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参数 | 参数值 | 操作 |
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商品目录 | 开发平台 |
Basic Parameters | |
SoC | Rockchip RK3399Pro |
GPU | ARM® Mali-T860 MP4 Quad-core GPU Support OpenGL ES1.1/2.0/3.0/3.1, OpenVG1.1, OpenCL, DX11 Support AFBC (frame buffer compression) |
CPU | Dual-core Cortex-A72 up to 1.8GHz Quad-core Cortex-A53 up to 1.4GHz |
NPU |
Support 8bit/16bit operation, computing power up to 3.0TOPS Full load computing power, low load operation power consumption is low Compatible with Caffe/Mxnet/TensorFlow model, support multiclass framework, support mainstream layer type, easy to add a custom layer Provides easy-to-use development tools, PC-based model conversion, performance estimation, and accuracy verification Provide AI application development interface: support Android NN API, provide RKNN cross-platform API, Linux support TensorFlow development; |
VPU |
Support 4K VP9 and 4K 10bits H265/H264 video decoding, up to 60fps 1080P multi-format video decoding (WMV, MPEG-1/2/4, VP8) 1080P video encoding, support H.264, VP8 format Video post processor: de-interlacing, denoising, edge/detail/color optimization |
RAM |
3GB LPDRR3(CPU 2GB + NPU 1GB) |
Flash |
16GB eMMC |
Hardware Characteristics | |
Ethernet | Built-in Gigabit Ethernet PHY chip, 10/100/1000Mbps adaptive |
Camera Interface |
MIPI-CSI×2,Dual camera interface (built-in dual hardware ISP, up to single 13Mpixel or dual 8Mpixel) |
Display Interface | MIPI-DSI eDP DP HDMI (Support 480p/480i/576p/576i/720p/1080p/1080i/4k, support RGB format) |
Audio Port |
I2S0:Support user extended use I2S1:Speaker×1, Headphone×1, MIC×1 |
Type-C | USB3.0/DisplayPort 1.2,OTG |
USB |
USB3.0×1 (according to RK3399Pro design, NPU needs to be mounted on USB3.0, so USB3.0 needs to connect back to NPU, if you need to expand USB3.0 interface, you need external HUB); |
Extension Port |
SDMMC(TF Card)×1; |
Power input | DC 5V |
ECCN | 3A991.a |
HSCODE | 8471504090 |
USHSCODE | 85177000 |
UPC |
Basic Parameters | |
SoC | Rockchip RK3399Pro |
GPU | ARM® Mali-T860 MP4 Quad-core GPU Support OpenGL ES1.1/2.0/3.0/3.1, OpenVG1.1, OpenCL, DX11 Support AFBC (frame buffer compression) |
CPU | Dual-core Cortex-A72 up to 1.8GHz Quad-core Cortex-A53 up to 1.4GHz |
NPU |
Support 8bit/16bit operation, computing power up to 3.0TOPS Full load computing power, low load operation power consumption is low Compatible with Caffe/Mxnet/TensorFlow model, support multiclass framework, support mainstream layer type, easy to add a custom layer Provides easy-to-use development tools, PC-based model conversion, performance estimation, and accuracy verification Provide AI application development interface: support Android NN API, provide RKNN cross-platform API, Linux support TensorFlow development; |
VPU |
Support 4K VP9 and 4K 10bits H265/H264 video decoding, up to 60fps 1080P multi-format video decoding (WMV, MPEG-1/2/4, VP8) 1080P video encoding, support H.264, VP8 format Video post processor: de-interlacing, denoising, edge/detail/color optimization |
RAM |
3GB LPDRR3(CPU 2GB + NPU 1GB) |
Flash |
16GB eMMC |
Hardware Characteristics | |
Ethernet | Built-in Gigabit Ethernet PHY chip, 10/100/1000Mbps adaptive |
Camera Interface |
MIPI-CSI×2,Dual camera interface (built-in dual hardware ISP, up to single 13Mpixel or dual 8Mpixel) |
Display Interface | MIPI-DSI eDP DP HDMI (Support 480p/480i/576p/576i/720p/1080p/1080i/4k, support RGB format) |
Audio Port |
I2S0:Support user extended use I2S1:Speaker×1, Headphone×1, MIC×1 |
Type-C | USB3.0/DisplayPort 1.2,OTG |
USB |
USB3.0×1 (according to RK3399Pro design, NPU needs to be mounted on USB3.0, so USB3.0 needs to connect back to NPU, if you need to expand USB3.0 interface, you need external HUB); |
Extension Port |
SDMMC(TF Card)×1; |
Power input | DC 5V |
ECCN | 3A991.a |
HSCODE | 8471504090 |
USHSCODE | 85177000 |
UPC |
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