Ai-Paipai Launches Development Program for the NVIDIA Jetson Orin Nano 2
Ai-Paipai Launches Development Program for the NVIDIA Jetson Orin Nano 2
NVIDIA has unveiled the Jetson Orin Nano 2, its new-generation robotics computer for entry-level autonomous machines. Compared with the previous Jetson Orin Nano Super, it delivers 2× higher generative-AI inference performance and cuts power draw by 40% at equal workload in the 15 W mode — while keeping the same 260-pin SO-DIMM footprint for a drop-in hardware migration.
For robotics and vision-AI teams, that combination matters: more on-device intelligence, less battery, and no carrier-board redesign. Here is what the module brings, and how Ai-Paipai is preparing to help you build on it.
1. Key Specifications at a Glance
| Parameter | Jetson Orin Nano 2 |
|---|---|
| AI Performance | Up to 78 TOPS (sparse INT8) |
| CPU | 8-core Arm® Cortex®-A78AE |
| GPU | Refined NVIDIA Ampere architecture |
| Accelerators | Next-generation Tensor Cores |
| Memory | 8 GB LPDDR5x |
| Power Envelope | Dynamically adjustable 15 W – 40 W |
| Form Factor | 260-pin SO-DIMM, 69.6 × 45 mm |
| Compatibility | Pin-to-pin with existing Orin Nano carrier boards |
| On-board Storage | None (no eMMC) |
| Boot Options | NVMe M.2 · microSD |
| Video Engine | Multi-channel 4K encode / decode |
| Target Workloads | Robotics · delivery & inspection drones · vision AI systems |
2. What Improved vs. Jetson Orin Nano Super
| Dimension | Orin Nano Super | Orin Nano 2 | Practical Impact |
|---|---|---|---|
| Generative-AI inference | Baseline | 2× faster | Runs larger LLMs / VLMs locally on the robot |
| Power at equal workload (15 W mode) | Baseline | 40% lower | Longer battery life for mobile platforms |
| AI compute | — | 78 TOPS sparse INT8 | Headroom for multi-sensor fusion |
| Mechanical / pinout | 260-pin SO-DIMM | Identical | No carrier-board respin, lower migration cost |
| Power modes | Fixed profiles | 15–40 W dynamic | Tune performance against thermal budget |
3. Software Stack & Model Support
The Jetson Orin Nano 2 is fully compatible with the NVIDIA software stack, so existing Jetson workflows carry over directly.
| Layer | Support | What It Enables |
|---|---|---|
| Compute / SDK | CUDA · cuDNN · TensorRT-LLM | Optimized inference pipelines |
| Foundation Models | NVIDIA Nemotron · NVIDIA Cosmos · Gemma 4 · Qwen3 | Local LLM and multimodal vision-language inference |
| Robotics Framework | Isaac ROS (deep integration) | End-to-end edge workflow: perception → scene understanding → LLM inference → motion decision |
| Offline Capability | On-device generative AI | Real-time semantic understanding and autonomous decisions without cloud dependency |
| Video Pipeline | Multi-channel 4K encode / decode | Concurrent processing from multiple vision sensors |
4. Target Applications
| Segment | Typical Platform | Why Orin Nano 2 Fits |
|---|---|---|
| Robotics | Humanoid robots | 78 TOPS for on-device VLM reasoning; 15 W mode for battery operation |
| Inspection | Wheeled inspection robots | Multi-sensor 4K pipelines + offline decision-making |
| Mobility | Low-speed mobile robots / AGV | Dynamic 15–40 W tuning against thermal envelope |
| Aerial | Delivery & inspection drones | 40% lower power at equal workload extends flight time |
| Vision AI | Industrial vision systems | Full 4K encode/decode across concurrent camera streams |
5. Ai-Paipai's Development Program
As an Embedded solutions provider based on NVIDIA Jetson modules, carrier boards, and complete Edge AI systems, Ai-Paipai has started pre-research on robotics solutions built around the Jetson Orin Nano 2. Our engineering work focuses on shortening your path from module to working prototype.
| Workstream | Scope | Outcome for You |
|---|---|---|
| Carrier Board Bring-up | Reference design, schematic review, power/thermal validation | Compatible hardware foundation, faster first boot |
| System Image Tuning | BSP / JetPack customization, boot-from-NVMe configuration | Stable, production-ready system image |
| Multimodal Model Porting | TensorRT-LLM optimization for Nemotron, Cosmos, Gemma 4, Qwen3 | Models running at target latency on-device |
| Sensor Driver Adaptation | Camera, LiDAR, IMU driver integration under Isaac ROS | Working perception stack on your sensor set |
| Reference Design | Lightweight robotics reference platform | Accelerated prototype validation, shorter dev cycle |
Why Build With Ai-Paipai
| Capability | Detail |
|---|---|
| Authorized Sourcing | Genuine modules and carrier boards with traceable serials and manufacturer warranty |
| Carrier Board Design | In-house PCB design experience on AI acceleration modules — custom carrier boards for production projects |
| Engineering Support | Datasheets, SDKs, BSP images and schematic review — before and after you buy |
| OEM & Customization | Enclosures, BSP tailoring, volume pricing for production builds |
| Global Fulfilment | DHL / FedEx dispatch from Shenzhen to 100+ countries, tracked |
Get Early Access
Planning a robotics or vision-AI build on the Jetson Orin Nano 2? Tell us your platform, sensor set and target power budget — our engineers will scope the bring-up with you.
Sample testing is in progress. Evaluation units and technical support will be released to industry developers first.
Contact an Engineer →
