Jetson Orin Nano Super for Edge AI — Specs, Sizing & Deployment Fit
Last updated: August 2026
The default entry point into the Jetson line: 67 TOPS and 102 GB/s memory bandwidth at the same ~$399 the plain Orin Nano module now lists for, so for new purchases the Super wins on price parity alone.
Planning Takeaway
The default entry point into the Jetson line: 67 TOPS and 102 GB/s memory bandwidth at the same ~$399 the plain Orin Nano module now lists for, so for new purchases the Super wins on price parity alone. Suits 2–6 camera 1080p detection nodes and light multi-model pipelines; needs active cooling at its upper power modes.
Specifications
| Spec | Value |
|---|---|
| Compute | 67 INT8 TOPS (Ampere GPU) |
| Memory | 8 GB LPDDR5, ~102 GB/s |
| Power modes | 7W · 15W · 25W Super · MAXN Super (10–25 W envelope) |
| Video decode (modeled planning ceiling) | ~7× 1080p / ~1× 4K H.264 concurrent |
| Est. planning capacity | ~6 concurrent 1080p detection streams |
| Cooling | Active required at upper modes |
| Form factor | Jetson module (69.6×45 mm); dev kit installs via USB ISO on JetPack 7 (no SD-card image) |
| Runtimes / precisions | TensorRT, PyTorch, ONNX · FP32/FP16/INT8 |
| Software | JetPack 7.2 (Ubuntu 24.04, CUDA 13, June 2026) — current; JetPack 6.x (Ubuntu 22.04) — legacy track |
| Indicative price | ~$399 (dev kit, as of mid-2026) |
Sizing Fit
Best for single-node deployments of two to six 1080p cameras running YOLO-class detection, entry multi-model pipelines, and dev-to-production paths that stay inside the Jetson toolchain.
- 4-camera SMB deployment on a budget — Reference architecture
- Power modes: 7W vs 15W vs Super modes — Guide
- MAXN vs MAXN Super throughput and thermals — Guide
- Upgrade math vs the original Orin Nano — Comparison
Decision Framework
Choose the Orin Nano Super if:
- You are buying new: at ~$399 price parity with the plain Orin Nano, the Super’s 67 vs 40 TOPS and 102 vs 68 GB/s make it strictly the better buy.
- Your node serves 2–6 cameras at 1080p with detection-class models.
- You want the Jetson software stack (TensorRT/DeepStream) with the lowest current entry price.
Choose a sibling instead if:
- Jetson Orin Nano 8GB — you are matching an existing fleet or a thermal design validated at the plain Nano’s 15 W ceiling.
- Jetson Orin NX 16GB — you need 8+ streams, 16 GB memory, or headroom for tracking and second models.
- Rockchip RK3588 — cost-per-stream dominates and your pipeline is fixed and RKNN-validated (~$149 board).
Frequently Asked Questions
How much does the Jetson Orin Nano Super cost?
The Orin Nano Super Developer Kit lists at ~$399 as of the July 2026 NVIDIA repricing. That is the same list price as the plain Orin Nano 8GB module, so for new purchases the Super is the default choice.
Orin Nano Super vs Orin Nano — which should I buy?
At price parity (~$399 each), the Super wins for new builds: 67 vs 40 TOPS and 102 vs 68 GB/s memory bandwidth. The plain Orin Nano mainly makes sense when matching an existing deployment or a thermal design built around its 15 W ceiling.
How much power does the Orin Nano Super draw?
Between roughly 10 and 25 W depending on power mode (7W, 15W, 25W Super, and MAXN Super presets). The upper Super modes need active cooling; sustained inference at 15 W is the common production setpoint.
What JetPack version does the Orin Nano Super run?
JetPack 7.2 (June 2026) is current for this module — Ubuntu 24.04, Linux kernel 6.8, CUDA 13. JetPack 6.x remains a widely deployed legacy track on Ubuntu 22.04. Moving an existing JetPack 6 install to 7 requires the OTA package or a full reflash — a plain apt upgrade is not an upgrade path. On JetPack 7 the dev kit installs via the unified USB ISO installer — there is no SD-card image.