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-`CPU-RV1126`: [Toybrick RV1126](https://t.rock-chips.com/en/portal.php?mod=view&aid=26), Rockchip RV1126 SoC with a quard-core ARM Cortex-A7 CPU and a 2.0TOPs NPU.
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-`CPU-KVE2`: [Khadas Edge 2](https://www.khadas.com/edge2), Rockchip RK3588S SoC with a CPU of 2.25GHz Quad Core ARM Cortex-A76 + 1.8GHz Quad Core Cortex-A55, and a 6TOPS NPU.
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-`CPU-HSX3`: [Horizon Sunrise X3](https://developer.horizon.ai/sunrise), an SoC from Horizon Robotics with a quad-core ARM Cortex-A53 1.2GHz CPU and a 5TOPS BPU (a.k.a NPU).
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-`CPU-AXP`: [MAIX-III AXera-Pi](https://wiki.sipeed.com/hardware/en/maixIII/ax-pi/axpi.html#Hardware), Axera AX620A with a quad-core ARM Cortex-A7 CPU and a 3.6TOPS@int8 NPU.
-`NPU-KV3`: [Khadas VIM3](https://www.khadas.com/vim3), 5TOPS Performance. Benchmarks are done using **quantized** models. You will need to compile OpenCV with TIM-VX following [this guide](https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU) to run benchmarks. The test results use the `per-tensor` quantization model by default.
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-`NPU-Ascend310`: [Ascend 310](https://e.huawei.com/uk/products/cloud-computing-dc/atlas/atlas-200), 22 TOPS @ INT8. Benchmarks are done on [Atlas 200 DK AI Developer Kit](https://e.huawei.com/in/products/cloud-computing-dc/atlas/atlas-200). Get the latest OpenCV source code and build following[this guide](https://github.com/opencv/opencv/wiki/Huawei-CANN-Backend) to enable CANN backend.
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-`CPU-D1`: [Allwinner D1](https://d1.docs.aw-ol.com/en), [Xuantie C906 CPU](https://www.t-head.cn/product/C906?spm=a2ouz.12986968.0.0.7bfc1384auGNPZ)(RISC-V, RVV 0.7.1) @ 1.0 GHz, 1 core. YuNet is supported for now. Visit [here](https://github.com/fengyuentau/opencv_zoo_cpp) for more details.
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-[Intel Core i7-12700K](https://www.intel.com/content/www/us/en/products/sku/134594/intel-core-i712700k-processor-25m-cache-up-to-5-00-ghz/specifications.html): 8 Performance-cores (3.60 GHz, turbo up to 4.90 GHz), 4 Efficient-cores (2.70 GHz, turbo up to 3.80 GHz), 20 threads.
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-[Raspberry Pi 4B](https://www.raspberrypi.com/products/raspberry-pi-4-model-b/specifications/): Broadcom BCM2711 SoC with a Quad core Cortex-A72 (ARM v8) 64-bit @ 1.5 GHz.
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-[Toybrick RV1126](https://t.rock-chips.com/en/portal.php?mod=view&aid=26): Rockchip RV1126 SoC with a quard-core ARM Cortex-A7 CPU and a 2.0 TOPs NPU.
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-[Khadas Edge 2](https://www.khadas.com/edge2): Rockchip RK3588S SoC with a CPU of 2.25 GHz Quad Core ARM Cortex-A76 + 1.8 GHz Quad Core Cortex-A55, and a 6 TOPS NPU.
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-[Horizon Sunrise X3](https://developer.horizon.ai/sunrise): an SoC from Horizon Robotics with a quad-core ARM Cortex-A53 1.2 GHz CPU and a 5 TOPS BPU (a.k.a NPU).
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-[MAIX-III AXera-Pi](https://wiki.sipeed.com/hardware/en/maixIII/ax-pi/axpi.html#Hardware): Axera AX620A SoC with a quad-core ARM Cortex-A7 CPU and a 3.6 TOPS @ int8 NPU.
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-[NVIDIA Jetson Nano B01](https://developer.nvidia.com/embedded/jetson-nano-developer-kit): a Quad-core ARM A57 @ 1.43 GHz CPU, and a 128-core NVIDIA Maxwell GPU.
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-[Khadas VIM3](https://www.khadas.com/vim3): Amlogic A311D SoC with a 2.2GHz Quad core ARM Cortex-A73 + 1.8GHz dual core Cortex-A53 ARM CPU, and a 5 TOPS NPU. Benchmarks are done using **per-tensor quantized** models. Follow [this guide](https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU) to build OpenCV with TIM-VX backend enabled.
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-[Atlas 200 DK](https://e.huawei.com/en/products/computing/ascend/atlas-200): Ascend 310 NPU with 22 TOPS @ INT8. Follow[this guide](https://github.com/opencv/opencv/wiki/Huawei-CANN-Backend) to build OpenCV with CANN backend enabled.
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-[Allwinner Nezha D1](https://d1.docs.aw-ol.com/en): Allwinner D1 SoC with a 1.0 GHz single-core RISC-V [Xuantie C906 CPU](https://www.t-head.cn/product/C906?spm=a2ouz.12986968.0.0.7bfc1384auGNPZ)with RVV 0.7.1 support. YuNet is tested for now. Visit [here](https://github.com/fengyuentau/opencv_zoo_cpp) for more details.
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