General-purpose robots and autonomous machines are moving from research labs to real-world mass-market deployment, creating demand for compact, power-efficient AI supercomputers capable of running foundation models at the edge.
To meet that need, NVIDIA today introduced the T3000 and T2000, new modules based on the NVIDIA Thor architecture that enable mass-market robotics and edge AI applications at scale.
Jetson AGX Thor is powering this next generation of humanoid and robotic systems, with growing adoption across industries. Leading companies - including 1X, Agile Robots, Amazon Robotics, Boston Dynamics, FANUC, Hitachi and Techman Robot - are building on the platform.
Unlocking Humanoid and Robotics Deployment With T3000 The hardware underpinning those capabilities starts with the Jetson and IGX T3000 modules, which delivers 865 FP4 teraflops of AI compute in a compact form factor roughly half the size and power of the T5000. Jetson T3000 combines an NVIDIA Blackwell GPU, an eight-core Neoverse Arm CPU, 32GB of LPDDR5X memory and 273GB/s of memory bandwidth, along with 25 GbE connectivity. IGX T3000 delivers the same performance with integrated functional safety while seamlessly running the NVIDIA Halos for Robotics full-stack safety system for robots operating alongside humans.
Despite its smaller footprint, the T3000 achieves similar inference performance of the T5000 for multimodal workloads, including large language models, vision language models, vision language action models and world foundation models. Migrating to T3000 helps reduce costs amid high memory prices.
Going Wide on Edge AI With T2000 The Jetson T2000 brings Thor architecture to a broader range of edge AI systems. With 400 FP4 teraflops of compute and 16GB of memory, it provides an entry point for developers building visual AI agents, autonomous mobile robots, industrial manipulators and other intelligent machines.
With the introduction of the new NVIDIA Jetson modules, NVIDIA now offers a scalable edge AI platform spanning performance from 70 TOPS to 2,000 teraflops, enabling developers to address virtually any edge AI workload.
New Agent Skills Automate Memory Optimization Across All Jetson Devices AI agents are transforming developer productivity by automating memory optimization, system configuration and deployment tasks that previously required manual effort and deep domain expertise.
With the newly released Jetson agent skills, developers can optimize the entire software stack and achieve significant memory savings in days instead of weeks. These skills support the entire Jetson portfolio, including Jetson Thor and Jetson Orin, enabling developers to run more capable workloads on lower-memory configurations.
The result is lower system cost, faster deployment and the flexibility to move down one memory SKU within the same product tier without compromising performance.
Companies across industries and regions have accelerated development while achieving substantial memory savings through software optimization.
Humanoid robotics leaders including UBTech and Agile Robots, along with industrial solutions provider Connect Tech, have reduced memory usage by up to 15GB, enabling them to move from NVIDIA Jetson AGX Orin 64GB to the 32GB module.
In smart retail, SandStar reduced memory usage by up to 4GB, enabling deployment on the NVIDIA Jetson Orin NX 8GB module instead of the 16GB configuration. In companion robotics, GROOVE X, creator of the LOVOT robot, uses Jetson's heterogeneous AI accelerators to optimize workload distribution, reducing memory usage and enabling deployment on lower-memory configurations.
In intelligent transportation, NoTraffic reduced memory usage by 30% on Jetson TX2 NX, creating headroom to add more AI capabilities into its smart traffic platform without increasing hardware requirements.
With agent skills simplifying development and NVIDIA NemoClaw blueprints orchestrating intelligent agents, Jetson is an agentic-ready platform for physical AI, enabling advanced reasoning, autonomous decision-making and task automation at scale.
Delivering Cosmos 3 Edge to NVIDIA Thor Lineup NVIDIA today expanded its NVIDIA Cosmos 3 frontier open world foundation model family - built as a robot foundation model for embodied systems - with a lightweight model compatible with NVIDIA Thor platforms. Cosmos 3 Edge is a 4-billion-parameter model helping embodied systems see the world, reason over it in real time, and predict and generate actions through on-device inference. Using the open Cosmos framework, developers can post-train Cosmos 3 Edge for specific embodiments and sensors in about a day - closing the sim-to-real gap - then deploy on Jetson Thor for real-time vision analysis and on-device robot policy.
Start Development Today With Emulation Mode Sharing the same chip architecture and software stack in the NVIDIA Thor family, the new modules provide a seamless development path. Developers can begin building today using the Jetson AGX Thor developer kit available through channel partners and emulate the performance of T3000 and T2000 modules.
Using NVIDIA's full physical AI software stack - including NVIDIA Isaac for robotics simulation and perception - alongside open models such as NVIDIA Nemotron, Cosmos 3 and Isaac GR00T, developers can accelerate the development of next-generation robots, autonomous machines and visual AI agents.
Developers can begin using T3000 emulation mode later this month with JetPack 7.2.1. Support for T2000 emulation mode will follow in a future release. The Jetson T3000 and T2000 modules are scheduled to become available in Q1 2027.
ADLINK, Advantech, AAEON, Aetina, Auvidea, AVerMedia, Connect Tech, ForeCR, JWIPC, NEXCOM Robotic Solutions, Realtimes, Seeed Studio, Twowin, TZTEK and YUAN are among other partners in the Jetson ecosystem already providin
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General-purpose robots and autonomous machines are moving from research labs to real-world mass-market deployment, creating demand for compact, power-efficient AI supercomputers capable of running foundation models at the edge. 
