NVIDIA Announces Jetson Orin Nano 2 Robotics Computer to Redefine Entry-Level Edge AI

Rhea-AI Summary

NVIDIA (NASDAQ: NVDA) unveiled the Jetson Orin Nano 2, a new entry-level robotics computer for edge AI that targets robots, drones and vision systems. The module delivers 78 trillion operations per second of AI compute, 8GB of memory and an 8-core Arm CPU.

According to NVIDIA, Jetson Orin Nano 2 offers 2x the inference performance of Jetson Orin Nano Super in the same form factor and can use 40% less power at equal performance. Over 3 million developers build on NVIDIA’s robotics stack, with early adopters including Cognex, Doosan Bobcat, Matic and Wing. Partners such as AAEON, ADLINK and Advantech are creating carrier boards and hardware systems. The module and developer kit are expected to be available in the first half of 2027.

News Explained

The release distinguishes partner status: Matic is adopting Jetson Orin Nano 2, while Wing is still using Jetson Orin Nano Super and only plans to evaluate the new computer.

Market Context

The momentum scanner recorded AMD at 4.707221686840057% up, placing this announcement within broader...

Analysis

The momentum scanner recorded AMD at 4.707221686840057% up, placing this announcement within broader semiconductor strength. Historical AI reactions averaged -2.18%; delivery timing and market acceptance remained relevant risks.

Key Figures

Inference performance: 2x Power consumption reduction: 40% Developer base: More than 3 million developers +5 more

8 metrics

Inference performance 2x vs. Jetson Orin Nano Super in the same compact form factor

Power consumption reduction 40% less power in 15-watt mode at the same performance

Developer base More than 3 million developers building on NVIDIA’s robotics stack

AI compute 78 trillion operations per second Jetson Orin Nano 2 AI compute

Memory 8GB Jetson Orin Nano 2

CPU 8-core Arm CPU Jetson Orin Nano 2

Power mode 15-watt operating mode referenced for power comparison

Availability First half of 2027 module and developer kit expected availability

Previous AI Reports

5 past events · Latest: Aug 24 (Positive)

Same Type Pattern 5 events

Date	Event	Sentiment	24h Move	Catalyst
Aug 24	AI accelerator production	Positive	-2.9%	Groq 3 LPX entered full production with reported inference speed advantages.
Aug 24	AI infrastructure adoption	Positive	-2.9%	SpaceXAI planned deployment of Vera CPUs and Vera Rubin infrastructure.
Aug 17	AI campus partnership	Positive	-0.1%	NVIDIA secured an Ohio AI campus role and committed $1.5 billion.
Jul 26	AI toolkit expansion	Positive	-5.0%	NVIDIA expanded engineering tools with PhysicsNeMo and CUDA-X libraries.
Jul 25	AI infrastructure expansion	Positive	+0.0%	NVIDIA announced Korea infrastructure expansion with NAVER and Brookfield.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

The five matched AI events averaged a -2.18% price reaction, with four negative reactions and one flat reaction despite generally positive announcements.

Key Terms

edge ai, inference performance, large language models, vision language models, +1 more

5 terms

edge ai technical

"a new robotics computer for entry-level edge AI"

Edge AI refers to artificial intelligence systems that process data directly on local devices or nearby servers rather than sending information to distant data centers. This allows for faster decision-making and real-time responses, similar to how a home security camera can instantly detect motion without needing to connect to a remote server. For investors, edge AI represents a growing trend toward more efficient, responsive technology that can create new opportunities across various industries.

inference performance technical

"delivers 2x the inference performance of its predecessor"

Inference performance is how well a trained machine-learning or AI model works when it is actually used to make predictions or decisions, measured by factors such as accuracy, speed (latency), throughput, and the computing resources required. For investors, it matters because those qualities determine user experience, operating cost and scalability—similar to how a car's fuel efficiency and acceleration affect its practicality for everyday driving and long trips.

large language models technical

"run the latest large language models and vision language models"

Large language models are advanced AI systems trained on vast amounts of text to understand and generate human-like writing, like a very fast reader and writer that learns patterns in words and sentences. They matter to investors because they can change how companies operate—automating customer service, speeding analysis, cutting costs, creating new products—and they introduce risks around accuracy, security and regulation that can affect a firm’s revenue and reputation.

