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NVIDIA Jetson Orin Nano 4 GB

NVIDIA graphics card specifications and benchmark scores

4 GB
VRAM
MHz Boost
10W
TDP
64
Bus Width
🤖Tensor Cores

NVIDIA Jetson Orin Nano 4 GB Specifications

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Jetson Orin Nano 4 GB GPU Core

Shader units and compute resources

The NVIDIA Jetson Orin Nano 4 GB GPU core specifications define its raw processing power for graphics and compute workloads. Shading units (also called CUDA cores, stream processors, or execution units depending on manufacturer) handle the parallel calculations required for rendering. TMUs (Texture Mapping Units) process texture data, while ROPs (Render Output Units) handle final pixel output. Higher shader counts generally translate to better GPU benchmark performance, especially in demanding games and 3D applications.

Shading Units
512
Shaders
512
TMUs
16
ROPs
8
SM Count
4
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Jetson Orin Nano 4 GB Clock Speeds

GPU and memory frequencies

Clock speeds directly impact the Jetson Orin Nano 4 GB's performance in GPU benchmarks and real-world gaming. The base clock represents the minimum guaranteed frequency, while the boost clock indicates peak performance under optimal thermal conditions. Memory clock speed affects texture loading and frame buffer operations. The Jetson Orin Nano 4 GB by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.

GPU Clock
625 MHz
Memory Clock
533 MHz 4.3 Gbps effective
GDDR GDDR 6X 6X

NVIDIA's Jetson Orin Nano 4 GB Memory

VRAM capacity and bandwidth

VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Jetson Orin Nano 4 GB's memory capacity determines how well it handles high-resolution textures and multiple displays. Memory bandwidth, measured in GB/s, affects how quickly data moves between the GPU and VRAM. Higher bandwidth improves performance in memory-intensive scenarios like 4K gaming. The memory bus width and type (GDDR6, GDDR6X, HBM) significantly influence overall GPU benchmark scores.

Memory Size
4 GB
VRAM
4,096 MB
Memory Type
LPDDR5
VRAM Type
LPDDR5
Memory Bus
64 bit
Bus Width
64-bit
Bandwidth
34.11 GB/s
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Jetson Orin Nano 4 GB by NVIDIA Cache

On-chip cache hierarchy

On-chip cache provides ultra-fast data access for the Jetson Orin Nano 4 GB, reducing the need to fetch data from slower VRAM. L1 and L2 caches store frequently accessed data close to the compute units. AMD's Infinity Cache (L3) dramatically increases effective bandwidth, improving GPU benchmark performance without requiring wider memory buses. Larger cache sizes help maintain high frame rates in memory-bound scenarios and reduce power consumption by minimizing VRAM accesses.

L1 Cache
128 KB (per SM)
L2 Cache
256 KB
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Jetson Orin Nano 4 GB Theoretical Performance

Compute and fill rates

Theoretical performance metrics provide a baseline for comparing the NVIDIA Jetson Orin Nano 4 GB against other graphics cards. FP32 (single-precision) performance, measured in TFLOPS, indicates compute capability for gaming and general GPU workloads. FP64 (double-precision) matters for scientific computing. Pixel and texture fill rates determine how quickly the GPU can render complex scenes. While real-world GPU benchmark results depend on many factors, these specifications help predict relative performance levels.

FP32 (Float)
640.0 GFLOPS
FP64 (Double)
320.0 GFLOPS (1:2)
FP16 (Half)
1,280.0 GFLOPS (2:1)
Pixel Rate
5.000 GPixel/s
Texture Rate
10.00 GTexel/s

Jetson Orin Nano 4 GB Ray Tracing & AI

Hardware acceleration features

The NVIDIA Jetson Orin Nano 4 GB includes dedicated hardware for ray tracing and AI acceleration. RT cores handle real-time ray tracing calculations for realistic lighting, reflections, and shadows in supported games. Tensor cores (NVIDIA) or XMX cores (Intel) accelerate AI workloads including DLSS, FSR, and XeSS upscaling technologies. These features enable higher visual quality without proportional performance costs, making the Jetson Orin Nano 4 GB capable of delivering both stunning graphics and smooth frame rates in modern titles.

Tensor Cores
16
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Ampere Architecture & Process

Manufacturing and design details

The NVIDIA Jetson Orin Nano 4 GB is built on NVIDIA's Ampere architecture, which defines how the GPU processes graphics and compute workloads. The manufacturing process node affects power efficiency, thermal characteristics, and maximum clock speeds. Smaller process nodes pack more transistors into the same die area, enabling higher performance per watt. Understanding the architecture helps predict how the Jetson Orin Nano 4 GB will perform in GPU benchmarks compared to previous generations.

Architecture
Ampere
GPU Name
GA10B
Process Node
8 nm
Foundry
Samsung
Die Size
200 mm²
🔌

NVIDIA's Jetson Orin Nano 4 GB Power & Thermal

TDP and power requirements

Power specifications for the NVIDIA Jetson Orin Nano 4 GB determine PSU requirements and thermal management needs. TDP (Thermal Design Power) indicates the heat output under typical loads, guiding cooler selection. Power connector requirements ensure adequate power delivery for stable operation during demanding GPU benchmarks. The suggested PSU wattage accounts for the entire system, not just the graphics card. Efficient power delivery enables the Jetson Orin Nano 4 GB to maintain boost clocks without throttling.

