ByteDance Nears MediaTek Deal for AI Chips
Barred from Nvidia's best chips, ByteDance is in advanced talks to buy custom AI chips from MediaTek, designed to stay under US export limits.
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At a glance
NVIDIA develops accelerated computing hardware and software. Coverage follows its GPUs, CUDA ecosystem, AI infrastructure and business decisions.
- Focus
- GPUs; CUDA; AI systems
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- NVIDIA
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.
Company milestones
Revenue, funding, product launches and major company events, newest first. Expand the earlier milestones for more history.
Q2 FY2027 revenue reaches $96.2B
Quarterly revenue grows 106% year over year; Data Center contributes $89.0B, up 117%. These are quarterly sales, not ARR.
Source: NVIDIAVera Rubin ramps into full production
NVIDIA reports partner deployments of its new platform, extending the hardware roadmap beyond Blackwell.
Source: NVIDIA
Show earlier milestonesHide earlier milestones2026–1993 · 10 milestones
Earlier revenue, financing and company milestones.
FY2026 revenue rises to $215.9B
Full-year revenue increases 65%; Data Center revenue reaches $193.7B. Fiscal 2026 ends in January 2026.
Source: NVIDIAAnnounces a 10GW OpenAI infrastructure plan
The companies sign a letter of intent. Planned capacity and contemplated investment are not recorded as delivered capacity or revenue.
Source: OpenAI / NVIDIAFY2025 revenue reaches $130.5B
Annual sales grow 114%; fourth-quarter Data Center revenue is $35.6B, showing the scale of the generative-AI infrastructure expansion.
Source: NVIDIAIntroduces Blackwell
The new GPU platform integrates compute, networking and software for large-scale model training and inference.
Source: NVIDIACompletes the $7B Mellanox acquisition
High-performance networking becomes a larger part of NVIDIA’s data-center platform alongside GPUs.
Source: NVIDIAIntroduces the DGX-1 AI system
The integrated GPU server combines accelerators, interconnects and optimized software for deep-learning development.
Source: NVIDIAAlexNet demonstrates GPU-trained deep learning
The ImageNet breakthrough uses NVIDIA GPUs, marking an important step in the shift from graphics hardware to AI computing.
Source: NVIDIA retrospectiveIntroduces CUDA
The programming platform opens GPU acceleration to general-purpose computing, becoming a foundation for later deep-learning workloads.
Source: NVIDIAGoes public
NVIDIA’s investor FAQ dates its public-market debut to January 22, before its later expansion into general-purpose GPU computing.
Source: NVIDIANVIDIA is founded
The company starts in computer graphics before expanding into accelerated computing and AI infrastructure.
Source: NVIDIA
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