
Want an SBC that can run heavy AI inference, host fast NVMe storage, and act as a compact workstation, all on one board?
The upcoming Orange Pi 6 Plus ARM development board marks a major step forward for the Orange Pi team, introducing a powerful new development board built around a 12-core ARM processor. Designed to appeal to both hobbyists and industry professionals, it brings a significant boost in performance and flexibility, ideal for modern DIY builds and embedded system projects. A key highlight is its integrated 30-TOPS NPU, which positions the board as a strong choice for AI-driven edge computing.
What further sets the Orange Pi 6 Plus apart is its advanced SoC engineered by CIX Technology, an emerging semiconductor company in China. Although not yet widely known, CIX is backed by a highly experienced engineering team with over two decades of expertise, making the company and its innovations, worth watching closely as it gains momentum in the industry.
Why the OrangePi 6 Plus Matters?
The OrangePi 6 Plus packs a 12-core CIX family SoC, LPDDR5 memory up to 64GB, dual M.2 NVMe slots, and a dedicated NPU rated in vendor materials up to 45 TOPS (system / combined figures). That hardware places it in the class of ARM SBC for AI edge computing designed for On-device AI, compact workstations, and multi-camera/edge-server use cases.
Orange Pi 6 Plus ARM Development Board Hardware Overview
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CPU |
12-core 64-bit processor |
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NPU |
28.8Tops |
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GPU |
Integrated graphics processor |
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Combined Computing Power |
45TOPS(CPU+NPU+GPU) |
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RAM |
LPDDR5: 128-bit x 32;16GB/32GB /64GB |
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Storage Expansion |
• SPI FLASH: 64Mbit |
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Wi-Fi Module |
M.2 KEY-E socket |
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PCIE Ethernet |
5G Ethernet*2 |
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USB |
• USB 3.0 HOST *2 |
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Camera Interface |
2*4-lane MIPI CSI camera interface |
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Display Interface |
• 1*DP1.4 4K@120HZ |
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Audio |
3.5mm headphone jack audio input/output, speakers*2, analog MIC*1 |
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TYPE-C Port Power Supply |
Type-C PD 20V IN*2, standard 100W |
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Expansion Interface |
40-pin function expansion interface, supporting the following interface types: |
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Indicator Light |
Power-on indicator, system indicator, battery charging indicator |
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Button |
1* Power button, 1* BOOT button, 1* RESET button |
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Fan Interface |
1* Fan connector with PWM control |
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Reserved Interface |
Board-to-board battery connector; 2-pin RTC connector |
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Power Adapter |
Type-C PD 20V input, standard 100W |
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Operating System |
Debian, Ubuntu, Android, Windows, ROS2 |
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Appearance Dimensions |
115*100mm |
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Weight |
132g |
Core Silicon (SoC)
- SoC family: CIX CD8180 / CD8160 series (CIX / CD8xxx family).
- CPU: 12-core ARM64 configuration (mix of newer high-performance cores + efficiency cores) designed for high single-thread and multi-thread throughput.
Memory & Storage
- RAM: LPDDR5 (128-bit bus), available in SKU options such as 16 GB, 32 GB, and up to 64 GB. LPDDR5 delivers much higher bandwidth than LPDDR4(X), which benefits GPU/NPU and data-intensive workloads.
- Storage: Two M.2 2280 NVMe slots (PCIe) on many SKUs plus eMMC socket and microSD for flexible system storage and ultra-fast SSD options.
AI & GPU
- NPU: Vendor and press materials advertise up to ~30 TOPS for the NPU alone and system figures up to ~45 TOPS in combined metrics (NPU + GPU + DSP), depending on precision and measurement. This is a meaningful step for on-device AI workloads.
- GPU: Modern Arm-class GPU (Immortalis-class on related chips reported) with modern API support (Vulkan/OpenGL ES), making it suitable for GPU-accelerated compute and desktop composition.
The glmark2 benchmark is a valuable tool for evaluating OpenGL ES 2.0 performance on systems running the Wayland display server. It measures how well a device handles essential graphics workloads, including vertex processing, texture management, and shader execution. This makes it especially useful for developers optimizing graphics performance on embedded systems and Linux-based devices. In our hands-on testing, the Orange Pi 6 Plus delivered impressive results, achieving a glmark2-wayland score of 1105 and an exceptional 5851 in the glmark2-es2-wayland test—clear indicators of its strong GPU capabilities.
I/O and Networking
- Ethernet: Options include multi-gigabit connectivity, vendor pages and previews cite Dual 5GbE on some configurations (great for NAS, multi-stream AI data ingestion and low-latency networks).
