85% des entreprises technologiques du Fortune 500

Canaux de vente en ligne et direct avec un support personnalisé

La panne du canal de vente de Nvidia:

Canal de vente	Pourcentage	Revenus annuels
Ventes directes de l'entreprise	42%	12,3 milliards de dollars
Ventes directes en ligne	28%	8,2 milliards de dollars
Revendeurs autorisés	30%	8,8 milliards de dollars

Nvidia Corporation (NVDA) - Modèle d'entreprise: canaux

Diriger les ventes en ligne via le site Web de l'entreprise

Nvidia génère 60,92 milliards de dollars de revenus pour l'exercice 2024. Le canal de vente direct en ligne représente environ 22% du total des ventes, ce qui représente 13,4 milliards de dollars de revenus numériques directs.

Canal de vente	Pourcentage de revenus	Revenus annuels
Site Web en ligne direct	22%	13,4 milliards de dollars

Réseau mondial de détaillants technologiques

NVIDIA s'associe à 5 200 détaillants de technologie mondiaux, notamment:

• Meilleur achat
• Micro-centre
• Amazone
• Newegg

Équipes de vente d'entreprise

NVIDIA maintient 1 250 représentants des ventes d'entreprises dans le monde, ciblant:

• Clients du centre de données
• Fournisseurs de services cloud
• Constructeurs automobiles
• Institutions de recherche IA

Partenariats des fournisseurs de services cloud

NVIDIA collabore avec 7 principaux fournisseurs de services cloud:

Fournisseur de cloud	Statut de partenariat
AWS	Partenariat actif
Microsoft Azure	Partenariat actif
Google Cloud	Partenariat actif

Distribution du fabricant d'équipements d'origine (OEM)

NVIDIA fournit des GPU à 22 grands fabricants informatiques, notamment:

• Tablier
• HP
• Lenovo
• Asus

Distribution totale des revenus du canal:

Type de canal	Pourcentage de revenus
Directement en ligne	22%
Canaux de vente au détail	35%
Ventes directes d'entreprise	28%
Distribution OEM	15%

NVIDIA Corporation (NVDA) - Modèle d'entreprise: segments de clientèle

Joueurs professionnels et amateurs de jeux

En 2023, le segment de jeu de Nvidia a généré 8,29 milliards de dollars de revenus. La part de marché GEForce GPU s'élève à environ 75% dans le monde.

Métriques du segment de jeu	2023 données
Revenus de jeux totaux	8,29 milliards de dollars
Part de marché mondial du GPU	75%
Utilisateurs de jeux actifs	Plus de 200 millions

Clients d'entreprise et de cloud computing

Les revenus du centre de données de l'entreprise ont atteint 10,37 milliards de dollars au cours de l'exercice 2024. Les principaux fournisseurs de cloud comprennent:

• Services Web Amazon
• Microsoft Azure
• Google Cloud Platform
• Oracle Cloud Infrastructure

Métriques du segment d'entreprise	2024 données
Revenus du centre de données	10,37 milliards de dollars
Déploiements de GPU d'entreprise	Plus de 40 000 installations

Institutions scientifiques et de recherche

Nvidia soutient plus de 3 000 institutions de recherche dans le monde. Les déploiements de supercomputing comprennent:

• US Department of Energy Labs
• Cern
• Laboratoires nationaux

Métriques du segment de recherche	2024 données
Institutions de recherche soutenues	3,000+
Déploiements GPU de recherche sur l'IA	Plus de 1 500 systèmes spécialisés

Constructeurs automobiles

La technologie automobile de Nvidia prend en charge plus de 370 modèles de véhicules. Automotive Design Win Win Pipeline d'une valeur de 13 milliards de dollars.

Métriques du segment automobile	2024 données
Modèles de véhicules pris en charge	370+
Pipe de conception de victoire	13 milliards de dollars

Intelligence artificielle et développeurs d'apprentissage automatique

Les revenus des infrastructures de l'IA ont atteint 12,1 milliards de dollars au cours de l'exercice 2024. La plate-forme CUDA prend en charge plus de 3 millions de développeurs dans le monde.

