NVIDIA
NVDAAI chip and GPU manufacturer, with a full-stack software line — CUDA-X, NeMo, NIM and Dynamo — for training and running models.
Press release · 26 Aug 2026News reporting · 26 Aug 2026Regulatory filing · 9 Sep 2026Regulatory filing · 9 Sep 2026Press release · 9 Sep 2026Press release · 9 Sep 2026Company disclosure · 9 Sep 2026Press release · 9 Sep 2026Press release · 9 Sep 2026Press release · 9 Sep 2026Company disclosure · 19 Mar 2026Products
Selected offerings — the AI products recorded here, not the vendor's full catalogue.
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Supported software suite for building and deploying AI workloads on NVIDIA hardware.
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NVIDIA Blackwell Hardware
Data-centre GPU architecture used for training and serving large models, sold in servers and rack systems.
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Programming toolkit and libraries for running general-purpose computation on NVIDIA GPUs.
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NVIDIA DGX Cloud Infrastructure service
NVIDIA's AI cloud of GPU clusters and managed AI services, which NVIDIA's own page now presents as its internal environment for building its models, and which is still sold on Microsoft's Azure marketplace.
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NVIDIA DRIVE Platform
End-to-end autonomous-vehicle platform spanning training infrastructure, simulation and safety-certified in-vehicle compute for production autonomy from L2++ to L4.
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Open robotics development platform combining simulation, CUDA-accelerated perception libraries, ROS 2 integration and humanoid tooling for building AI-powered robots.
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NVIDIA Vera Rubin Hardware
NVIDIA's data-centre platform succeeding Blackwell, pairing Rubin GPUs with Vera CPUs at rack scale for agentic AI and reasoning workloads.
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Data-processing-unit (DPU) platform combining compute with accelerated networking, storage and security for AI-factory infrastructure.
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Free application that enhances livestreams and video calls with AI noise removal, background replacement and other audio/video effects; requires a GeForce RTX GPU.
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Desktop AI supercomputer powered by the GB10 Grace Blackwell Superchip for local autonomous agents, running models up to 200B parameters for inference.
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Deskside AI supercomputer powered by the GB300 Grace Blackwell Ultra Superchip, up to 20 petaFLOPS and 748GB coherent memory, supporting models up to 1T parameters.
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Reference baseboard specification (HGX B200, B300, Vera Rubin NVL8) that system integrators and OEMs build into complete AI servers, listed in NVIDIA's Qualified System Catalog.
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Edge-AI developer kits (IGX Thor, IGX Thor Mini, IGX Orin) for industrial and medical edge computing.
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Family of embedded AI modules and developer kits for robotics and edge AI (Thor, AGX Orin, Orin NX/Nano, Xavier, TX2/Nano series).
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Scalable data-centre server systems (e.g. OVX L40S with four or eight GPUs) for AI and graphics workloads, built by NVIDIA OVX partners.
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Quantum-X800 InfiniBand switching for large-scale AI clusters, part of NVIDIA's InfiniBand networking line.
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Professional GPU line (RTX PRO 2000 through RTX PRO 6000) for AI, graphics and simulation workloads across Blackwell, Ada Lovelace, Ampere and Turing architectures.
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Ethernet networking platform (switches, ConnectX SuperNICs, BlueField DPUs, LinkX cables) purpose-built for generative-AI-scale data centres.
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Software that virtualizes GPUs across VMs in enterprise data centres and cloud deployments, licensed through NVIDIA's vGPU License and Support Portal.
Inside NVIDIA AI Enterprise
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Suite of libraries and microservices covering the AI agent lifecycle - data curation, customisation, evaluation, guardrails and monitoring.
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Prebuilt inference microservices that package foundation models with optimised serving engines and standard APIs, deployable as hosted endpoints or self-hosted containers.
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Platform of OpenUSD-based libraries and microservices for building simulation-ready digital twins and synthetic-data environments used to train and validate physical AI and robots.
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Suite of AI technologies (speech, intelligence, animation models and plugins) for building conversational, actionable in-game characters, mostly MIT-licensed with some components under NVIDIA's open model license.
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Free development-environment manager for creating, customizing and collaborating on AI applications across GPU systems, with enterprise support available through an NVIDIA AI Enterprise license.
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Development platform for AI-driven biology and drug discovery: open models, libraries, datasets and NIM microservices for the full AI lifecycle in biopharma.
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Open-source model-deployment server for TensorRT, PyTorch, ONNX, OpenVINO and other frameworks across GPUs and CPUs, with production support and stable APIs through NVIDIA AI Enterprise.
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Suite of open-source, GPU-accelerated data-science libraries (cuDF, cuML, cuGraph, cuxfilter), rebranding to "CUDA-X for Data Science."
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Deployable speech-AI library (ASR/TTS) for production inference, free to prototype via build.nvidia.com and licensed for production deployment through NVIDIA AI Enterprise.
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Ecosystem of compilers, runtimes and optimization tools for high-performance deep-learning inference; TensorRT-LLM and Model Optimizer are free on GitHub, with commercial deployment options via NVIDIA AI Enterprise.
Closest alternatives 17
Similar products 133
Closest alternatives are pairs a vendor page itself compares. Similar products are matched from what each product does; nothing in that group is asserted as a rivalry.
Sources
- Market cap
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Third-party database · 27 Aug 2026
Refreshed against the listing's own page.
- Employees
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Regulatory filing · 25 Jan 2026
NVIDIA CORP Form 10-K (Item 1, Human Capital), SEC, filed 2026-02-25, for the period ended 2026-01-25. Filing states: "As of the end of fiscal year 2026, we had approximately 42,000 employees in 38 countries; 31,000 were engaged in research and development." CIK 1045810.
- Founded
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Wikipedia infobox "founded" field, read 2026-08-27.
- Revenue (TTM)
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Regulatory filing · 25 Jan 2026
NVIDIA CORP Form 10-K, SEC, filed 2026-02-25, for fiscal year ended 2026-01-25. us-gaap:Revenues per XBRL, audited. This is the trailing twelve months AS OF the fiscal year end, not as of today. CIK 1045810.
- Description
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Official documentation · 6 Sep 2026
"Powers most of the world's AI training and inference" is a market-share claim with no scope, no metric and no date, and NVIDIA does not make it: its own AI page claims "full-stack innovation across accelerated infrastructure, enterprise-grade software, and AI models" and names the software line the sentence now names.
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