- USB & Display: The board offers an impressive range of display output options, including HDMI, DisplayPort, USB-C with DP Alt Mode, and eDP—capable of delivering stunning 4K at 120Hz visuals via DisplayPort.
- Other: 40-pin GPIO, fan connector, RTC header, and expansion slots common to Orange Pi family boards.
OrangePi 6 Plus Benchmark Technical Deep Dive (What these specs mean in practice?)
CPU Design & Performance Expectations
The CIX CD8180 is a high-performance 12-core Armv9.2 processor developed by CIX Technology, a Chinese semiconductor company specializing in AI-focused and edge-computing SoCs. It uses a tri-cluster architecture featuring 4 Cortex-A720 “Big” cores (up to 2.8 GHz), 4 Cortex-A720 “Medium” cores (up to 2.4 GHz), and 4 Cortex-A520 “LITTLE” cores (up to 1.8 GHz), providing an efficient balance between performance and power consumption. The chip includes an Arm Immortalis-G720 MC10 GPU with hardware ray tracing and support for Vulkan 1.3, OpenGL ES 3.2, and OpenCL 3.0. Complementing this is a robust 30-TOPS NPU that supports INT4/8/16, FP16, and TF32 precision, making it highly capable for modern AI workloads.
Power Consumption
Idle Power Consumption: The board typically uses 5–7 watts when idle, depending on attached peripherals and background activity.
Moderate Workloads: During everyday tasks—such as web browsing or light AI inference—power usage generally falls between 10–15 watts.
Peak Usage: Under maximum CPU, GPU, and NPU load, especially when running NVMe storage or dual Ethernet, consumption can reach 18–20 watts.
Power Requirements: The Orange Pi 6 Plus is powered via USB-C Power Delivery, and a 20W or higher power adapter is recommended to ensure stable performance.
edge AI computing SBC Note: Benchmarks published in early hands-on previews and community tests show the board is competitive with other top SBCs for single-thread tasks and often excels in multi-threaded workloads when paired with adequate cooling.
Memory Bandwidth & Why LPDDR5 Matters?
LPDDR5 increases memory bandwidth and reduces latency vs LPDDR4(X). For workloads that shuttle large tensors or frames between NPU/GPU/CPU (e.g., vision pipelines, LLM embeddings), that bandwidth is often the bottleneck — so LPDDR5 gives measurable gains in throughput and reduced stalls. If you plan to run large models or many parallel vision streams, the high RAM ceiling (up to 64 GB) is a standout feature.
NPU and On-device AI: Realistic Expectations
Marketing TOPS numbers vary depending on precision (INT4/8, FP16, etc.) and whether the figure is NPU alone or a combined system value. Practical considerations:
- Model format & conversion required: Many models need quantization (INT8/INT4) or conversion to vendor runtimes to hit peak NPU throughput. Community tools and runtimes are evolving.
- Use cases: The board can handle object detection, segmentation, and many smaller transformer models for embeddings or low-latency responses on the edge. For very large LLMs, the limiting factors are model size and runtime support rather than raw TOPS alone.
The Orange Pi 6 Plus features a powerful NPU capable of delivering 30 TOPS, dramatically improving both AI development and on-device deployment. It supports a wide range of mainstream AI models, making it well-suited for edge-based generative AI workloads such as chatbots, coding assistants, and real-time intelligent applications.
In terms of AI capability, the board is often compared to the AMD Ryzen AI 9 HX 370, as both platforms reach up to 45 TOPS when leveraging their combined AI engines—allowing advanced models to run locally with high efficiency. Paired with the Arm Immortalis-G720 MC10 GPU, the Orange Pi 6 Plus also provides high-end graphics performance, including 8K video decoding and hardware-accelerated ray tracing, making it an excellent choice for demanding multimedia and graphics-intensive tasks.
Storage and I/O in Real Deployments
Dual NVMe slots let you build compact, high-IOPS NAS/DB nodes or host databases and container images locally with low latency. Combined with multi-gigabit Ethernet, the 6 Plus can operate as a small, fast edge server or inference appliance. This combination of NVMe + multi-GbE is rare on SBCs and a key differentiator vs older Orange Pi models and many competitors.
Software & Community (Maturity and Compatibility)
- OS support: Early images for Debian/Ubuntu and Android are being published; community ports and kernel work are ongoing. Expect active community development but anticipate some early-adopter quirks (driver refinements, firmware updates) while mainline support grows.
- AI toolchain: Tooling to convert and optimize models for the NPU will be necessary. Users on community forums report early experiments with model conversion and runtime integration; expect growing documentation in the months after launch.
