Configurable module. Figures shown are for the 40 W MAXN_SUPER mode NVIDIA added through JetPack 6.2 in December 2024; the module also runs at 10, 15 and 25 W. The headline module TOPS count the NVDLA deep learning accelerators as well as the GPU, so this page shows the GPU share and states the module total in the notes.

NVIDIA Jetson Orin NX 16GB

Architecture: AmpereForm factor: ModuleReleased: 2022Spec confidence: Official
FP32
2.4
TFLOPS
Memory
16 GB
LPDDR5
Bandwidth
102 GB/s
memory
TDP
40 W
60.0 FP32 dense TFLOPS/kW of TDP

Overview

The Jetson Orin NX 16GB is the larger of NVIDIA's two Orin NX system-on-modules, a 69.6 by 45 mm board on a 260-pin SO-DIMM edge connector. It pairs a 1024-core Ampere GPU with 32 third-generation tensor cores, two NVDLA v2.0 deep learning accelerators and an 8-core Arm Cortex-A78AE CPU over 16 GB of 128-bit LPDDR5 at 102 GB/s. NVIDIA launched it in 2022 at 100 sparse INT8 TOPS for the module in a 10 to 25 W envelope, and JetPack 6.2 added a 40 W MAXN_SUPER mode in December 2024 that lifts the GPU clock from 918 to 1,173 MHz and the module to 157 sparse TOPS. Of that 157, 80 come from the two NVDLA engines, leaving 77 sparse or 38.5 dense INT8 TOPS on the GPU, and the GPU's CUDA cores deliver 2.40 TFLOPS of FP32. It targets robots, drones, smart cameras and other edge systems that need more than an Orin Nano but cannot take the power or size of an AGX Orin.

Performance

Peak theoretical throughput by precision type

PrecisionDense2:4 Sparse
FP64
No verified data available Structured sparsity is a tensor-core feature; this vector precision has no sparse form
FP32
32-bit floating point
2.4TFLOPS Structured sparsity is a tensor-core feature; this vector precision has no sparse form
TF32
No verified data available The part supports 2:4 sparsity, but the vendor publishes no sparse figure for this precision
BF16
No verified data available The part supports 2:4 sparsity, but the vendor publishes no sparse figure for this precision
FP16
16-bit floating point
No verified data available The part supports 2:4 sparsity, but the vendor publishes no sparse figure for this precision
FP8
No verified data available The part supports 2:4 sparsity, but the vendor publishes no sparse figure for this precision
FP6
No verified data available The part supports 2:4 sparsity, but the vendor publishes no sparse figure for this precision
FP4
No verified data available The part supports 2:4 sparsity, but the vendor publishes no sparse figure for this precision
INT8
8-bit integer
39TOPS 77TOPS

Specifications

Architecture

Ampere

Form Factor

Module

Launch Year

2022

Process Node

No verified data available

Memory

16 GB LPDDR5

Bandwidth

102 GB/s

TDP

40 W

Max power

40 W

CUDA Cores

1,024

Spec Confidence

Official

Full Specifications

Compute Engine
CUDA Cores 1,024
Tensor Cores 32 (3rd Gen)
Streaming Multiprocessors 8
Boost Clock 1.17 GHz
Memory
Memory 16 GB
Memory Type LPDDR5
Bandwidth 102 GB/s
Interface Width 128-bit
Interconnect & I/O
PCIe 4.0
Power & Thermal
TDP 40 W
Max power 40 W
Enterprise Features
Sparsity Yes
General
Form Factor Module
Architecture Ampere
Process Node No verified data available
Launch Year 2022

Datasheet & Resources

Data Provenance

Every figure traced to a source

Primary Source

Publisher
NVIDIA
Published
2026-02-20

Data Quality

Spec confidence
Official
Clock basis
Boost
Core precisions with figures
2 of 9
Normalization
All values in TFLOPS

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Frequently Asked Questions

How many TFLOPS does the NVIDIA Jetson Orin NX have?

The NVIDIA Jetson Orin NX delivers 2.4 TFLOPS FP32 at peak. Flopper does not currently have verified FP16 and FP8 throughput figures for it.

What is the power consumption of the NVIDIA Jetson Orin NX?

The NVIDIA Jetson Orin NX has a TDP (Thermal Design Power) rating of 40 watts.

How much memory does the NVIDIA Jetson Orin NX have?

The NVIDIA Jetson Orin NX is equipped with 16 GB of memory with 102 GB/s of memory bandwidth.

What architecture is the NVIDIA Jetson Orin NX based on?

The NVIDIA Jetson Orin NX is based on the Ampere architecture, launched in 2022.

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