Jetson Orin NX 16GB for Edge AI — Specs, Sizing & Deployment Fit
Last updated: August 2026
The mainstream production Jetson for multi-camera work: 157 TOPS, 16 GB of memory, and enough decode to carry 8–12 detection streams on one node.
Planning Takeaway
The mainstream production Jetson for multi-camera work: 157 TOPS, 16 GB of memory, and enough decode to carry 8–12 detection streams on one node. At ~$999 it sits where stream count, memory, and cost intersect for most 8-camera deployments.
Specifications
| Spec | Value |
|---|---|
| Compute | 157 INT8 TOPS (Ampere GPU + 2× NVDLA) |
| Memory | 16 GB LPDDR5, ~102 GB/s |
| Power modes | 10W · 15W · MAXN · 40W Super · MAXN Super (10–40 W envelope) |
| Video decode (modeled planning ceiling) | ~12× 1080p / ~3× 4K H.264 concurrent |
| Est. planning capacity | ~12 concurrent 1080p detection streams |
| Cooling | Active required |
| Form factor | Jetson module (69.6×45 mm) |
| Runtimes / precisions | TensorRT, PyTorch, ONNX, llama.cpp · 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 | ~$999 (module, as of mid-2026; NX 8GB module ~$649) |
Sizing Fit
The default pick for 8-camera 1080p production nodes, tracking-plus-detection pipelines, and retail or warehouse architectures that need one-node simplicity.
- 8-camera retail deployment — Reference architecture
- Warehouse forklift-safety architecture — Reference architecture
- Orin Nano vs Orin NX decision guide — Comparison
- Jetson lineup power comparison — Benchmarks
Decision Framework
Choose the Orin NX 16GB if:
- You need 8–12 concurrent 1080p streams with detection (and some tracking) on a single node.
- Your models need more than 8 GB of memory — multi-model pipelines fit comfortably in 16 GB.
- You want DLA engines for power-efficient offload alongside the GPU.
Choose a sibling instead if:
- Jetson Orin Nano Super — your node serves ≤6 streams and ~$399 buys enough compute.
- Jetson AGX Orin 64GB — you need 16+ streams, 64 GB memory, or VLM-class models on the same box.
- Hailo-10H — detection-only at up to ~8 streams on an existing host at a fraction of the power (~$130).
Frequently Asked Questions
How much does the Jetson Orin NX 16GB cost?
The Orin NX 16GB module lists at ~$999 as of the July 2026 NVIDIA repricing (up from $599); the 8 GB variant lists at ~$649. Carrier board and cooling are additional.
How many cameras can the Orin NX 16GB handle?
EdgeAIStack’s planning model puts it around 12 concurrent 1080p detection streams at 15 FPS, with hardware decode ceilings near ~12× 1080p or ~3× 4K H.264. Real capacity depends on model, resolution, and pipeline — validate with the Hardware Selector.
Orin NX 16GB vs AGX Orin — when do I step up?
Step up when you need more than ~12 streams, more than 16 GB of memory, or VLM/generative workloads co-located with vision. For pure 8-camera detection the NX 16GB at ~$999 is usually the better-balanced spend than the ~$2,999 AGX Orin 64GB.
What JetPack version does the Orin NX 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.