vision language models technical

"large language models and vision language models optimized"

Vision language models are artificial intelligence systems that understand and generate insights from both images and text together, like a person who can look at a picture and read a caption to form a single, meaningful interpretation. Investors care because these models can enable new products, automate tasks such as image-based search or document review, and change cost and revenue dynamics across industries much like how smartphones reshaped consumer services.

carrier boards technical

"partners are building carrier boards, hardware systems"

A carrier board is a printed circuit board designed to hold and connect a smaller computing module (like a system-on-module or compute module), supplying power, physical mounting, and routes for input/output connectors, memory, and other peripherals. Think of it as an adapter or motherboard that turns a compact compute module into a complete device with usable ports and interfaces. Investors see mentions of carrier boards because they relate to how quickly and cheaply a hardware product can be produced, customized, and brought to market, affecting manufacturing complexity and potential revenue streams.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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News Summary:

• NVIDIA Jetson Orin Nano 2, a new robotics computer for entry-level edge AI, enables millions of developers worldwide to build robots, delivery and inspection drones, and vision AI systems for frontier physical AI applications.
• Jetson Orin Nano 2 delivers 2x the inference performance of its predecessor in the same form factor and consumes 40% less power at the same performance.
• More than 3 million developers have built on the NVIDIA robotics stack, with Cognex, Doosan Bobcat and Matic among the first to adopt and explore Jetson Orin Nano 2.
• Ecosystem partners are building carrier boards, hardware systems and reference solutions to help customers accelerate time to market.

SANTA CLARA, Calif., Aug. 25, 2026 (GLOBE NEWSWIRE) -- NVIDIA today announced NVIDIA Jetson Orin Nano™ 2, a new robotics computer set to redefine entry-level edge AI — putting frontier-class generative AI performance in the hands of millions of developers.

As AI models grow smaller and more efficient, more edge devices can become autonomous systems that understand context, interpret language and images, and act in real time. To bring these capabilities into physical machines like robots, delivery and inspection drones, and vision AI systems, developers need compact, energy-efficient robotics computers built for edge AI.

“Today’s small and medium frontier models have reached the accuracy of last year’s largest frontier models, unlocking real-time intelligence for edge devices,” said Deepu Talla, vice president of robotics and edge AI at NVIDIA. “The Jetson Orin Nano 2 computer puts that breakthrough within reach of millions of developers, delivering the performance and energy efficiency needed for real-time reasoning at the edge.”

Cognex, Doosan Bobcat and Matic are among the first to adopt and explore Jetson Orin Nano 2.

A Major Leap for Entry-Level Edge AI
Featuring 78 trillion operations per second of AI compute, 8GB of memory and an 8-core Arm CPU, Jetson Orin Nano 2 delivers a significant leap in AI and video-processing performance in a cost-effective, power-efficient system.

Jetson Orin Nano 2 achieves 2x the inference performance of Jetson Orin Nano Super through improved Tensor Cores and higher memory bandwidth, while maintaining the same compact form factor. In 15-watt mode, Jetson Orin Nano 2 consumes 40% less power to deliver the same performance as its predecessor.

Powered by NVIDIA’s open software stack, NVIDIA Jetson™ agent skills and a rich AI ecosystem, Jetson Orin Nano 2 enables developers to run the latest large language models and vision language models optimized for memory-efficient edge inference — including open models like NVIDIA Cosmos™ and NVIDIA Nemotron™, Gemma 4 and Qwen 3 — to rapidly build advanced AI applications.

Partner Ecosystem and Millions of Robotics Developers Build on Jetson
More than 3 million developers are building on NVIDIA’s robotics stack, and with Jetson Orin Nano 2, partners like Cognex, Doosan Bobcat, Matic and Wing are bringing real-world edge AI applications to compact devices, including home robots, vision AI systems, delivery and inspection drones, carrier boards, hardware systems and reference solutions.

Wing, a leading drone delivery company and subsidiary of Alphabet, is using Jetson Orin Nano Super and the NVIDIA software stack in its delivery drone fleet — and plans to evaluate Jetson Orin Nano 2 to advance real-time AI perception and reasoning for faster, safer delivery from local businesses to residential yards.