Métriques de développement de l'IA	2024 données
Revenus d'infrastructure d'IA	12,1 milliards de dollars
Développeurs de plate-forme CUDA	3 millions +

NVIDIA Corporation (NVDA) - Modèle d'entreprise: Structure des coûts

Dépenses de recherche et développement approfondies

Les dépenses de R&D de NVIDIA pour l'exercice 2024 ont totalisé 13,97 milliards de dollars, ce qui représente environ 25,7% des revenus totaux. Les investissements de recherche et développement de l'entreprise se concentrent principalement sur:

• Développement d'architecture GPU
• IA et technologies d'apprentissage automatique
• Innovation de conception de semi-conducteurs

Exercice fiscal	Dépenses de R&D	Pourcentage de revenus
2024	13,97 milliards de dollars	25.7%
2023	7,34 milliards de dollars	21.4%

Coût de fabrication de semi-conducteurs élevés

Les coûts de fabrication de semi-conducteurs de Nvidia sont substantiels, avec des investissements importants dans les technologies de processus avancées:

• Fabrication de nœuds de processus TSMC 4NM et 5NM
• Coûts d'achat estimés à la plaquette: 15 000 $ à 20 000 $ par plaquette avancée
• Dépenses de fabrication annuelles de semi-conducteurs: environ 8 à 10 milliards de dollars

Acquisition et rétention mondiales de talents

La stratégie d'acquisition de talents de Nvidia implique des investissements importants en rémunération:

Catégorie de compensation	Coût annuel
Compensation totale des employés	4,2 milliards de dollars
Salaire moyen de l'ingénieur	$220,000 - $250,000

Infrastructure de marketing et de vente

Frais de marketing et de vente pour Nvidia au cours de l'exercice 2024:

• Total des dépenses de marketing et de vente: 3,6 milliards de dollars
• Équipe de vente mondiale: environ 2 500 professionnels
• Canaux de marketing: numériques, salons commerciaux, conférences techniques

Investissements d'innovation technologique continue

La répartition des coûts de l'innovation technologique de Nvidia:

Zone d'innovation	Investissement annuel
Recherche d'IA	2,5 milliards de dollars
Recherche informatique quantique	350 millions de dollars
Technologies graphiques avancées	1,8 milliard de dollars

NVIDIA Corporation (NVDA) - Modèle d'entreprise: Strots de revenus

Ventes de l'unité de traitement graphique (GPU)

Pour l'exercice 2024 (se terminant le 28 janvier 2024), NVIDIA a déclaré un chiffre d'affaires total des ventes de GPU de 60,22 milliards de dollars.

Segment GPU	Revenus (milliards USD)
GPUS de jeu	$10.37
GPUS du centre de données	$47.50

Centre de données et solutions informatiques AI

Les revenus du centre de données de NVIDIA pour l'exercice 2024 ont atteint 47,50 milliards de dollars, ce qui représente une augmentation de 409% d'une année sur l'autre.

• Infrastructure IA Revenus: 36,24 milliards de dollars
• Solutions informatiques d'entreprise: 11,26 milliards de dollars

Produits de visualisation professionnelle

Les revenus du segment de visualisation professionnelle pour l'exercice 2024 étaient de 1,48 milliard de dollars.

Catégorie de produits	Revenus (millions USD)
GPUS de poste de travail	$831
Logiciel GPU virtuel	$649

Licence de propriété intellectuelle

Les revenus de licence IP pour l'exercice 2024 étaient de 152 millions de dollars.

Abonnements en cloud computing et logiciel

Les revenus des services cloud et logiciels ont totalisé 1,06 milliard de dollars au cours de l'exercice 2024.

Catégorie de service	Revenus (millions USD)
Services GPU cloud	$712
Abonnements logiciels AI	$348

NVIDIA Corporation (NVDA) - Canvas Business Model: Value Propositions

You're looking at the core reasons why customers are lining up for NVIDIA Corporation's gear, especially as we close out 2025. It really boils down to raw, demonstrable performance and a platform that covers the entire AI lifecycle, from the cloud to the car.

