Physical AI Takes the Wheel: How the World’s Robotaxi Leaders Are Building With NVIDIA Technologies

NVIDIA's modular robotaxi stack powers every major commercial-scale robotaxi program operating today, spanning AI training, simulation and in-vehicle computing, according to the company. The global robotaxi market is projected to reach $400 billion by 2035 with over 6 million commercial vehicles in operation, per Goldman Sachs. NVIDIA's three-computer solution pairs DGX training systems and the Alpamayo open reasoning vision language action (VLA) models with Omniverse NuRec and Cosmos simulation running on RTX PRO Servers.

The global robotaxi https://www.nvidia.com/en-us/glossary/robotaxi/ market — physical AI’s https://www.nvidia.com/en-us/glossary/generative-physical-ai/ first commercial breakthrough — is projected to reach $400 billion by 2035 https://www.goldmansachs.com/insights/articles/robotaxis-to-become-a-400-billion-dollar-market-in-2035 , with over 6 million commercial vehicles in operation as driverless fleets are already moving people through some of the world’s busiest and most complex streets. Deploying a driverless vehicle is one challenge. Scaling a fleet is a next-level computing challenge; it means delivering the same safe, reliable performance across thousands of vehicles. Meeting those demands requires enormous amounts of compute across the robotaxi development lifecycle, from preparing and training AI models to simulating and validating driving behavior, as well as real-time processing in the vehicle. NVIDIA provides an open platform for AI training https://www.nvidia.com/en-us/solutions/autonomous-vehicles/ai-training/ , simulation https://www.nvidia.com/en-us/solutions/autonomous-vehicles/simulation/ and safety validation https://www.nvidia.com/en-us/ai-trust-center/halos/autonomous-vehicles/ , with libraries, software development kits, workflows and models that developers can use alongside their own technology stacks. Every major robotaxi program operating at commercial scale today is running on NVIDIA’s modular stack, spanning AI training, simulation, in-vehicle computing https://www.nvidia.com/en-us/solutions/autonomous-vehicles/in-vehicle-computing/ — or a combination of the three — to develop and deploy fleets at scale. What Is a Robotaxi Technology Stack? A robotaxi technology stack is the end-to-end set of technologies used to develop, validate and deploy autonomous vehicles AVs — from data and AI model training to simulation, safety validation and real-time in-vehicle computing. NVIDIA’s robotaxi and AV platform https://www.nvidia.com/en-us/solutions/autonomous-vehicles/ brings these capabilities together in a three-computer solution: the model training computer, simulation and validation computer, and in-vehicle computer. 1. Training Computer: NVIDIA DGX Robotaxi intelligence advances as programs turn growing volumes of fleet data into increasingly capable models. Driving models can be trained on NVIDIA DGX https://www.nvidia.com/en-us/data-center/dgx-platform/ systems. The NVIDIA Alpamayo https://www.nvidia.com/en-us/solutions/autonomous-vehicles/alpamayo/ portfolio of open reasoning vision language action VLA models, simulation frameworks and physical AI datasets gives developers building blocks they can adapt to their own data, requirements and technology stacks. Its reasoning models help address long-tail AV challenges by breaking complex driving situations into smaller steps, reasoning through each one and selecting the safest trajectory. NVIDIA also provides physical AI datasets, reinforcement learning blueprints and recipes for post-training and distillation, helping developers optimize models for their target vehicles. 2. Simulation and Validation Computer: NVIDIA Omniverse and Cosmos on NVIDIA RTX PRO Robotaxi programs can’t rely on physical miles alone to capture rare, long-tail driving scenarios. NVIDIA Omniverse NuRec https://docs.nvidia.com/nurec/ models reconstruct real-world driving scenarios from sensor data, while NVIDIA Cosmos world foundation models generate physically based variations of them, enabling developers to turn thousands of real-world corner cases into millions of combinations of driving behavior, traffic, weather, lighting and sensor conditions. Running on NVIDIA RTX PRO Servers https://www.nvidia.com/en-us/data-center/products/rtx-pro-server/ , NVIDIA Omniverse and Cosmos support closed-loop simulation and validation. The NVIDIA AlpaSim simulation framework extends the workflow for training and evaluating reasoning-based autonomous-driving models, helping developers identify weaknesses before deployment. 