CARINA Jetson Orin NX Developer Kit

Overview

Prototype on the silicon you will deploy. An open carrier board with the Orin NX module and JetPack preloaded — full I/O access for bring-up, then the identical module in a sealed production node once the design is proven.

Key highlights

• NVIDIA Jetson Orin NX — 70/100 TOPS (Super mode: 117/157 TOPS).
• 8–16 GB unified LPDDR5 · 102.4 GB/s — CPU and GPU share one memory pool.
• Open carrier board with full I/O broken out for bring-up.
• Full CUDA and JetPack — the same toolchain as every larger NVIDIA system RDP supplies.
• Identical module to the production node — validate once, deploy unchanged.
• Compact footprint for cabinets, control rooms and equipment racks.
• Imaged and validated by RDP against your application before dispatch; GST invoice, pan-India onsite, GeM.

AI workload fit

• Multi-camera computer vision — inspection, safety, surveillance.
• Real-time inference where latency or connectivity rules out the cloud.
• Agentic AI running unattended at a remote site.
• NLP & speech processing of local audio.
• Generative AI at the edge for on-site content and reporting.
• Design-in, bring-up and pipeline validation before a fleet commitment.

AI workload positioning

Edge deployments fail on interfaces and environment far more often than on compute. Camera link type, time sync, power tolerance and ingress protection decide whether a unit survives the site; the accelerator rarely does. Specify those with the deployment, not after it. A developer kit earns its place by de-risking the fleet order that follows: the module is identical to the production node, so what you validate is what you deploy. It is a design-in tool, not a production unit — deploy the sealed node.

Industry use cases

• Manufacturing: line inspection, safety zones and predictive maintenance.
• Public sector & sovereign: smart-city, traffic and rail-transit analytics, on soil.
• Telecom & 5G: inference at the network edge and in cell-site cabinets.
• Automotive & mobility: AMR/AGV fleets and off-highway machinery.
• Defence & aerospace: inspection drones and rugged field systems.

Performance & how to be sure

Precision basis matters enormously at the edge — an FP4 TFLOPS figure is not comparable with an INT8 TOPS number, and vendors quote whichever flatters. RDP will run your actual pipeline on the unit rather than restate a headline. NVIDIA publishes 70/100 TOPS (Super mode: 117/157 TOPS) for this module; any “Super mode” figure is a power/clock mode rather than the default and carries a real thermal cost. Rather than quote a tokens/sec figure that will not match your workload, RDP offers a “benchmark your model” session: bring the model, precision and context length you actually intend to run, and we will validate it on this exact configuration before you commit.

Series & upgrade path

CARINA tier. The Jetson ladder runs Orin Nano → Orin NX → AGX Orin → Thor; step up when model size or camera count exceeds the tier, not by default. Above the ladder: RDP micro data center pods when a site outgrows a single node.

On-prem vs cloud (TCO)

For sustained daily AI work this configuration removes per-GPU-hour billing, queueing for scarce instances, and egress charges on your own data — and keeps everything on-premises for DPDP and data-residency obligations. Cloud still wins for burst capacity and one-off very large training runs; on-prem wins on sustained utilisation, control and predictable INR capital cost. We model the crossover with your actual usage rather than assert it.

Software & day-one readiness

Ships with NVIDIA JetPack — the Jetson SDK — including CUDA, cuDNN, TensorRT, DeepStream for multi-camera video analytics, and support for the Isaac (robotics) and Metropolis (vision) frameworks. This is the same CUDA programming model as every larger NVIDIA system RDP supplies, so a model developed on a workstation or GPU server deploys to the edge without a rewrite. RDP images and validates the unit against your application before dispatch.

Power, thermal & acoustics

DC input on a compact fanless chassis; exact input range and mounting confirmed per deployment. No moving parts — suited to sealed cabinets and dusty indoor environments. Exact wattage, BTU and dB(A) figures come from RDP bench measurement rather than estimates — ask for the site-readiness sheet with your quote.

Deployment, warranty & support

Built to order by RDP Technologies. Supplied with GST invoice, pan-India onsite support, and availability through GeM for public-sector procurement. Built to order — typically 6–8 weeks; module allocation confirmed at quotation.

Why RDP

RDP Technologies is a Make-in-India OEM with 14+ years and 300,000+ units shipped, supplying AI infrastructure from desk-side systems to rack-scale AI factories — with predictable INR pricing, GST invoicing and pan-India onsite service.

Buy with confidence

Use Request a Quote to reach an RDP solution architect for sizing, a benchmark-your-model session, financing options and a delivery plan. No obligation.

Specifications