Unmatched compute performance for AI training and inference

The performance gains with the Blackwell architecture are not incremental; they are step-changes that redefine what's possible in large model deployment. For instance, the Blackwell series is showing up in MLPerf benchmarks as potentially outperforming the prior Hopper class by a factor of four on the biggest LLM workloads, like Llama 2 70B, driven by features like the second-generation Transformer Engine and FP4 Tensor Cores.

When you look at the hard numbers from the MLPerf v4.1 Training benchmarks, NVIDIA is reporting up to a 2.2x gain for Blackwell over Hopper. Honestly, the math on training time is staggering: achieving the same performance on the GPT-3 175B benchmark required only 64 Blackwell GPUs compared to 256 Hopper GPUs.

For inference, which is where most AI engines run in production, the performance advantage is also clear. The H200 delivered up to 27% more generative AI inference performance over previous benchmark tests. Furthermore, Blackwell systems are showing 10x throughput per megawatt compared to the previous generation in the SemiAnalysis InferenceMAX benchmarks.

The market demand reflects this: CEO Jensen Huang confirmed in the Q3 FY26 earnings call that Blackwell sales are 'off the charts,' and cloud GPUs are sold out. Management has stated they currently have visibility to $0.5 trillion in Blackwell and Rubin revenue from the start of 2025 through the end of calendar year 2026.

Here's a quick comparison of the training performance leap:

Benchmark Metric	Hopper (H100)	Blackwell (B200/GB200)
MLPerf v4.1 AI Training Gain vs. Hopper	Baseline	Up to 2.2x
GPT-3 175B GPUs Required	256	64
Inference Throughput per Megawatt	Baseline	10x improvement

Full-stack accelerated computing platform (hardware, software, systems)

NVIDIA isn't just selling chips; they are selling the entire factory floor for AI. This full-stack approach integrates the chip architecture, the node and rack architecture (like the GB200 NVL72), and the necessary software layers. This is why the Data Center segment hit a record $51.2 billion in Q3 FY26 revenue, which is up 66% year-over-year. The total company revenue for that same quarter was $57.0 billion.

The platform's strength is evident across the stack:

• The networking business is now reported as the largest in the world.
• The non-GAAP gross margin for Q3 FY26 held strong at 73.6%.
• Systems are built with high-speed NVLink fabrics, HBM3e memory, and are designed for liquid cooling, which is table stakes for dense AI racks.

Lower Total Cost of Ownership (TCO) for AI infrastructure

While NVIDIA's performance is industry-leading, the competitive landscape means large hyperscalers are driving down the effective cost. For major customers, competitive pressure has reportedly led to concessions that reduce the Total Cost of Ownership (TCO) of their computing clusters by approximately 30%. This is seen when comparing the all-in cost per chip at rack scale for a GB200 or GB300 system versus alternatives like Google's TPUv7, which is cited as providing a more cost-effective alternative for certain performance levels.

Industry-leading AI-driven graphics and rendering for gamers

The gaming side still shows solid growth, even as Data Center dominates the narrative. For Q3 FY26, Gaming revenue came in at $4.3 billion, representing a 30% increase year-over-year. This is supported by the launch of technologies like NVIDIA DLSS 4 with Multi Frame Generation and NVIDIA Reflex.

End-to-end platforms for autonomous vehicles and robotics

NVIDIA Corporation's DRIVE platform provides a full 'cloud-to-car' stack, which is seeing significant commercial traction. The Automotive & Robotics segment reported $567 million in revenue for Q1 FY 2026, a 72% year-over-year jump. For the full fiscal year 2025, that segment generated $1.7 billion.

The company is targeting roughly $5 billion in automotive revenue for fiscal year 2026. This is being driven by major design wins:

• Toyota is building next-gen vehicles on DRIVE AGX Orin with DriveOS.
• Magna is deploying DRIVE Thor SoCs for L2-L4 ADAS.
• Continental plans to mass-produce NVIDIA-powered L4 self-driving trucks with Aurora.
• Partnerships include Volvo Cars, Mercedes-Benz, Lucid, BYD, and NIO using the DRIVE AGX platform.

