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At CES 2026<\/a>, Nvidia launched Alpamayo, a new family of open-source AI models, simulation tools, and datasets for training physical robots and vehicles that are designed to help usher autonomous vehicles reason through complex driving situations.<\/p>\n \u201cThe ChatGPT moment for physical AI is here \u2013 when machines begin to understand, reason, and act in the real world,\u201d Nvidia CEO Jensen Huang said in a statement. \u201cAlpamayo brings reasoning to autonomous vehicles, allowing them to think through rare scenarios, drive safely in complex environments, and explain their driving decisions.\u201d\u00a0<\/p>\n At the core of Nvidia\u2019s new family is Alpamayo 1, a 10-billion-parameter chain-of-thought, reason-based vision language action (VLA) model that allows an AV to think more like a human so it can solve complex edge cases \u2013 like how to navigate a traffic light outage at a busy intersection \u2013 without previous experience.\u00a0<\/p>\n \u201cIt does this by breaking down problems into steps, reasoning through every possibility, and then selecting the safest path,\u201d Ali Kani, Nvidia\u2019s vice president of automotive, said Monday during a press briefing.\u00a0<\/p>\n Alpamayo 1\u2019s underlying code is available on Hugging Face. Developers can fine-tune Alpamayo into smaller, faster versions for vehicle development, use it to train simpler driving systems, or build tools on top of it like auto-labeling systems that automatically tag video data or evaluators that check if a car made a smart decision.\u00a0<\/p>\n \u201cThey can also use Cosmos to generate synthetic data and then train and test their Alpamayo-based AV application on the combination of the real and synthetic dataset,\u201d Kani said. Cosmos<\/a> is Nvidia\u2019s brand of generative world models<\/a>, AI systems that create a representation of a physical environment so they can make predictions and take actions.\u00a0<\/p>\n As part of the Alpamayo rollout, Nvidia is also releasing an open dataset with more than 1,700 hours of driving data collected across a range of geographies and conditions, covering rare and complex real-world scenarios. The company is additionally launching AlpaSim, an open-source simulation framework for validating autonomous driving systems. Available on GitHub, AlpaSim is designed to recreate real-world driving conditions, from sensors to traffic, so developers can safely test systems at scale.<\/p>\n Techcrunch event<\/p>\n