· AI Vision Processor RV1126B
· Deployment of Lightweight AI models
· Built-in 12-Megapixel ISP
· 4K High-Frame-Rate Video Decoding
· Simultaneous Input From 5 cameras
· 38mm × 38mm Mini Size
· Robust Network Capabilities
· Rich Expansion Interfaces
Qwen
Gemma
Phi
MiniCPM
Powered by Rockchip quad-core AI vision processor RV1126B, it integrates 3 TOPS NPU and supports mainstream large AI models and deep learning frameworks. It features a built-in 12MP ISP, an 8MP AI-ISP, and incorporates multiple algorithm accelerators. The SoM supports 12MP video encoding, 4K video decoding, and simultaneous input from 5 cameras.
AI Processor RV1126B
Private Deployment
Built-in 12-Megapixel ISP
4K Video Decoding
Input From 5 Cameras
38mm × 38mm Mini Size
Robust Network Capabilities
Rich Expansion Interfaces
Integrated with a 3 TOPS NPU supporting INT4/INT8/INT16/FP16 hybrid quantization, it maintains compatibility with mainstream deep learning frameworks including TensorFlow, TensorFlow Lite, PyTorch, Caffe, and ONNX. This enables intelligent data processing, voice recognition, and image analysis capabilities, meeting the demands of most edge AI applications in terminal devices.
It is widely applicable in various industry sectors such as facial recognition, access control gates, intelligent security systems, smart network cameras, smart peepholes/doorbells, and dash cams.

ICORE-1126BQ38 |
ICORE-1126BJQ38 |
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Basic Specifications |
SOC |
Rockchip RV1126B |
Rockchip RV1126BJ |
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CPU |
Quad-core 64-bit ARM Cortex-A53, integrated with NEON and FPU, maximum main frequency of 1.6GHz |
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NPU |
3TOPS NPU, supporting INT4/INT8/INT16/FP16 mixed-precision computing |
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ISP |
12MP ISP, 8MP AI-ISP, integrated with multiple algorithm accelerators including HDR, 3A, LSC, 3DNR, 2DNR, sharpening, defogging, fisheye correction, gamma correction, feature point detection, etc. |
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Encoding/ Decoding |
Encoding: Up to 12M@30fps H.264 Decoding: Up to 4K@30fps H.264 |
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RAM |
LPDDR4/LPDDR4X (1GB/2GB/4GB Optional) |
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Storage |
eMMC (8GB/16GB/64GB Optional) |
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Power |
5V (voltage tolerance ±5%) |
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Power consumption |
Normal: 1W(5V/200mA), Max: 3W(5V/600mA), Min(Sleep): 0.2W(5V/40mA) |
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OS |
Debian12, Buildroot+QT |
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Software support |
Supports private deployment of lightweight large language models and multimodal large models with up to 2B parameters under the Transformer architecture, such as small-sized large AI models including the Qwen series, Gemma2-2B, Phi2, InternLM2, MiniCPM series, TinyLLAMA, and RWKV7. Supports deep learning frameworks such as TensorFlow, TensorFlow Lite, PyTorch, Caffe, and ONNX. |
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Interface |
BTB (2 × BTB Socket (100Pin)) |
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Size |
38.0mm × 38.0mm × 5.68mm |
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Weight |
≈9g |
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Environment |
Operating Temperature: -20℃ ~ 60℃, Storage Humidity: 10%~90%RH (non-condensing) |
Operating Temperature: -40℃ ~ 85℃, Storage Humidity: 10%~90%RH (non-condensing) |
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Interface Specifications |
Internet |
One Gigabit Ethernet port can be expanded via the GMAC interface, with FEPHY Fast Ethernet functionality supported. Due to hardware resource limitations, only one of the two Ethernet modes can be selected for use at any given time. TSO (TCP Segmentation Offload) and USO (UDP Segmentation Offload) network acceleration are supported 2.4GHz/5GHz dual-band Wi-Fi and Bluetooth can be expanded via the SDIO 3.0 interface 4G/3G networks can be expanded via the USB interface |
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Video input |
2 × (MIPI-CSI/LVDS/Sub LVDS) DPHY - 4 Lanes per DPHY group (1×4 Lanes or 2×2 Lanes) - 2.5 Gbps per Lane 1 × DVP (BT.601/BT.656/BT.1120) *A maximum of 5 cameras can be supported for concurrent input via the above interfaces |
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Video output |
1 × MIPI-DSI (1080P@60Hz, 1×4lanes) Supports BT.656/BT.1120 interfaces Supports MCU/RGB LCD interfaces, with a maximum of 24 bits |
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Audio |
1 × SAI (4T/4R), 1 × SAI (1T/1R), 1 × SAI (1T/3R), supporting I2S/TDM/PCM audio protocols PDM and Audio Codec support a sampling rate of up to 192KHz |
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USB |
1 × USB2.0 HOST, 1 × USB3.0 DRD |
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Others |
2 × SPI, 8 × UART, 5 × I2C, 2 × CAN, 27 × PWM, GPIOs, 1 × SDMMC, 1 × SDIO3.0, 3 × SARADC |
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