Finance: review the Q4 FY26 automotive revenue forecast against the $5 billion FY2026 target by next Tuesday.

NVIDIA Corporation (NVDA) - Canvas Business Model: Customer Relationships

You're looking at how NVIDIA Corporation maintains its grip on the AI infrastructure market, and it all comes down to how they manage relationships across vastly different customer types. It's not a one-size-fits-all approach; it's highly segmented.

Dedicated, high-touch sales and engineering support for hyperscalers

For the largest cloud providers-the hyperscalers-the relationship is intensely collaborative. NVIDIA Corporation is enabling a scale and velocity in deploying one-and-a-half ton AI supercomputers the world has never seen before, according to their 2025 Annual Review. The Blackwell platform is powering AI infrastructure across these hyperscalers, enterprises, and sovereign clouds. This high-touch engagement is critical, as evidenced by the fact that NVIDIA's Data Centre revenue growth was reported at 17% in the second quarter of fiscal year 2025. This segment is about ensuring the entire stack, from the hardware to the networking like Spectrum-XGS Ethernet, is perfectly integrated for their massive AI factory buildouts.

Deep co-development with key enterprise and sovereign AI customers

The move from AI pilots to scaled deployment means deep integration with enterprise and government clients. NVIDIA Corporation is partnering with government and research institutions to build seven new supercomputers, with some systems utilizing more than 100,000 NVIDIA GPUs to support open science and national laboratories. This level of co-design extends to the enterprise side; for instance, Dell announced that it already had 2,000 customers within a year of announcing its NVIDIA AI stack. Furthermore, major enterprise SAS companies like ServiceNow, SAP, and Salesforce are adopting NVIDIA Inference Microservices (NIMs), which essentially require NVIDIA hardware to run effectively. Sovereign AI strategies are also a focus, with NVIDIA announcing GPU deployments with 12 global telcos to fuel these national infrastructure projects.

Large-scale, community-driven support for the developer ecosystem

The foundation of NVIDIA Corporation's long-term moat is its developer community, which is supported through extensive, scalable resources. The NVIDIA Developer Program provides free access to advanced tools and a dedicated community. This includes access to GPU-optimized software via the NGC Catalog and support for startups through the NVIDIA Inception accelerator, which provides access to the Deep Learning Institute (DLI). To democratize access, NVIDIA introduced Project Digits at CES 2025, a device priced at $3,000 that offers 1 PFLOPS of FP4 performance, tailored for developers to run large language models locally.

The key components of this developer engagement include:

• Access to the NGC Catalog for software and models.
• Support for startups via NVIDIA Inception.
• Training through the Deep Learning Institute (DLI).
• New hardware like Project Digits for local AI development.

Standardized, transactional relationship with retail consumers

For the consumer segment, primarily focused on gaming and creative workloads with GeForce GPUs, the relationship is largely transactional, driven by product availability and performance benchmarks. As of the first quarter of 2025, NVIDIA Corporation held a 92% share of the discrete desktop and laptop GPU market. This segment relies on the established brand and ecosystem, like DLSS 4 updates, but the direct, high-touch engineering support seen with hyperscalers is absent here.

GTC conference as the defintely central engagement point

The GPU Technology Conference (GTC) serves as the single most important event for aligning the entire ecosystem-from the largest customers to individual developers. It is the epicenter for showcasing AI opportunity, and every company wishing to play a role is in attendance. The March 2025 event solidified this role as the 'Super Bowl of AI.'

Here are the key engagement metrics from GTC 2025:

Metric	Value
In-Person Attendees	25,000
Virtual Attendees	300,000
Exhibitors On-Site	Nearly 400
Total Sessions	Over 200

The conference is where NVIDIA Corporation unveils its next-generation platforms, such as Blackwell Ultra, which delivers 50x more AI factory output compared to the Hopper platform for large-scale reasoning workloads. Finance: draft 13-week cash view by Friday.

