Figure AI Secures 100,000 NVIDIA GPUs in $6 Billion Deal for Next-Generation Humanoid Robots

US: 100,000 GPUs to power Figure's next-generation humanoid robots

U.S. robotics firm Figure has signed a strategic partnership with UK-based Nscale to secure large-scale computing capacity for training its next generation of humanoid robot AI models. Under the agreement, Nscale will deploy up to 100,000 GPUs based on NVIDIA's Vera Rubin platform for Figure's AI development. The partnership aims to address the growing data and compute demands of training models for general-purpose robotics. Figure says the collaboration will provide the computing infrastructure needed to scale its physical intelligence efforts and advance the capabilities of its humanoid robots. The new partnership aims to secure large-scale computing infrastructure for training the artificial intelligence systems that power its humanoid robots. The partnership will support deployment of up to 100,000 GPUs based on NVIDIA's Vera Rubin platform, with initial deployment targeted for the second half of 2027 in Barstow, Texas. The agreement represents an initial $3.5 billion commitment for computing capacity, with plans to expand the investment to more than $6 billion. Nscale will also make a strategic investment in Figure, while both companies will explore using humanoid robots to support and scale Nscale's supply chain operations. The computing infrastructure is being developed to address the growing demands of training Helix, Figure's AI system for humanoid robots. As the company expands its training datasets, the growing volume of physical-world data requires substantially more computational capacity to process and train increasingly capable models. The partnership is designed to create a complete infrastructure pipeline for physical AI, combining large-scale model training with simulation and deployment. It will use NVIDIA's computing hardware and robotics simulation technologies to train, test, and deploy AI models on humanoid robots, providing the computational foundation needed to advance general-purpose robotic systems. "Nscale and Figure have activated the robotics flywheel: training Figure's models on NVIDIA Vera Rubin through Nscale's AI cloud, validating them in NVIDIA Isaac Sim, and deploying them on NVIDIA GPUs in Figure's robots. This is the physical AI flywheel that will accelerate the path from models to robots in the world," said Brett Adcock, Founder and CEO, Figure, in a statement. Recently, Figure announced that it is scaling Index - a large, continuously expanding dataset of real-world human activity. The platform has surpassed 264,000 downloads across 108 countries and has more than 44,000 weekly active users, with contributors uploading enough video to generate 30 minutes of data every second. According to Figure, Index is designed to capture the diversity and complexity of physical tasks needed to train general-purpose robotic intelligence. Its dataset spans household and workplace activities, covering hundreds of tasks, thousands of objects, and numerous environments, allowing AI models to learn from varied human behavior rather than highly controlled demonstrations. Figure has built its own data pipeline after conventional data suppliers failed to meet the required scale, diversity, and quality. The system automatically filters incoming videos for technical, visual, and semantic quality before human reviewers check samples for fraud and other issues. Videos are also processed for similarity, with duplicate or highly repetitive data removed to preserve dataset diversity. The remaining data is rebalanced according to task requirements and behavioral variation before hierarchical text descriptions are generated for training. The resulting data is intended to improve Helix, Figure's AI system, by giving it broader exposure to real-world interactions and long-tail physical tasks. Figure has paid $15 million to contributors so far and plans to scale data and compute spending substantially. The broader goal is to create the training infrastructure needed to move humanoid robots from controlled demonstrations toward reliable, general-purpose physical work.

Nvidia's Next AI Customer Isn't Building Chatbots - NVIDIA (NASDAQ:NVDA)

The biggest new customer for Nvidia Corp's (NASDAQ:NVDA) next-generation AI chips isn't another chatbot maker or cloud giant. It's a humanoid robotics company. Figure AI's decision to secure access to up to 100,000 Nvidia Vera Rubin GPUs signals that the next wave of AI infrastructure spending may come from teaching robots how to understand and interact with the physical world -- not just generate text. Beyond Chatbots Figure this week announced a strategic partnership with AI cloud provider Nscale to deploy up to 100,000 GPUs built on Nvidia's Vera Rubin platform. The agreement includes an initial $3.5 billion compute commitment, with plans to scale beyond $6 billion, as Figure trains the AI models powering its humanoid robots. Deployments are expected to begin in the second half of 2027. While the headline numbers are eye-catching, the more important takeaway is why Figure needs that much computing power. The company said it is increasingly constrained not by hardware manufacturing but by the data and compute required to train Helix, its robotics foundation model. Figure also pointed to Index, its recently launched data platform, which it says is generating 35 minutes of training data every second. "Data alone cannot solve this problem," the company said. "Scaling physical intelligence will require an immense amount of compute." Long Ideas Figure AI's 100K Robot Plan Backed by Nvidia, OpenAI Figure AI, backed by Nvidia, OpenAI and Jeff Bezos, targets 100,000 humanoid robots in 4 years - a shift to real-world AI deployment. 2 min read Read this article The Rise of Physical AI For Nvidia, the announcement underscores how demand for AI infrastructure is broadening beyond large language models. Humanoid robots represent a fundamentally different AI challenge. Instead of answering questions or writing code, they must perceive the physical world, understand their surroundings and safely perform real-world tasks. That requires continuous training on massive amounts of visual and behavioral data. Nvidia CEO Jensen Huang described the partnership as activating a "robotics flywheel." In his words, Figure's AI models will train on Nvidia's Vera Rubin platform through Nscale's cloud, validate in Nvidia Isaac Sim, and ultimately deploy on Nvidia-powered robots. He called it "the physical AI flywheel" that will accelerate the path from AI models to real-world robots. That framing matters because it positions robotics as a new long-term demand driver for Nvidia's AI ecosystem rather than simply another buyer of GPUs. What Investors Should Watch Investors have largely viewed Nvidia's growth through the lens of hyperscalers and generative AI companies racing to build ever-larger language models. Figure's latest commitment suggests another market is beginning to emerge. If humanoid robotics scales as companies such as Figure envision, demand for AI infrastructure may increasingly come from training machines to operate in the physical world. For Nvidia, that could broaden its customer base beyond cloud providers and AI labs, reinforcing Huang's long-held view that physical AI represents the industry's next frontier. The Figure partnership may be one of the clearest signs yet that the shift is already underway. Tech Tesla Isn't Leading Humanoid Robotics -- Figure AI Is RoboStrategy CEO Andrew Kang says Figure AI -- not Tesla -- currently leads U.S. humanoid robotics based on commercial production progress. 2 min read Read this article Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.