3. In-Vehicle Computer and Sensor Architecture: NVIDIA DRIVE Hyperion With DRIVE AGX NVIDIA DRIVE Hyperion https://www.nvidia.com/en-us/solutions/autonomous-vehicles/drive-hyperion/ is NVIDIA’s modular in-vehicle compute and sensor reference architecture for level-4-ready robotaxis. DRIVE Hyperion 10 pairs dual NVIDIA DRIVE AGX Thor systems-on-a-chip, built on the NVIDIA Blackwell platform https://www.nvidia.com/en-us/data-center/technologies/blackwell-architecture/ , with 14 high-definition cameras, nine radars, three lidars and 12 ultrasonics for real-time, 360-degree sensor fusion. Its redundant compute and sensing design supports fail-operational driving if a sensor or compute component fails. The dual DRIVE AGX Thor https://www.nvidia.com/en-us/solutions/autonomous-vehicles/in-vehicle-computing/ hardware is designed to run modern AI workloads — including VLA models — for perception, reasoning, path planning and driving actions. NVIDIA Halos https://www.nvidia.com/en-sg/ai-trust-center/halos/autonomous-vehicles/ provides a production-ready safety foundation through Halos OS, and a broader validation and certification framework spanning independent inspection, system validation, large-scale simulation and continuous testing from cloud to car. Robotaxi Leaders Adopting NVIDIA’s Robotaxi Technology Stack NVIDIA’s robotaxi ecosystem spans every region where commercial robotaxi services are emerging today: Asia, Europe, the Middle East and North America. Across these markets, mobility providers, AV developers and automakers are adopting NVIDIA’s three-computer architecture to train AI models, simulate and validate driving behavior, and deploy autonomous vehicles at scale. Scaling Robotaxi Services Globally - Uber https://investor.uber.com/news-events/news/press-release-details/2026/NVIDIA-to-Launch-L4-Software-Driven-Robotaxis-on-Uber-Across-28-Cities-by-2028/default.aspx is scaling its fleet of NVIDIA DRIVE Hyperion, with plans to reach 28 cities by 2028. Uber and NVIDIA are also building a robotaxi AI data factory on NVIDIA Cosmos to curate fleet driving data for rare scenarios. Together, Uber and NVIDIA are collaborating with Autobrains, Avride, Lucid, May Mobility, Mercedes-Benz, Momenta, Nissan, Nuro, Pony.ai, Stellantis, Waabi, Wayve, WeRide and Zoox to bring NVIDIA-powered robotaxi services to the Uber platform. - May Mobility https://investor.nvidia.com/news/press-release-details/2025/NVIDIA-Makes-the-World-Robotaxi-Ready-With-Uber-Partnership-to-Support-Global-Expansion/default.aspx is planning to operate autonomous ride-hailing services through Uber’s network, while developing its software stack on the NVIDIA DRIVE platform. - Bolt https://bolt.eu/en/blog/nvidia-bolt-announcement/ uses NVIDIA technologies to develop and scale AVs across Europe. - Lyft https://investor.lyft.com/news-events-presentations/press-releases/detail/193/lyft-to-make-rides-smarter-and-more-efficient-through-agentic-ai-accelerate-av-future-with-nvidia-drive-hyperion plans to use NVIDIA DRIVE Hyperion as a reference architecture for future autonomous fleets. May Mobility vehicles are also currently operating on Lyft’s network in Atlanta, powered by NVIDIA DRIVE. - Through its partnership with Grab , WeRide https://ir.weride.ai/news-releases/news-release-details/weride-showcases-robotaxi-gxr-powered-nvidia-drive-hyperion plans to bring its DRIVE Hyperion- and DRIVE AGX Thor-based GXR to key markets across Southeast Asia. Building Robotaxi Intelligence Behind these services, AV developers are using NVIDIA accelerated computing, simulation and in-vehicle platforms to build the intelligence that operators and automakers deploy. - Wayve https://wayve.ai/press/wayve-nissan-robotaxi-gtc/ , Nissan and Uber are developing a global robotaxi program using a prototype vehicle that combines Nissan’s vehicle engineering, Wayve’s embodied AI and the NVIDIA DRIVE Hyperion platform. - Autobrains