TDP
10 W
TDP
10W
📐

Jetson Orin Nano 4 GB by NVIDIA Physical & Connectivity

Dimensions and outputs

Physical dimensions of the NVIDIA Jetson Orin Nano 4 GB are critical for case compatibility. Card length, height, and slot width determine whether it fits in your chassis. The PCIe interface version affects bandwidth for communication with the CPU. Display outputs define monitor connectivity options, with modern cards supporting multiple high-resolution displays simultaneously. Verify these specifications against your case and motherboard before purchasing to ensure a proper fit.

Slot Width
IGP
Length
70 mm 2.8 inches
Height
45 mm 1.8 inches
Bus Interface
PCIe 4.0 x4
Display Outputs
Portable Device Dependent
Display Outputs
Portable Device Dependent
🎮

NVIDIA API Support

Graphics and compute APIs

API support determines which games and applications can fully utilize the NVIDIA Jetson Orin Nano 4 GB. DirectX 12 Ultimate enables advanced features like ray tracing and variable rate shading. Vulkan provides cross-platform graphics capabilities with low-level hardware access. OpenGL remains important for professional applications and older games. CUDA (NVIDIA) and OpenCL enable GPU compute for video editing, 3D rendering, and scientific applications. Higher API versions unlock newer graphical features in GPU benchmarks and games.

DirectX
12 Ultimate (12_2)
DirectX
12 Ultimate (12_2)
OpenGL
4.6
OpenGL
4.6
Vulkan
1.4
Vulkan
1.4
OpenCL
3.0
CUDA
8.7
Shader Model
6.8
📦

Jetson Orin Nano 4 GB Product Information

Release and pricing details

The NVIDIA Jetson Orin Nano 4 GB is manufactured by NVIDIA as part of their graphics card lineup. Release date and launch pricing provide context for comparing GPU benchmark results with competing products from the same era. Understanding the product lifecycle helps evaluate whether the Jetson Orin Nano 4 GB by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.

Manufacturer
NVIDIA
Launch Price
199 USD
Production
End-of-life

Jetson Orin Nano 4 GB Benchmark Scores

📊

No benchmark data available for this GPU.

About NVIDIA Jetson Orin Nano 4 GB

The NVIDIA Jetson Orin Nano 4 GB arrives at a launch price of $199 USD, positioning it as one of the most affordable AI edge modules on the market. At this price point, the cost per gigabyte of LPDDR5 memory drops to roughly $50, which is competitive against both legacy and contemporary development boards. The 10‑W TDP further reduces operational expenses by limiting power‑supply requirements and cooling infrastructure. For small‑scale deployments, the low upfront cost enables rapid prototyping without a significant capital outlay. Enterprises can also benefit from the modest price when scaling dozens of units, as bulk purchasing discounts often apply. Overall, the pricing strategy makes the board attractive for budget‑conscious projects that still demand modern Ampere‑based performance.

In the current AI hardware landscape, the Orin Nano occupies the low‑to‑mid tier, bridging the gap between hobbyist platforms and high‑end industrial modules. Its 8 nm Ampere GPU core delivers sufficient CUDA cores for real‑time inference on lightweight models such as YOLO‑v5s or MobileNet‑V3. The PCIe 4.0 x4 interface provides ample bandwidth for external accelerators, yet the board remains compact enough for embedded enclosures. Compared with the larger Jetson AGX series, the Nano’s reduced power envelope and smaller form factor target edge devices like smart cameras, drones, and portable robots. The 4 GB of LPDDR5 memory is adequate for most vision and sensor‑fusion workloads, though it may limit very large transformer models. Consequently, the device is best suited for developers who need a balance of performance, size, and cost without the overhead of enterprise‑grade hardware.

From an investment perspective, the NVIDIA Jetson Orin Nano 4 GB offers a compelling total cost of ownership over its lifecycle. Its low power draw translates to reduced electricity bills, especially in deployments that run continuously 24/7. The mature JetPack SDK and extensive software ecosystem shorten development cycles, lowering labor costs. Because the module is supported by a wide range of pre‑trained models, teams can leverage transfer learning rather than building solutions from scratch. The board’s compatibility with standard Linux tools also protects against vendor lock‑in, preserving flexibility for future upgrades. When factoring in hardware, energy, and development expenses, the Orin Nano presents a strong ROI for projects that require on‑device AI without excessive overhead.

To maximize the capabilities of the NVIDIA Jetson Orin Nano 4 GB, pairing it with complementary peripherals is essential. A high‑resolution MIPI‑CSI camera coupled with a dedicated image signal processor can feed the GPU with rich visual data for object detection tasks. Adding a compact SSD via the PCIe 4.0 lane provides fast local storage for model checkpoints and dataset caching. For robotics applications, integrating an IMU and motor driver board through the GPIO header enables closed‑loop control with minimal latency. A lightweight heatsink with a fan, sized for the 10 W TDP, ensures thermal stability during sustained inference bursts. Finally, consider a power‑over‑Ethernet (PoE) injector to simplify cabling in remote installations, allowing the module to operate autonomously in the field.

  1. 4K MIPI‑CSI camera module with ISP support
  2. NVMe SSD utilizing the PCIe 4.0 x4 interface
  3. Active cooling solution (low‑profile heatsink plus fan)
  4. PoE power injector and breakout board for

The AMD Equivalent of Jetson Orin Nano 4 GB

Looking for a similar graphics card from AMD? The AMD Radeon RX 7700 offers comparable performance and features in the AMD lineup.

AMD Radeon RX 7700

AMD • 16 GB VRAM

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