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ncnn 小板子

ncnn is a high-performance neural network inference framework.

See https://github.com/Tencent/ncnn for more info about ncnn.

  • The benchmark score is the inference time, less is better.
  • Runs on all cpu big cores or vulkan, and fp16 arithmetic is enabled if supported.
  • Table contents are ordered by mobilenet.
  • rpi5b data from Tencent/ncnn#5058
small-board image spec squeezenet mobilenet shufflenet
NVIDIA Jetson AGX Orin img Ampere 1.3GHz x 2048

Tensor Core x 64		 2.13 2.03 2.57
NVIDIA Jetson AGX Orin img A78AE 2.2GHz x 12 3.50 3.49 5.08
Radxa Rock5B img RK3588

A76 2.4GHz x 4
A55 1.8GHz x 4		 3.65 5.41 3.37
Orange Pi 5 img RK3588S

A76 2.4GHz x 4
A55 1.8GHz x 4		 3.83 5.75 3.57
ZYSJ RK3588 ARM Mali-G610 7.09 9.16 5.88
ZYSJ RK3588 RK3588

A76 2.4GHz x 4
A55 1.8GHz x 4		 7.57 11.01 7.95
Raspberry Pi 5B BCM2712

A76 2.4GHz x 4		 8.56 11.32 4.56
M4N DOCK img AX650

A55 1.7Ghz x 8		 10.61 11.86 10.64
NVIDIA Jetson Nano img Maxwell 921MHz x 128 9.03 15.39 10.61
Khadas VIM4 img ARM Mali-G52

800MHz x MP8(8EE)		 12.77 20.17 12.81
Unisoc Tiger T710 Unisoc Tiger T710

A75 1.82GHz x 4
A55 1.82GHz x 4		 16.25 20.31 10.59
Radxa Rock3A RK3568

A55 2.0GHz x 4		 23.20 30.78 19.49
Khadas VIM3 ARM Mali-G52

800MHz x MP4(6EE)		 19.54 31.62 17.91
Panther X2 RK3566

A55 1.8GHz x 4		 25.91 33.17 21.81
NanoPi M4 ARM Mali-T864 24.57 35.86 33.90
Radxa RockPi X Intel HD Graphics (Cherry Trail) 500 MHz 29.91 36.41 24.54
Khadas VIM4 A311D2

A73 2.2GHz x 4
A53 2.0GHz x 2		 24.27 37.65 19.79
NVIDIA Jetson Nano A57 1.43GHz x 4 28.55 40.25 19.44
Khadas VIM3 A311D

A73 2.2GHz x 4
A53 1.8GHz x 2		 30.98 42.57 21.62
Lichee Pi 4A T-Head TH1520

RV64GCV 2.0GHz x 4		 42.29 47.73 120.13
NanoPi Fire3 S5P6818

A53 1.4GHz x 8		 41.81 52.33 33.54
Debix Model A i.MX8M Plus

A53 1.6GHz x 4		 40.15 54.01 29.33
Odroid XU4 Exynos 5422

A15 2GHz x 4
A7 1.3GHz x 4		 35.73 54.17 25.75
Tinker Board S R2.0 ARM Mali-T764 41.48 60.28 55.87
Radxa Zero S905Y2

A53 1.8GHz x 4		 46.82 60.49 35.18
Raspberry Pi 4B BCM2711B0

A72 1.5GHz x 4		 46.28 60.74 32.91
NanoPi M4 RK3399

A72 1.8GHz x 2
A53 1.5GHz x 4		 43.73 64.28 27.43
BeagleBone AI 64 TDA4VM

A72 2.0GHz x 2		 42.23 65.78 29.97
NanoPi K2 S905

A53 1.5GHz x 4		 56.96 75.25 38.70
Radxa RockPi X Atom x5-Z8350

x86-64 1.92 GHz x 4		 50.22 80.12 37.96
Tinker Board S R2.0 RK3288CGW

A17 1.8GHz x 4		 52.86 82.19 38.17
NanoPi R2S RK3328

A53 1.3GHz x 4		 62.20 82.88 52.34
EAIDK 310 RK3228H

A53 1.3GHz x 4		 61.87 83.88 45.83
Radxa Zero ARM Mali-G31 850 MHz x 2 57.95 98.62 51.71
Raspberry Pi 3B+ BCM2837B0

A53 1.4GHz x 4		 84.74 107.84 58.38
Banana Pi M3 AllWinner A83T

A7 1.8GHz x 8		 88.35 109.72 80.91
MangoPI MQ-Quad AllWinner H616

A53 1.5GHz x 4		 99.60 129.70 66.90
Raspberry Pi Zero 2W BCM2710A1

A53 1.0GHz x 4		 119.52 162.60 72.72
EASY EAI Nano RV1126

A7 1.5GHz x 4		 105.16 163.82 68.79
Radxa RockPi S RK3308

A35 1.3GHz x 4		 142.02 214.56 102.44
StarFive VisionFive V2 SiFive’s U74

RV64GFC 1.5GHz x 4		 150.07 256.21 91.14
RVB-ICE T-Head C910

RV64GC 1.2GHz x 2		 161.10 274.39 118.61
Loongson Pie Lite Loongson 2K1000

GS264 1.0GHz x 2		 185.28 276.03 124.39
Ingenic X2000 Ingenic X2000

XBurst2 1.2GHz x 2		 175.99 282.25 118.4
Raspberry Pi 2B BCM2836

A7 900MHz x 4		 179.50 296.97 132.49
Banana Pi M2 Zero 2 AllWinner H2+

A7 1.2GHz x 4		 218.73 303.92 138.43
Raspberry Pi 4B Broadcom VideoCore VI 286.71 365.04 162.14
PICO-PI-IMX7 i.MX7D

A7 1.0GHz x 2		 220.10 366.92 137.02
Microphase Z7-Lite XC7Z020CLG400

A9 766MHz x 2		 389.18 623.71 212.20
MangoPI MQ-Pro D1 C906

RV64GCV 1GHz x 1		 385.21 691.47 487.67
NeZha D1 D1 C906

RV64GCV 1GHz x 1		 396.18 727.97 495.87
StarFive VisionFive V1 SiFive’s U74

RV64GFC 1.5GHz x 2		 609.41 993.87 358.98
Raspberry Pi B+ ARM1176JZF-S

700MHz x 1		 4285.24 7684.05 2102.22