https://autobrains.ai/autobrains-and-uber-launch-agentic-ai-robotaxi-program-in-munich-built-on-nvidia-drive-hyperion/ is developing robotaxi programs with Uber in Munich and VinFast https://vinfastauto.us/newsroom/press-release/vinfast-and-autobrains-launch-first-agentic-ai-l4-program-for-southeast-asia in Southeast Asia, built on NVIDIA DRIVE Hyperion and enabled by Autobrains’ Agentic AI technology. - Zoox https://blogs.nvidia.com/blog/nvidia-zoox-autonomous-ride-hailing/ uses NVIDIA DRIVE for in-vehicle computing and cloud-based training and simulation. - Momenta https://nvidianews.nvidia.com/news/nvidia-uber-robotaxi is developing its software stack based on NVIDIA DRIVE AGX running on DriveOS. - Pony.ai https://ir.pony.ai/news-releases/news-release-details/pony-ai-inc-announces-new-generation-autonomous-driving-domain developed its new-generation autonomous-driving domain controller with NVIDIA DRIVE Hyperion and DRIVE AGX Thor. - Tensor https://www.tensor.auto/press/lyft2025 is developing its level 4 Robocar with eight NVIDIA DRIVE AGX Thor systems-on-a-chip in its in-vehicle supercomputer. - Waabi https://waabi.ai/insights/waabi-secures-1-billion-in-new-funding-to-lead-physical-ai-revolution expands into the robotaxi market through a deployment collaboration with Uber ; its Waabi Driver platform is built on NVIDIA DRIVE AGX Thor. - TIER IV and Isuzu https://www.isuzu-global.com/en/newsroom/20260317 1.html are deploying level 4 autonomous buses built on NVIDIA DRIVE Hyperion and DRIVE AGX Thor. - Lenovo https://news.lenovo.com/pressroom/press-releases/lenovo-works-with-swm-to-develop-next-generation-robotaxi-on-nvidia-drive-agx-thor/ is supplying its NVIDIA DRIVE AGX Thor-based AD1 level 4 domain controller for a next-generation robotaxi program with SWM . - DeepRoute.ai https://www.prnewswire.com/news-releases/deeprouteai-presents-40b-vision-language-action-foundation-model-at-nvidia-gtc-2026-accelerating-autonomous-driving-at-scale-302716046.html is developing a new generation of robotaxis built on the NVIDIA DRIVE Hyperion platform with DRIVE AGX Thor. Bringing Robotaxis Into Production As these systems move from development into production, automakers are integrating NVIDIA technology into autonomous and robotaxi-ready vehicle programs. - Tesla trains its autonomous-driving neural networks on NVIDIA supercomputers. - Mercedes-Benz https://media.mbusa.com/releases/release-cfaf7728c8957661f23433449e08d179-mercedes-benz-accelerates-future-robotaxi-ecosystem-and-collaborates-with-industry-leading-partners and NVIDIA are collaborating with Uber to develop a robotaxi ecosystem based on the new S-Class, built on the NVIDIA DRIVE Hyperion architecture, full-stack NVIDIA DRIVE AV L4 software, and NVIDIA Alpamayo open AI models, simulation tools and datasets to support reasoning-based, safety-first autonomy. - Stellantis, Wayve and Uber are collaborating to develop and deploy L4 driverless mobility services, leveraging NVIDIA DRIVE Hyperion and AI computing technologies. - Lucid https://ir.lucidmotors.com/news-releases/news-release-details/lucid-nuro-and-uber-unveil-global-robotaxi-ces-announce?utm source=chatgpt.com , Nuro and Uber are developing a global robotaxi service using NVIDIA DRIVE AGX Thor, part of the DRIVE Hyperion platform. - Hyundai Motor https://nvidianews.nvidia.com/news/hyundai-motor-kia-autonomous-driving and Kia are expanding their collaboration with NVIDIA to develop data-driven autonomous-driving systems built on NVIDIA DRIVE Hyperion. NVIDIA will also explore expanded collaboration with Hyundai Motor Group’s joint venture, Motional , to advance level 4 robotaxi services. - Geely https://www.globenewswire.com/news-release/2026/03/18/3258289/0/en/geely-expands-strategic-partnership-with-nvidia-across-physical-enterprise-and-industrial-ai.html , alongside its ecosystem partners, plans to develop and commercialize robotaxis using DRIVE Hyperion. - Zeekr https://www.prnewswire.com/news-releases/zeekr-announces-january-2025-delivery-update-302365781.html , a Geely Auto Group brand, has adopted DRIVE AGX Thor for a centralized domain controller. From cloud to car, nearly every layer of the robotaxi platform is being developed on NVIDIA accelerated computing. Explore NVIDIA’s complete platform for robotaxi development .