This is Part 3 of a 3-part breakdown of the GTC 2026 keynote. Start with Part 1: Overview & Context or go back to Part 2: Intro, Analytics, CUDA-X & Inference. The single-page version is also available.

Previously in Parts 1 & 2: After setting the scene at GTC, Jensen spent the first half of the keynote celebrating CUDA’s 20-year flywheel, making the case for NVIDIA’s role in accelerating enterprise analytics (with partnerships from IBM, Dell, and Google Cloud), reviewing the CUDA-X library ecosystem, and laying out the economics of the AI inference boom, framing the $1T infrastructure wave ahead and how GB300 NVL72 became the inference king on tokens-per-watt.

Summary of Part 3 sections

The second half of the keynote covered the following sections:

Duration Section
38 min Full Vera Rubin hardware stack + DSX platform — Showing Vera Rubin + Groq hardware and explaining how they improve the throughput vs. interactivity performance curves
19 min OpenClaw, NemoClaw, Open Model Coalition — Praising the explosive growth of OpenClaw as a revolutionary moment, and announcing NVIDIA’s enterprise reference NemoClaw and the open model coalition
14 min Robotics, Physical AI, & recap — Describing the evolution of physical AI and the robotic landscape and recaping with a specially generated music video

Full Vera Rubin hardware stack — GPU, NVLink, Rubin Ultra, and Spectrum-X Groq LPX + DSX platform for AI factory optimization (38min)

A Decade of AI Infrastructure Innovation: From DGX-1 to Vera Rubin · 3:30min
Jensen narrates NVIDIA's decade of data center infrastructure innovation:
2016
DGX-1 —packages 8 Pascal GPUs, first supercomputer built for deep learning, one delivered to openAI that year
2017
Volta — introduces NVLink 2 switch, GPU-to-GPU interconnect inside nodes
2019
Mellanox acquisition — allows the data center to become a single unit of computing
2020
Ampere / DGX A100 SuperPOD — brings scale-up via NVLink 3, scale-out via ConnectX-6 InfiniBand
2022
Hopper — supports FP8 Transformer Engine for Gen AI, NVLink 4, ConnectX-7
2024
Blackwell / NVL72 — achieves 130 TB/s bandwidth and a deeper rack-level co-design for top performance
2026
Vera Rubin — built for agentic AI · 35× throughput/MW · 40M× cumulative compute over the decade
NVIDIA Vera Rubin · 2:27min
Jensen introduces the Vera Rubin hardware on stage
NVIDIA Vera Rubin, NVLink and Groq · 1:36min
He makes some interesting observations: with the recent tray designs, installation time falls down from 2 days to 2 hours. Also cooling is done with hot water at 45 degrees.
Spectrum-X Switch, Co-Packaged Optics, Vera and BlueField-4 · 2:09min
discusses the 8 grok 3rd gen tray which is in production and shows the Spectrum Co-packaged optics switch. Vera brings 2x performance per watt. ConnectX9 and storage platform are powered by Vera CPU.
Rubin Ultra · 2:03min
Jensen also shows VR Ultra and the new Kyber rack that can connect 144 gpus that now slide vertically into the rack. He also shows the new NVLink tray design that sits behind, also vertically.
Inference Performance and Efficiency Drive Company Results · 9:35min
Jensen's main message to CEOs is how they will need to evaluate their company's usage of tokens, and study the tradeoff between throughput (as Token per Sec per MW) vs Interactivity (as token per second per user). Input and output Context length are growing and usage depends on use case. Jensen shows a graph partitionned by kind of model at different prices and how nvidia's chips performs on this tradeoff. The value of Ultra lays enabling bigger more interactive models with better energy efficiencies. GB NVL72 has increased the medium tier by 35x and Vera rubin will increase high tier by 3x and increased premium tier by 10x. Rubin + Groq LPX increase most valuable tier by 35x. Ultra enables even better interactivity.
Uniting Processors of Extreme Performances · 3:36min
Jensen delves into the performance of Groq, which has high SRAM capacity (500MB) at very high throughput (150TB). This complements Rubin's 288GB of HBM4 memory at 22TB/s by providing statically compiled compute primitives specially used for the decode Feed Forward phase of AI inference, and helps achieve very low latency for token generation.
NVIDIA Groq 3 LPX · 0:38min
Jensen shows Groq LPX manufactured by samsung and say he expects to ship by Q3 this year.
Announcing NVIDIA Launch Partners · 1:56min
shows all the AI labs, cloud, and OEM/ODM that will launch Vera Rubin. Expects production in the 1000s per week. also shows launch partners for Vera CPU and BlueField storage systems
NVIDIA Vera Rubin: 7 Chips – 5 Rack Systems · 1:02min
Jensen shows how much progress was made by comparing x86 hopper generation to Vera Rubin GiGaWatt factory. VR can generate 350x more tokens per seconds than Hopper thanks to 35x more scale up BW per Rack (at 288TB/s) and with half as many GPUs.
NVIDIA Extreme Co-Design Delivering X-Factors Every Year · 3:37min
shows the roadmap to 2028 with Feynman. Oberon will enable scale up in both copper and optical to support NVL576 racks (Kyber) and then NVL1152 for Feynman with Kyber.
NVIDIA DSX AI Factory Platform · 2:10min
Jensen describes the importance of the NVIDIA Omniverse solution to help design GW factory digital twins and reach max performance at lowest possible energy usage. He talks about tools for simulation such as DSX Sim, DSX exchange, DSX flex power management and DSX Max Q for dynamic power adjustment in the data center.
How AI Factories Maximize Tokens, Power, and Profit With NVIDIA DSX · 3:25min
The video summarizes all the components of the DSX AI factory platform
Space-1 Vera Rubin Module · 0:43min
Jensen briefly mentions NVIDIA's foray in space with Space-1 Vera Rubin module and mentions the challenge of cooling in space.

