Faraday Future Unveils Nine New Robots Across Humanoid and Quadruped Lines

On September 21, 2026, Faraday Future announced nine embodied AI robot configurations across five models, covering both humanoid and quadruped/wheeled-legged forms. According to the company, its EAI Robot World portfolio now covers humanoid, quadruped, and mobile manipulator robots, spanning 5 product series, 11 models, and 24 products. This numerical framing is worth noting: nine 'configurations' and five 'models' are not at the same level—the former is more like variants in compute, hands, or payload on the same hardware platform.

The price range is the hardest information in this list. The Master Mini humanoid robot starts at $9,990, with three versions offering 48, 117, and 200 TOPS of compute respectively, and a top price of $17,990; the All-New Futurist full-size humanoid starts at $89,900 for the standard version and $129,900 for the Ultra version; the Aegis Hyper industrial quadruped starts at $137,900; the Aegis Mega wheeled-legged robot starts at $74,990; and the Aegis Classic Ultra-W is priced at $12,990. From an educational model under $10,000 to an industrial model near $140,000, the span is more than thirteenfold, indicating this is not a product for a single market but an attempt to cover classrooms, laboratories, and hazardous work sites with one product line.

The hardware specifications provided by the company are quite specific. The All-New Futurist has 51 active degrees of freedom, which can reach 71 with upgraded dexterous hands; a 1,152 Wh dual-battery system supports about eight hours of operation under standard conditions and supports autonomous charging; the Ultra version uses Nvidia Jetson Thor with 700 TOPS of compute. The Aegis Mega has a maximum payload of 50 kg, can climb 25 cm steps and clear a single obstacle up to 80 cm high, and runs at least five hours unloaded using hot-swappable dual batteries. The Aegis Classic Ultra-W weighs about 22 kg and supports multi-robot collaboration and simulation training.

But the key promise of 'deliverable' currently rests only on the company's own statements. Reports say Faraday Future states all new products can be purchased and delivered through FF.com, Amazon, and RobotShop, and offers three configurations: standalone unit, standalone unit plus skill package, and standalone unit plus full application solution. A distinction is needed here: product specifications and pricing are company-published product information, while 'available for sale and delivery' is a company claim, with no independent source verifying actual shipping status, production capacity, or delivery timelines.

The sales and rental network also comes from the company's own account: the so-called '6+1' system covers commercial sales, partner channels, e-commerce, marketing and video sales, community sales, and Mcube, plus a RoboShare platform operated by majority-owned AIxC, offering on-demand rental and asset access for qualified robots. There is no third-party evidence in the source that these arrangements are actually operating.

Alongside the hardware, Faraday Future launched four industry directions. Education targets K-12, centered on the Master Mini, with Blockly, Python, and ROS courses, teacher training, competitions, and classroom management tools; research targets universities, using models such as the All-New Futurist, providing a unified SDK, ROS interfaces, simulation, digital twins, data collection, and model training tools; security plans to use the Aegis Classic for indoor patrols and the Aegis Mega for larger outdoor and high-risk environments, supporting thermal imaging, LiDAR, autonomous patrols, remote operation, and multi-robot management; inspection uses the Aegis Mega, Aegis Hyper, and Faber, targeting energy, manufacturing, mining, and tunnels, with capabilities including gas detection, 3D scanning, meter reading, anomaly detection, and automatic reporting.

The logic of this approach is to package hardware, software, data, and specialized payloads, and it says external partners can connect to its embodied AI ecosystem. For buyers, this means the decision shifts from 'buying a robot' to 'connecting to a system'; but the source provides no landed customers, deployment scale, or performance data, so the four solutions are currently closer to product planning than proven commercial results.

Founder and Global CEO YT Jia cited Stanford professor Fei-Fei Li in the announcement, saying multiple robot forms will coexist in the same ecosystem, because different forms can both cover a wider range of tasks and generate real-world data from diverse scenarios and interactions. According to the company, this data supports EAI Brain training, skill development, and device iteration through the EAI Data Factory, allowing forms and capabilities to evolve together.

This is the most ambitious and least externally verified part of the entire announcement. It strings low-priced educational models, mid-priced wheeled-legged models, and high-priced industrial models into a data collection chain: the more forms, the more varied the scenarios, the richer the data, the stronger the model, which then feeds back into hardware. The logic is self-consistent, but the source contains no quantitative evidence on data scale, training effectiveness, or iteration cycles, nor any third-party assessment of its 'four-core full-stack AI' ecosystem. Therefore, this loop should be regarded as the company's strategic claim, not a proven capability.

In other words, the nine robots are the visible hardware list, while the data loop is the invisible bet. The former can be checked against prices and specs; the latter can only be tested by delivery volumes, real usage data, and subsequent iterations.

What can be confirmed: Faraday Future announced nine robot configurations, five models, and corresponding prices on September 21, 2026, and described four industry solutions and sales and rental arrangements. These are company-published product information.

What needs to be kept in mind: all statements about availability and delivery, ecosystem openness, and the effectiveness of the data loop come from the company itself, with no independent verification, customer cases, or delivery data in the source. For readers, a reasonable judgment is that the hardware list and pricing can be used for comparison, while commercial promises and the data narrative should await external evidence.

The next indicators worth watching are specific: whether these models actually generate verifiable orders and deliveries through FF.com, Amazon, and RobotShop; whether real buyers emerge for the K-12 and research solutions; and whether the EAI Data Factory publishes any checkable training or iteration data. Until these appear, the value of this announcement lies mainly in showing a roadmap, not in proving implementation.