According to Electrek, Tesla has applied to register the name "Megapod" with the United States Patent and Trademark Office (USPTO). The filing describes a modular hardware solution intended to run artificial intelligence workloads, designed to be placed in data centers for rapid capacity expansion or to be combined with other units to form a complete AI data center.
The application characterizes the Megapod as a self-contained computing system: in simple terms, an element that can be added to AI data centers to scale capacity quickly or assembled together to create a full facility.
Strong competition already on the market
Tesla would not be first to market with such a unit. Nvidia already offers the GB200 NVL72, a liquid-cooled, rack-mountable system that integrates 72 Blackwell GPUs and 36 Grace processors and can function as a single very large GPU. Nvidia’s DGX SuperPOD assembles these racks into clusters that can include more than 9,000 GPUs.
Dell is building its own machine on the same platform as the PowerEdge XE9712, and Supermicro markets a GB200 NVL72 SuperCluster variant.
Name conflict and trademark considerations
A potential naming conflict exists: Submer already markets a product called MegaPod, which is essentially a 12-meter prefabricated data center. Nevertheless, Tesla could still obtain trademark protection for Megapod because the company filed in a different product category — computer hardware — than Submer’s product.
Tesla’s position in AI hardware
How successful Tesla’s Megapod concept might be remains uncertain. Tesla is not primarily a hardware vendor in this space and is itself a customer of Nvidia. The company’s track record in developing its own AI infrastructure is mixed: Tesla shut down its Dojo supercomputer in August 2025, and Elon Musk described plans for Dojo 2 as an "evolutionary dead end," facts that may weigh on market and partner perceptions.
In sum, the Megapod trademark filing signals Tesla’s interest in expanding its footprint in AI infrastructure, but established competitors, existing product alternatives and Tesla’s recent history in AI hardware make the project's feasibility and commercial prospects uncertain.