OpenClaw, NemoClaw, Open Model Coalition (19min)

NemoClaw for OpenClaw · 1:24min
Jensen is very excited about OpenClaw, the most popular open source in history, with the fastest project to get the most stars in github
OpenClaw: The ChatGPT Moment for Long-Running, Autonomous Agents · 9:14min
He shows how openclaw grew as a project to 340k stars on GitHub since the end of january 2026. It is the operating system of agents and every enterprise will soon need an OpenClaw strategy.
NVIDIA Nemotron and Open Models · 0:28min
Jensen announces new models in Nvidia's open foundation model families: bioNemo for biomedical AI, earth-2 for Ai physics, Nemotron for Agentic AI, Cosmos for Physical AI, GROOT for Robotics, and Alpamayo for Autonomous Vehicles.
How NVIDIA Open Models Power Every Industry's AI · 4:17min
The video shows models from each of the Nvidia families. They are world class, doing well on benchmarks. Shows nemotron-3-super-120b as #4 on best open model for openClaw. Nemotron 3 ultra.
Announcing Global AI Leaders Join NVIDIA Nemotron Coalition · 2:57min
Jensen announces the NVIDIA Nemotron Coalition1 aimed at accelerating the co-development of open AI frontier models with partners Black Forest Labs, Cursor, LangChain, Mistral AI, Perplexity, Reflection AI, Sarvam and Thinking Machines Lab
Announcing NVIDIA NemoClaw Reference OpenClaw · 0:39min
Jensen says the openClaw event cannot be understated and is as big as linux and html. In response, Nvidia is releasing NemoClaw, a reference enterprise-ready solution to secure openClaw deployments inside enterprises.

Robotics, Physical AI, & recap (14min)

Physical AI and Robotics · 3:11min
Jensen talks robots, mentions there are 110 robots at GTC, announces 4 new auto partners: BYD, Hyundai, Nissan, and Geely are joining Mercedes, Toyota, and GM to build robotaxi technologies. Jensen also announces a partnership with Uber to launch a large fleet of autonomous vehicles for 2027 on the NVIDIA DRIVE AV stack2
The Age of Physical AI and Robotics · 4:27min
This video shows how autonomous cars have been improving thanks to NVIDIA's and partner ecosystem.
Olaf Takes the Stage With Jensen Huang · 1:55min
Jensen welcomes the only guest at the keynote. Last year it was a Star Wars inspired robot "blue", this year it is Olaf from Frozen
Official Keynote Closing Video · 4:02min
The Keynote ends with a generated video recapping the keynote with a jensen emoticon playing harmonica in the forest, surrounded by a band of robots playing instruments, a bit silly for my tast but again showcasing the power of the tools

Full keynote is available here and the slides here.


← Part 2: Intro, Analytics, CUDA-X & Inference

References

  1. NVIDIA Launches Nemotron Coalition of Leading Global AI Labs to Advance Open Frontier Models — nvidianews.nvidia.com
  2. NVIDIA DRIVE Hyperion Achieves Level 4 Autonomy with Uber Partnership — nvidianews.nvidia.com