NVIDIA Corporation (NVDA) - Canvas Business Model: Channels

You're looking at how NVIDIA Corporation gets its massive revenue-which hit $130.5 billion in fiscal year 2025-into the hands of its customers. The channels are highly segmented, reflecting the dual nature of the business: powering the world's largest AI infrastructure and serving the consumer gaming market.

The Data Center segment is the engine, accounting for 88.27% of total revenue, or $115.19 billion in FY2025. This revenue flows through several critical, high-volume channels.

Direct sales to major Data Center customers and governments

This channel involves direct engagement for the highest-tier, largest-scale AI deployments. The concentration here is notable; in the most recent quarter, more than half of Data Center revenue came from just three unnamed clients. Here's the quick math on that concentration:

Customer Group	Recent Quarterly Revenue Amount
Customer A	$9.5 billion
Customer B	$6.6 billion
Customer C	$5.7 billion

This direct channel also includes significant government contracts, such as the announced partnership for the $500 billion Stargate Project.

Cloud Service Providers (CSPs) offering GPU instances (e.g., DGX Cloud)

Cloud Service Providers are fundamental volume purchasers for the Data Center segment. NVIDIA revealed that major CSPs, including AWS, CoreWeave, Google Cloud Platform (GCP), Microsoft Azure, and Oracle Cloud Infrastructure (OCI), are deploying NVIDIA GB200 systems globally. The networking component supporting these massive clusters is also a key channel indicator; the combined networking segment delivered $8.19 billion in revenue in the third quarter of fiscal 2025, growing 162% year-over-year.

Original Equipment Manufacturers (OEMs) like Dell and HPE

OEMs take NVIDIA components, integrate them into servers and systems, and resell them. While the search results don't break out OEM revenue specifically, the 'OEM And Other' segment represented 0.30% of total FY2025 revenue, amounting to $389.00 million. This channel is crucial for distributing standard server platforms containing NVIDIA accelerators.

Global retail and e-commerce networks for Gaming GPUs

The Gaming segment generated $11.35 billion in FY2025, representing 8.7% of the total. This consumer-facing channel is dominated by NVIDIA's brand strength. In the first quarter of 2025, NVIDIA captured a staggering 92% share in the add-in board (AIB) GPU market, and generally holds over 80% market share in discrete GPUs used for gaming.

The launch of the GeForce RTX 50 Series drove this performance, with Blackwell architecture sales contributing billions of dollars in its first quarter, with one report citing $11 billion of Blackwell revenue delivered in the fourth quarter of fiscal 2025 alone.

Value-Added Resellers (VARs) for enterprise AI solutions

VARs are essential for deploying specialized, often smaller-scale or customized, enterprise AI solutions where direct CSP or OEM routes are less efficient. This channel helps distribute solutions built around platforms like the NVIDIA DGX Cloud and NIM microservices to a wider enterprise base.

The distribution of NVIDIA's massive Data Center revenue relies on a mix of direct hyperscaler deals and channel partners:

• Cloud Service Providers (CSPs) are the primary volume buyers for AI infrastructure.
• Direct sales capture the largest, most strategic national and government AI buildouts.
• OEMs and VARs handle the broader enterprise and system integrator market distribution.
• The Gaming channel maintains near-total dominance in the discrete GPU retail space.

Finance: draft 13-week cash view by Friday.

NVIDIA Corporation (NVDA) - Canvas Business Model: Customer Segments

You're looking at the core buyers driving NVIDIA Corporation's massive scale as of late 2025. Honestly, the customer base is heavily skewed, which is a key strategic point to watch.

Hyperscale Cloud Providers represent the undisputed largest segment. This group, which includes giants like AWS, Google Cloud Platform (GCP), Microsoft Azure, and Oracle Cloud Infrastructure (OCI), is responsible for the bulk of the company's success. In fiscal year 2025, the Data Center segment, which primarily serves these providers, generated $115.19 billion in revenue. That figure alone represents a staggering 88.27% of NVIDIA Corporation's total revenue for the year. These providers are deploying NVIDIA GB200 systems globally to meet the surging demand for AI training and inference workloads.