ARM SBC for AI edge computing Typical Use Cases
Great fit for:
- Edge AI developers (real-time vision, inference appliances) who need local NPU acceleration.
- Makers building compact servers, NVMe-backed storage appliances, or multi-camera robotics.
- Developers wanting a powerful Linux desktop SBC for compiling code, running containers, or lightweight virtualization.
Not the best fit for:
- Users who need a plug-and-play, extensively battle-tested platform without tinkering — early adopters will face software polishing steps.
ARM Dev Board for AI Real-world Notes & Early reports
- Early reviewers and community testers report that the board performs well in synthetic and some real workloads, but sustained multi-core/NPU throughput benefits from active cooling.
- The NPU’s real-world effectiveness depends on runtime support and model conversion — which is improving but still maturing in community toolchains.
OrangePi 6 Plus Pros & Cons
Pros
- High AI compute potential: Vendor/system figures advertise up to 45 TOPS (combined); NPU alone commonly cited around 30 TOPS — great for edge inference.
- Large, fast RAM: LPDDR5 support and high SKUs up to 64 GB enable large models, heavy multitasking and memory-hungry workloads.
- Dual NVMe + multi-GbE: Two M.2 2280 NVMe slots and dual 5 GbE options enable compact, high-IOPS storage solutions and fast networked inference.
- Modern GPU & display I/O: Modern GPU APIs (Vulkan, OpenGL ES) and robust display outputs — good for GPU-accelerated tasks and desktop use.
- Solid CPU core count: 12 cores give strong parallel compute for server-style and workstation tasks.
Cons
- Early software maturity: As a new platform with a newer SoC family, mainline kernel support, optimized runtimes, and community docs are still arriving, expect early-adopter work.
- Power & thermal demands: For best sustained performance on CPU and NPU, active cooling (fan + heatsink) is recommended. Expect higher power draw under load.
- Marketing TOPS vs real throughput: TOPS numbers are useful but depend heavily on precision, model format, and runtime real gains require model optimization.
- Price & availability variability: Advanced SKUs (large RAM, bundled accessories) carry a premium and availability may vary by region and seller.
Real-World Performance Comparison: Orange Pi 6 Plus vs Raspberry Pi 5
1. Performance (CPU & Throughput)
Orange Pi 6 Plus
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The 6 Plus uses a 12-core CIX (CD8180 / CD8160) SoC with a mix of Cortex-A720 and A520 cores.
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According to CNX Software, it’s built on a 6 nm process and offers high-performance CPU, GPU, and NPU.
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Graphics benchmarks: according to AndroidPimp, glmark2-wayland score is ~1,105, and glmark2-es2-wayland is ~5,851 — indicating strong GPU performance.
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AI performance: up to 45 TOPS total (CPU + GPU + NPU) for model inference.
Raspberry Pi 5
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The Pi 5 uses a Broadcom BCM2712 CPU with 4× Cortex-A76 cores @ 2.4 GHz.
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In a real review, CNX-Software measured memory bandwidth, throughput, and other benchmarks using their sbc-bench suite.
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No dedicated high-TOPS NPU on Pi 5 — it’s not designed for heavy on-device AI inference.
Summary point: The Orange Pi 6 Plus has significantly higher raw compute potential, especially for multi-threaded and AI workloads. The Pi 5 is more traditional compute-oriented and less focused on AI inference.
2. AI / Inference Workloads
Orange Pi 6 Plus
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The NPU provides up to 30 TOPS, and combined with GPU + CPU, total AI throughput is claimed up to 45 TOPS.
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Supported precisions: INT4, INT8, INT16, FP16, BF16, TF32.
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With this much AI power, it’s suitable for on-device inference of vision models, LLM embeddings, or other AI workloads that require local compute.
Raspberry Pi 5
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The Pi 5 does not have a dedicated high-performance NPU. Inference on Pi 5 is therefore limited to CPU/GPU or external accelerators.
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There are academic experiments: for example, a paper deployed a quantized YOLOv4-Tiny model on the Pi 5 and measured inference times and power.
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Because of this, Pi 5 is more suited for lightweight AI use or as a development platform when using external AI hardware.
Summary point: For serious on-device AI inference, the 6 Plus has a clear advantage. The Pi 5 is more limited without external AI acceleration.
3. Power Consumption & Efficiency
Orange Pi 6 Plus
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According to AndroidPimp’s hardware overview, idle power draw is around 5–7 W, depending on attached peripherals.
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Under moderate load (e.g., light inference or SSD usage), power consumption can go up to 10–15 W.
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Under full load (CPU + NPU + NVMe + network), peak power can reach 18–20 W, per the same source.
