AIO-3399C (AI Version)
T-ChipThe AIO-3399C (AI Version) is based on a Rockchip RK3399 SoC and a quad-core Mali-T860 GPU, and includes a modular neural deep-learning accelerator NPU with no external buffer memory needed. It has strong peak power and super high performance, supports Pytorch, Caffe deep-learning framework, and provides complete and user-friendly model training tools and web training model cases, enabling it to be rapidly used for mobile edge computing, smart home devices, facial recognition, AI server, etc.
📅 Added on January 25, 2019
🔗 Official website
🛠️ Edit source (see our guide)
Hardware Specifications (Start Comparison)
| Manufacturer | T-Chip |
|---|---|
| SoC | Rockchip RK3399 |
| CPU |
2× ARM Cortex-A72 @
2.0Ghz
4× ARM Cortex-A53 @ 1.5Ghz |
| GPU | 4× Mali-T860 MP4 600Mhz |
| RAM | 4.0 GiB LPDDR4 |
| eMMC | 1× soldered |
| SD | 1× SD slot bootable |
| USB |
1× host port
1x USB-OTG
|
| Ethernet | 1× 1 Gbps |
| Wi-Fi |
On-board Wi-Fi without external antenna 2.4Ghz b/g/n 5Ghz a/n/ac |
| Bluetooth |
On-board Bluetooth (4.2)
|
| Video interfaces |
1×
HDMI
|
| Display I/O | - |
| Audio |
1× audio output
1× line-in
1× microphone-in
|
| Camera I/O | 2× camera interfaces |
| GPIOs | - |
| Pin Header | none / custom |
| Embedded I/O | - |
| Generic Peripherals | - |
Physical Aspects
| Power Requirements |
12.0
V DC
2.0A
|
|---|---|
| Battery | - |
| Dimensions | 126mm x 91mm |
| Form Factor | Unknown |
| Mounting holes | No |
Software
| Linux |
Yes
|
|---|---|
| Android | - |
| Windows | - |
Certifications and conformity
(No information available)
Links
Add any links to relevant datasheets and schematics here.No links were added yet.
Availability
The reference price is (US) $139.0For purchase information, please refer to the official website .