The next tier involves AI/ML Startups and Large Enterprises, including those in finance and healthcare. While often bundled into the Data Center reporting, this group is actively building sovereign AI capabilities and deploying AI infrastructure beyond the major cloud players. The growth here is fueled by the need for generative AI, moving from training to reasoning workloads.

For PC Gamers and Enthusiasts, this remains a foundational, though now smaller, customer group. Gaming and AI PC revenue was $11.35 billion in fiscal year 2025. That's about 8.7% of the total pie. They are the initial market for new consumer GPUs, like the recently announced GeForce RTX 50 Series cards.

The specialized segments round out the picture. Automotive OEMs and Tier 1 suppliers are buying in for AI-driven vehicle technologies. This segment brought in $1.69 billion in fiscal year 2025. Then you have Government and Academic High-Performance Computing (HPC) centers, which utilize the technology for research and national projects, such as powering the top machines on the Green500 list.

Here's the quick math on how the revenue broke down across these customer-facing areas for fiscal year 2025:

Customer Segment Focus	FY2025 Revenue (USD)	Percentage of Total Revenue
Data Center (Hyperscalers/Enterprise AI)	$115.19 billion	88.27%
Gaming and AI PC	$11.35 billion	8.7%
Professional Visualization	$1.88 billion	1.44%
Automotive	$1.69 billion	1.3%
OEM And Other	$389.00 million	0.3%

The core customer types driving the Data Center segment include:

• Cloud service providers (AWS, Azure, GCP, OCI)
• Enterprise customers building AI infrastructure
• Sovereign AI initiatives
• Consumer internet companies using generative AI

What this estimate hides is the intense focus on securing supply commitments; NVIDIA's purchase commitments and obligations for inventory and production capacity were $30.8 billion as of the end of FY2025, showing how much they are pre-paying to serve these top segments.

Finance: draft 13-week cash view by Friday.

NVIDIA Corporation (NVDA) - Canvas Business Model: Cost Structure

When you look at NVIDIA Corporation's cost structure, you're seeing the financial reality of leading the accelerated computing revolution. The sheer scale of their revenue in Fiscal Year 2025-a massive $130.50 billion-is what makes the absolute dollar costs for R&D and operations look so large, yet their efficiency, or operating leverage, is what really matters for your analysis.

The most significant component, the High cost of revenue due to advanced chip fabrication (CoR), reflects the expense of designing and outsourcing the manufacturing of their cutting-edge GPUs and networking gear. For FY2025, the Cost of Revenue was $32.639 billion. That translates to a CoR as a percentage of sales of about 24.99% for the full fiscal year, which is a key metric showing how efficiently they are managing the direct costs of their products, even with the complexity of advanced node fabrication.

Next, consider the engine for future growth: Research and Development (R&D). NVIDIA is pouring capital into staying ahead of the curve, especially with the Blackwell architecture now ramping. For FY2025, R&D expense hit $12.91 billion. The good news for your valuation model is that this investment, while large in absolute terms, represented only 9.89% of that year's revenue, showing significant operating leverage compared to prior years.

Here's a quick breakdown of the major expense categories from the close of FY2025, so you can map it against that $130.50 billion revenue base:

Expense Category	FY2025 Absolute Amount (GAAP)	FY2025 % of Revenue
Cost of Revenue	$32.639 billion	Approx. 24.99%
Research & Development (R&D)	$12.91 billion	9.89%
Sales, General, and Administrative (SG&A)	$3.49 billion	2.67%
Total Operating Expenses (Sum of R&D, SG&A, and Other OpEx)	$16.41 billion	Approx. 12.58%

You'll notice the Sales, General, and Administrative (SG&A) expenses are relatively lean for a company of this size, coming in at $3.49 billion, or just 2.67% of revenue in FY2025. This low percentage is a direct result of the massive revenue growth outpacing the growth in overhead staff and administrative costs; that's the operating leverage you want to see.