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Requires a beefy power supply: the board supports USB-C PD, and a 20 V or similarly powerful adapter is recommended.
Raspberry Pi 5
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In the CNX-Software review, idle power consumption is quite low: ~3.0 W (headless) to ~3.6 W (with peripherals).
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Under a 4-core stress test, Pi 5’s measured power consumption was around 8.8 W.
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In a heavier combined workload (4K video + external SSD + stress test), it can go up to ~16.8 W per tests.
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Pi 5 runs hot: Tom’s Hardware measured thermal throttling — under load, it reached ~86.7 °C and the CPU scaled down to reduce temperature.
Summary point: The Pi 5 is very power efficient when idle but can draw significant power under heavy load; the 6 Plus draws more overall but gives far greater performance per watt when doing AI or data-heavy workloads.
4. Real-World Use Case Implications
For Edge AI / Inference / Robotics
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With high AI throughput (45 TOPS), the Orange Pi 6 Plus is very well-suited for on-device AI, robotics, computer vision, and applications that benefit from running models locally rather than relying on the cloud.
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Its power draw under load is higher, so use in battery-powered or power-constrained environments requires careful design (good PSU, possibly power management).
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The dual NVMe slots also allow for very fast local storage of models and data.
For Maker / General-Purpose Use
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The Raspberry Pi 5 excels in general development, education, media projects, and typical maker applications.
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For AI on Pi 5, you’d likely use quantized models or external accelerators (e.g., USB NPUs) because the built-in CPU/GPU capacity is limited.
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The Pi 5’s lower idle power makes it ideal for always-on tasks, small servers, IoT gateways, or retro computing where efficiency is more important than raw AI performance.
Verdict on Performance + AI + Power
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Compute & AI: The Orange Pi 6 Plus wins hands-down for raw compute power and on-device AI inference. Its 12-core CPU, powerful NPU, and high memory bandwidth make it a top choice for AI-heavy workflows.
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Energy Efficiency (idle): The Raspberry Pi 5 is more efficient when doing lighter tasks — great for low-power projects.
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Power Budget for AI Projects: If you’re building an AI edge device or local inference box, the Orange Pi 6 Plus is very compelling — just plan for a strong power supply and good cooling.
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Ease of Use & Ecosystem: The Pi 5 benefits from Raspberry Pi’s mature ecosystem, whereas the 6 Plus may require more work to fully leverage its AI capabilities.
Conclusion:
If your next project needs on-device AI acceleration, high memory capacity, NVMe storage, and multi-gigabit networking in a single SBC, the OrangePi 6 Plus is one of the most capable boards available today. It’s particularly compelling for edge-AI deployments, robotics, and compact NAS/edge-server use cases.
If you prefer maximum out-of-the-box software stability with long community history, you may prefer to wait a short while for the platform to mature — but if you’re comfortable with early-adopter tasks and want top-tier hardware on a single board, the 6 Plus is worth exploring.
FAQs:
- What makes the Orange Pi 6 Plus different from previous Orange Pi models?
The Orange Pi 6 Plus introduces a significant leap in performance thanks to its 12-core Armv9.2 CPU, Immortalis-G720 MC10 GPU, and 30-TOPS NPU—none of which were available in earlier models. It also offers LPDDR5 RAM up to 64GB, dual NVMe SSD slots, and dual 5GbE Ethernet, making it suitable for high-end AI workloads, edge computing, and small-form-factor servers. This is the most powerful and AI-focused Orange Pi board to date.
- Can the Orange Pi 6 Plus run large AI models locally without cloud access?
Yes. With its 30-TOPS NPU and high-bandwidth LPDDR5 memory, the Orange Pi 6 Plus is designed for on-device AI processing. It can efficiently run quantized LLMs, computer vision models, and generative AI pipelines without relying on cloud services. This allows for lower latency, improved privacy, and real-time inference—ideal for robotics, automation, and offline AI assistants.
- How does the GPU on the Orange Pi 6 Plus compare to typical ARM SBC GPUs?
The board’s Arm Immortalis-G720 MC10 GPU is far more advanced than the GPUs found in most Raspberry Pi or older Orange Pi boards. It supports hardware-accelerated ray tracing, 8K video decoding, and modern APIs such as Vulkan 1.3 and OpenGL ES 3.2. This makes it capable of handling demanding 3D workloads, high-resolution media playback, and GPU-accelerated compute tasks.
Sources & further reading:
Basic specs and official info: Orange Pi product page. orangepi.org
Hands-on press and initial pricing: CNX-Software, Liliputing. CNX Software – Embedded Systems News+1
Technical coverage & NPU detail: Golem, Notebookcheck. golem.de+1