“Drone delivery depends on AI that can enable fast, reliable understanding of the real world,” said Dinuka Abeywardena, head of perception at Wing. “Wing is exploring Jetson Orin Nano 2 to give us a path to more responsive, energy-efficient drones that can help make deliveries quicker and more dependable for customers.”

Matic Robots, an advanced consumer robotics company, is adopting Jetson Orin Nano 2 to enable more intuitive interactions with its home cleaning robots, enabling them with conversational AI, gesture detection, deeper context of the home with precision mapping and semantic understanding, and autonomous cleaning capabilities.

“Home robots need to understand people, map spaces precisely, understand the layout of objects and spaces, and clean autonomously in dynamic and constantly changing environments,” said Navneet Dalal, cofounder and CEO of Matic Robotics. “With Jetson Orin Nano 2, Matic can run state-of-the-art AI models at the edge in a compact home robotics platform built for real-time perception, interaction and navigation.”

AAEON, ADLINK, Advantech, Aetina, Antmicro, Aptiv, Auvidea, AVerMedia, Chuanglebo, Connect Tech, ForeCR, JWIPC, Neurealm, Plink, Realtimes, RidgeRun, RS, Seeed Studio, Tauro Tech, Twowin, TZTEK and YUAN are among other Jetson partners building carrier boards, hardware systems, customized AI software and reference solutions to help customers accelerate time to market.

Availability
The NVIDIA Jetson Orin Nano 2 module and developer kit are expected to be available in the first half of 2027.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.

For further information, contact:
Paris Fox
Corporate Communications
NVIDIA Corporation
press@nvidia.com  

Certain statements in this press release including, but not limited to, statements as to: expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on NVIDIA’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, Jetson, Jetson Orin Nano, Nemotron and NVIDIA Cosmos are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/b57df87f-2cc6-4a5f-a81a-197f726f144a

FAQ

What is NVIDIA Jetson Orin Nano 2 and how does it relate to NVDA stock?

NVIDIA Jetson Orin Nano 2 is a new entry-level robotics computer for edge AI. According to NVIDIA, it targets robots, drones and vision AI systems, extending the Jetson platform that underpins many physical AI applications developers build on today.

How much performance does Jetson Orin Nano 2 deliver compared with previous Jetson models from NVIDIA (NVDA)?

Jetson Orin Nano 2 delivers 78 trillion operations per second of AI compute. According to NVIDIA, it achieves 2x the inference performance of Jetson Orin Nano Super in the same form factor, aided by improved Tensor Cores and higher memory bandwidth for edge inference.

How does Jetson Orin Nano 2 improve power efficiency for edge AI robotics?

Jetson Orin Nano 2 can consume 40% less power at the same performance level as its predecessor. According to NVIDIA, in 15-watt mode it maintains equal performance, supporting more energy‑efficient robots, drones and vision systems where power budgets are constrained.

When will NVIDIA Jetson Orin Nano 2 modules and developer kits be available?

NVIDIA expects Jetson Orin Nano 2 modules and developer kits to be available in the first half of 2027. According to NVIDIA, this timing will give partners and developers a roadmap to plan new robotics, drone and vision AI designs around the upgraded platform.

Which companies are early adopters of NVIDIA Jetson Orin Nano 2 edge AI platform?

Early adopters include Cognex, Doosan Bobcat, Matic and Wing. According to NVIDIA, these partners are exploring Jetson Orin Nano 2 for applications such as industrial vision, construction equipment, home cleaning robots and drone delivery with real-time AI perception and reasoning.

How many developers build on NVIDIA’s robotics stack that includes Jetson Orin Nano 2?

More than 3 million developers are building on NVIDIA’s robotics stack. According to NVIDIA, this community uses Jetson hardware, NVIDIA Jetson agent skills and the broader AI ecosystem to create robots, delivery and inspection drones, and compact vision AI systems at the edge.

What AI models can run on NVIDIA Jetson Orin Nano 2 for edge applications?

Jetson Orin Nano 2 can run large language and vision language models optimized for memory‑efficient edge inference. According to NVIDIA, supported open models include NVIDIA Cosmos, NVIDIA Nemotron, Gemma 4 and Qwen 3 for building advanced perception and reasoning at the edge.