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NVIDIA develops accelerated computing hardware and software. Coverage follows its GPUs, CUDA ecosystem, AI infrastructure and business decisions.
Reviewed 19 October 2026. Dates retain the precision of the source; retrospective disclosures are identified in the event. Fiscal-year, quarterly and Data Center sales are labelled separately; none is presented as ARR.
Revenue, funding, product launches and major company events, newest first. Expand the earlier milestones for more history.
Quarterly revenue grows 106% year over year; Data Center contributes $89.0B, up 117%. These are quarterly sales, not ARR.
Source: NVIDIANVIDIA reports partner deployments of its new platform, extending the hardware roadmap beyond Blackwell.
Source: NVIDIAEarlier revenue, financing and company milestones.
Full-year revenue increases 65%; Data Center revenue reaches $193.7B. Fiscal 2026 ends in January 2026.
Source: NVIDIAThe companies sign a letter of intent. Planned capacity and contemplated investment are not recorded as delivered capacity or revenue.
Source: OpenAI / NVIDIAAnnual sales grow 114%; fourth-quarter Data Center revenue is $35.6B, showing the scale of the generative-AI infrastructure expansion.
Source: NVIDIAThe new GPU platform integrates compute, networking and software for large-scale model training and inference.
Source: NVIDIAHigh-performance networking becomes a larger part of NVIDIA’s data-center platform alongside GPUs.
Source: NVIDIAThe integrated GPU server combines accelerators, interconnects and optimized software for deep-learning development.
Source: NVIDIAThe ImageNet breakthrough uses NVIDIA GPUs, marking an important step in the shift from graphics hardware to AI computing.
Source: NVIDIA retrospectiveThe programming platform opens GPU acceleration to general-purpose computing, becoming a foundation for later deep-learning workloads.
Source: NVIDIANVIDIA’s investor FAQ dates its public-market debut to January 22, before its later expansion into general-purpose GPU computing.
Source: NVIDIAThe company starts in computer graphics before expanding into accelerated computing and AI infrastructure.
Source: NVIDIABriefs, articles and relevant sections, newest first. Explore older coverage below.
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