The Costs associated with global supply chain and logistics are embedded within the Cost of Revenue and operating expenses, particularly in the SG&A for managing that global footprint. Since NVIDIA operates a fabless model, they avoid the multi-billion dollar capital expenditures of building foundries, but they still incur significant costs managing the complex logistics, inventory risk, and securing capacity with partners like TSMC. This is a variable cost that scales with production volume.

Looking ahead, the company's forward guidance gives you a sense of near-term cost control expectations. For instance, the Non-GAAP outlook for the first quarter of Fiscal Year 2026 projected operating expenses to be approximately $3.6 billion. Still, you should watch the full-year FY2026 operating expense growth projection, which management guided to be in the mid-30% range year-over-year, even as revenue growth forecasts moderated slightly due to export controls.

To summarize the expense profile you're dealing with:

• R&D spending is a strategic investment, not just a cost; it was $12.91 billion in FY2025.
• The company is managing overhead well, with SG&A at only 2.67% of FY2025 revenue.
• The Q1 FY2026 Non-GAAP operating expense projection was set at $3.6 billion.
• Cost of Revenue, at $32.639 billion in FY2025, is the largest single cost line item.

Finance: draft the Q2 FY2026 OpEx forecast based on the mid-30% full-year growth guidance by Friday.

NVIDIA Corporation (NVDA) - Canvas Business Model: Revenue Streams

You're looking at how NVIDIA Corporation actually brings in the money, and right now, it's all about the data center. It's a massive shift from where the company was even a few years ago, but the numbers tell the whole story for fiscal year 2025.

Data Center GPU and System Sales were the undisputed engine, pulling in a staggering $115.19 billion in FY2025. Honestly, this segment's growth is what defines the company's current valuation. This revenue comes from selling the core AI accelerators, like the H100s and the newer Blackwell systems, to hyperscalers and enterprise customers building out their AI infrastructure.

Gaming GPU Sales, while still a huge business, is now a smaller piece of the pie compared to the AI behemoth. For FY2025, this segment generated $11.35 billion. It's still a healthy business, driven by high-end GeForce GPUs for gamers and AI PC users, but the scale is dwarfed by the data center demand.

Software and Support Subscriptions are the recurring revenue layer that analysts love to see building out. The projected annual run rate is approaching $2 billion by the end of 2025. This is tied to things like the AI Enterprise software licenses and support contracts that lock customers into the NVIDIA ecosystem, which is a key part of their moat.

Automotive Platform and Licensing Fees brought in $1.69 billion in FY2025. This stream is about selling the DRIVE platform and related software for autonomous driving and in-vehicle infotainment systems. It shows NVIDIA is successfully monetizing its compute expertise beyond the server rack.

Professional Visualization Hardware and Software Sales also contributed significantly, hitting $1.88 billion in FY2025. This covers the RTX Ada Generation GPUs and related software for designers, engineers, and media professionals who need serious rendering power.

To give you a clearer picture of the entire revenue landscape for FY2025, here is the full breakdown of the key segments:

Revenue Segment	FY2025 Revenue Amount	Primary Driver
Data Center GPU and System Sales	$115.19 billion	AI Training and Inference Compute Demand
Gaming GPU Sales	$11.35 billion	Consumer and AI PC GPU Sales
Professional Visualization Hardware and Software Sales	$1.88 billion	Workstation Graphics and Design Software
Automotive Platform and Licensing Fees	$1.69 billion	DRIVE Platform and Autonomous Vehicle Licensing
Software and Support Subscriptions (ARR)	Approaching $2 billion	AI Enterprise and Cloud Service Attach Rates
OEM And Other	$389.00 million	Legacy and Miscellaneous Hardware Sales

The growth in these streams is heavily concentrated, which is important to note for near-term risk assessment. The key revenue drivers for the Data Center segment, which is the lion's share, include:

• Hyperscale cloud provider demand for AI infrastructure.
• Enterprise adoption of sovereign AI capabilities.
• Sales of full AI racks, not just individual chips.

Also, remember that the software component is designed to reinforce the hardware sales. If onboarding takes 14+ days, churn risk rises, but the subscription model helps secure long-term revenue visibility. Finance: draft 13-week cash view by Friday.