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Brand Name : OEM
Model Number : YT-64
Place of Origin : China
MOQ : 1pcs
Price : US$55-US$65
Payment Terms : T/T
Supply Ability : 1000PCS/WEEK
Delivery Time : 20 Work days
Packaging Details : white box
CPU : Quad core Cortex-A55 1.8GHZ
NPU : G52 2EE, OpenGL ES1.1/2.0/3.0/3.1/3.2, Vulkan 1.1, OpenCL 2.0
NNIP : NNIP / RK NN / 0.8 Tops
DDR : LP4/LP4x/LP3/DDR4/DDR3L
OS : Android 11
RAM : Nor SFC, SPI Nand, eMMC 5.1, Nand
YT-64 RK3568 Android11 Motherboard
Electrical and Structural Parameters
| CPU | Quad coreCortex-A55 1.8GHZ | 
| GPU | G52 2EE, OpenGL ES1.1/2.0/3.0/3.1/3.2, Vulkan 1.1, OpenCL 2.0 | 
| NNIP | RK NN, 0.8 Tops | 
| DDR | LP4/LP4x/LP3/DDR4/DDR3L | 
| RAM | Nor SFC, SPI Nand, eMMC 5.1, Nand | 
| Video decoder | 4KP60 H.264/H.265/VP9 Profile0 2 | 
| Video encoder | 1080P60 H.264, H.265 | 
| ISP | 8M ISP, HDR | 
| MIPI_CSI | MIPI-CSI2, 1×4-lane/2×2-lane | 
| CIF/DVP | IO: 150MHz, Support BT.656/601/1120 | 
| Display | LVDS/MIPI DSI, HDMI, eDp, Eink | 
| SDIO | SDIO 3.0 x3 | 
| peripheral equipment | USB 2.0 HOST x4, USB2.0 OTG | 
| USB3.0 HOST, Share with 2 Serdes Lanes | |
| UART: 4, SPI: 4, PWM: 16, I2C: 6, SAR-ADC: 4 | |
| Ethernet | GMACx1(10/100/1000M) | 
| audio port | 1x 8chI2S/TDM, 2x2ch I2S | 
| 8ch PDM | |
| SPDIF OUT | 
YT-64 is a motherboard based on Rockchip RK3568, which is independently developed, produced and sold by Shenzhen YECON Technology Co., Ltd.
RK3568 chip from Rockchip is a general-purpose SoC designed for consumer industry applications. The CPU uses a 4-core A55 architecture processor, integrated G52 graphics processor, built-in independent NPU, and runs Android 11 and Linux systems. RK3566 is mainly tailored for consumer products such as tablet computers, speakers with screens, Android laptops, dictionary pens, and industry products such as face payment POS machines, e-books, cloud terminals, video phones, and NAS storage.
 
 RK3568 built-in Rockchip's self-developed NPU, with a hashrate of 0.8 Tops, 512 INT8 MAC 128 INT16/FP16/BFP16 MAC Up to 800MHz. Rockchip also provides developers with a simple and easy-to-use model conversion tool RKNN-Toolkit, which supports one-click conversion of Caffe / TensorFlow / TF-Lite / ONNX / PyTorch / Keras / Darknet mainstream architecture models.
 
  


  
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