Nvidia has launched its latest robotics chip module, Jetson AGX Thor, now available as a developer kit for US$3,499.

The chip is based on Nvidia’s Blackwell graphics processor, will begin shipping next month, and is designed for companies building robots.

Bulk orders of over 1,000 units are priced at US$2,999 per module.

Nvidia said the Jetson AGX Thor is 7.5 times faster than its previous generation and comes with 128GB of memory to support large AI models.

The company noted that firms such as Agility Robotics, Amazon, Meta, and Boston Dynamics are using its Jetson line for robotics applications.

Robotics currently contributes about 1% of Nvidia’s total revenue, and the combined automotive and robotics unit reported a 72% year-on-year sales rise in May.

Nvidia has also grouped its automotive and robotics businesses into a single division.

.source-ref{font-size:0.85em;color:#666;display:block;margin-top:1em;}a.ask-tia-citation-link:hover{color:#11628d !important;background:#e9f6f5 !important;border-color:#11628d !important;text-decoration:none !important;}@media only screen and (min-width:768px){a.ask-tia-citation-link{font-size:11px !important;}}

🔗 Source: CNBC

🧠 Food for thought

1️⃣ Nvidia repeats its successful playbook of extending dominant architectures into new markets

The Jetson Thor launch follows a familiar pattern in Nvidia’s history, taking a successful chip architecture and adapting it for entirely new industries.

This mirrors what happened with the NV20 in 2001, which was the first programmable GPU and opened up applications far beyond gaming into scientific computing and eventually machine learning 2.

Now Nvidia is applying the same strategy with its Blackwell architecture, using the same GPU technology that powers AI data centers in a robotics chip that costs $2,999 per module for large orders 1.

The approach leverages Nvidia’s core strength: instead of building entirely new chip architectures for robotics, they’re adapting proven technology with 128GB of memory specifically sized for AI models that robots need to interpret their environment 1.

This strategy has historically allowed Nvidia to maintain technical leadership while expanding into new markets, though robotics currently represents only about 1% of the company’s revenue despite growing 72% year-over-year to $567 million quarterly 1.

The real test will be whether Nvidia can replicate in robotics the developer ecosystem dominance it achieved in AI, where it holds 85-90% market share 3.

Recent Nvidia developments

……