NVIDIA Jetson Orin Nano 4 GB

Benchmark Performance

The NVIDIA Jetson Orin Nano 4 GB occupies a unique position in the benchmark database. While it is an integrated graphics processor (IGP) with a 10 W thermal design power, its Ampere architecture and 512 shading units deliver a measured FP32 throughput of 640.0 GFLOPS. This places it at the 50th percentile among all GPUs tracked in the database, meaning half of all recorded graphics processors outperform it and half fall below its level of compute capability.

The chip's rendering throughput is defined by its 16 texture mapping units and 8 raster operation pipelines. These produce a texture rate of 10.00 GTexel/s and a pixel rate of 5.000 GPixel/s, respectively. For context, this pixel rate means the chip can fill roughly five gigapixels per second under ideal conditions, which is modest by discrete graphics standards but entirely appropriate for its embedded and edge-computing role. The FP16 performance doubles to 1,280.0 GFLOPS via a 2:1 ratio, a figure that hints at the architecture's design intent for AI inference workloads rather than pure rasterization.

Because the nearestRivals array is empty in the data, direct percentage comparisons against competing parts are not available from the FACT PACK. However, the percentile ranking provides a useful interpretive anchor: at the median of all GPUs, this is not a part designed to challenge desktop graphics cards. Its performance class is defined more by its power envelope and form factor than by raw frame rates. The 8 nm Samsung process node and 200 mm² die size indicate a relatively large silicon area for such a low-power part, suggesting that the transistor budget is heavily weighted toward tensor cores and AI acceleration rather than traditional graphics throughput.

The absence of a boost clock and base clock in the specifications further underscores that this is not a performance-oriented graphics solution in the conventional sense. Instead, benchmark results should be interpreted through the lens of sustained, low-power compute tasks. The DirectX 12 Ultimate (12_2) support, OpenGL 4.6, and Vulkan 1.4 API compatibility ensure that modern graphics features are available, but the hardware execution rates will limit their practical application in demanding scenarios.

Memory Subsystem

The memory configuration of the Jetson Orin Nano 4 GB is one of its most defining characteristics. It ships with 4 GB of LPDDR5 memory across a 64-bit bus, yielding a total bandwidth of 34.11 GB/s. The memory clock runs at 533 MHz, which translates to an effective 4.3 Gbps per pin. This is a tightly constrained memory subsystem when compared to discrete graphics cards, but for an embedded IGP, it represents a balanced design.

The 64-bit bus width is half of what many entry-level desktop GPUs use, and the resulting bandwidth of 34.11 GB/s will be the primary limiting factor at higher resolutions. For 1080p gaming or lightweight graphics workloads, the memory bandwidth may prove sufficient for low-to-medium settings, but 1440p or 4K rendering will likely expose the bottleneck. High-resolution textures and heavy anti-aliasing consume bandwidth rapidly, and the data suggests that the Jetson Orin Nano 4 GB is not equipped to handle such demands with fluidity.

LPDDR5 is a low-power memory standard, which aligns with the 10 W TDP of the overall package. The trade-off is clear: power efficiency comes at the cost of raw throughput. For AI workloads, where the tensor cores can process data in a more compute-dense manner, the memory bandwidth may be less of a constraint. But for graphics rendering, where every pixel and texture fetch requires memory transactions, the 34.11 GB/s figure will cap performance well before the compute units reach their limits.

The memory type also influences the system's overall footprint. Being an IGP, there is no dedicated VRAM allocation; the 4 GB is shared with the system. This further reduces the effective memory available for graphics in multi-tasking scenarios. The 5.000 GPixel/s pixel rate combined with 34.11 GB/s bandwidth suggests that the design point is primarily for low-resolution, low-latency inference and lightweight display output rather than immersive gaming.

Who Should Consider It

Benchmark data indicates this processor is best suited for developers and integrators building compact, power-constrained systems where AI inference is the primary workload. The 16 tensor cores and FP16 throughput of 1,280.0 GFLOPS provide meaningful compute for neural network inference, and the 10 W TDP allows for passive cooling or small fan solutions in embedded chassis. The 70 mm length and 45 mm height dimensions reinforce its role in space-constrained designs.

For graphics-oriented tasks, the recommendation is more cautious. At 1080p with low settings, the 640.0 GFLOPS FP32 performance and 34.11 GB/s bandwidth could handle older titles, esports games, or 2D applications. The 50th percentile ranking against all GPUs suggests that users should not expect playable frame rates in modern AAA games even at reduced resolutions. The pixel rate of 5.000 GPixel/s and texture rate of 10.00 GTexel/s are simply too low for demanding rasterization.

The DirectX 12 Ultimate (12_2) support is a notable inclusion, but it does not guarantee high performance. Rather, it ensures feature compatibility for applications that require the latest API features. Users targeting AI development, robotics, or edge computing will find the tensor cores and FP16 capabilities more relevant than the graphics pipeline. The end-of-life production status suggests that this is a mature product for existing designs rather than a new purchase recommendation.

FAQ

Q: What is the memory bandwidth of the NVIDIA Jetson Orin Nano 4 GB?

A: The memory bandwidth is 34.11 GB/s, achieved with 4 GB of LPDDR5 memory on a 64-bit bus running at 533 MHz (4.3 Gbps effective).

Q: Does this GPU support modern graphics APIs?

A: Yes, it supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4.

Q: What is the thermal design power of this processor?

A: The TDP is 10 W, which makes it suitable for passively cooled or low-power embedded systems.

Q: How many tensor cores are included?

A: There are 16 tensor cores, which are part of the Ampere architecture's AI acceleration capabilities.

Q: What is the FP32 compute performance?

A: The FP32 performance is 640.0 GFLOPS, with FP16 performance reaching 1,280.0 GFLOPS via a 2:1 ratio.

Q: What is the production status of this product?

A: The production status is listed as end-of-life.

How It Compares

The nearestRivals array in the FACT PACK is empty, so no direct rival comparisons with specific score deltas are available from the data. This absence is itself informative: the Jetson Orin Nano 4 GB occupies a niche that the benchmark database does not currently populate with direct competitors. Its combination of a 10 W TDP, 4 GB LPDDR5, and tensor-core-heavy compute places it in a category where traditional GPU comparisons are less meaningful.

Without rival data, the percentile ranking of 50% against all GPUs serves as the primary comparative anchor. This indicates that while the chip is not a performance outlier, it is also not at the bottom of the database. Its position in the middle of the distribution reflects a design that trades raw graphics throughput for power efficiency and AI functionality, a trade-off that is difficult to quantify with standard gaming benchmarks.

The 200 mm² die size on Samsung's 8 nm process suggests a significant investment in silicon area, which is likely allocated to the tensor cores and AI logic rather than traditional shading units. The 512 shading units are modest in number, but the architecture's efficiency at low power levels is the key differentiator. For users comparing this to other embedded or mobile GPUs, the absence of direct rival scores means that qualitative assessments must rely on the power, memory, and compute specifications listed above.