Uber and Nvidia Forge Ambitious 100,000‑Robotaxi Partnership

In a landmark development for the future of transportation, Uber has announced a strategic partnership with Nvidia to deploy up to 100,000 autonomous robotaxis, starting in 2027. This bold move positions Uber at the forefront of the race to integrate Level 4 self-driving technology into commercial ride-hailing. Leveraging Nvidia’s latest AI-driven hardware and software platforms, the initiative is set to transform how urban mobility is managed and scaled globally.

The Robotaxi Revolution

• Central to the partnership is Nvidia’s newly unveiled DRIVE AGX Hyperion 10 platform.
• This system equips vehicles with high-performance computing, sensors, and software capable of full self-driving in controlled environments, known as Level 4 autonomy.
• This platform allows auto manufacturers to integrate autonomous capabilities during production, ensuring consistency, safety, and efficiency across fleets.
• It also supports the rapid training and simulation of driving scenarios using real-world and synthetic data, significantly reducing development cycles.

Uber’s Role

While Nvidia supplies the AI infrastructure, Uber will manage the end-to-end operations of the autonomous fleet. This includes responsibilities such as,

• Remote monitoring
• Charging and cleaning
• Maintenance
• Customer service support

Uber aims to enhance its mobility network by transitioning from traditional human-driven rides to a hybrid system where autonomous vehicles complement human drivers. This will not only diversify its service but also reduce dependency on gig workers in the long term.

Stellantis and Global Deployment

• As part of the partnership, Stellantis will deliver at least 5,000 Nvidia-powered robotaxis, expected to enter production in 2028.
• Initial rollout will take place in the United States, with global operations expanding based on regulatory approvals and pilot program results.
• Production support will come from electronics giant Foxconn, ensuring systems integration and hardware readiness.
• This collaboration marks a critical step in achieving economies of scale for mass robotaxi deployment.

Boosting AI Development Through Data

Uber is also working with Nvidia to build a robotaxi data factory, gathering over 3 million hours of autonomous driving data. This data will be used to,

• Train and validate AI driving models
• Simulate real-world traffic and weather conditions
• Improve safety and reliability of autonomous systems
• By creating a continuous loop of data ingestion, scenario mining, and large-scale training, this facility aims to accelerate the timeline to profitability for autonomous fleets.

Benefits and Strategic Impact

Deploying 100,000 robotaxis could significantly lower the cost-per-mile for ride-hailing services. Automation reduces operational expenses tied to human labor, making autonomous rides more affordable and accessible over time.

Moreover, by managing a fleet at this scale, Uber can ensure,

• Standardized safety protocols
• Optimized routing and dispatching
• Better service availability in high-demand zones

These benefits can help Uber gain a competitive edge over rivals in both traditional ride-hailing and emerging autonomous services.

Key Static Facts

• Partnership announced: October 2025
• Target deployment: Begin in 2027
• Full production (Stellantis): From 2028
• Robotaxi fleet goal: 100,000 vehicles
• Initial supplier: Stellantis with hardware integration from Foxconn
• Technology used: Nvidia DRIVE AGX Hyperion 10
• Autonomy level targeted: Level 4 (self-driving under specific conditions)
• Pilot cities include: Austin, Atlanta, Abu Dhabi, and others
• Current autonomous partners: Waymo, Nuro, Pony.ai, May Mobility, WeRide, Momenta