CAM-3576Q38 38mm Mini Single Board Computer

CAM-3576Q38 38mm Mini Single Board Computer

$199.00

Taxes included. Shipping calculated at checkout.

Spec:Commercial (CAM-3576Q38) Commercial (CAM-3576Q38) Industrial (CAM-3576JQ38) Automotive (CAM-3576MQ38)

Storage:4G RAM+64G ROM 4G RAM+64G ROM 4G RAM+32G ROM

Manual WikiDownload

Brand Firefly

Availability

5 in stock

CAM-3576Q38 Mini AI SBC

Featuring the Rockchip octa-core 64-bit AIoT processor RK3576, it integrates a 6 TOPS computing NPU and supports the private deployment of mainstream large AI models as well as various deep learning frameworks. It also supports 4K@120fps decoding, 4K@60fps encoding, and delivers 4K@120fps high-definition, high-frame-rate display capabilities.

Al Processor RK3576

Features the octa-core 64-bit high-performance AIoT processor RK3576, utilizing a big.LITTLE architecture with a main frequency of up to 2.2GHz. Equipped with the Mali-G52 MC3 GPU, its 145 GFLOPS performance enables efficient heterogeneous computing, providing robust support for high-performance computing and multitasking.

Private Deployment

Supports private deployment of ultra-large-scale parameter models based on the Transformer architecture, such as the Gemma series, ChatGLM series, Qwen series, Phi series, and other large language models.

8K Viede Decoding

Supports 8K@30fps / 4K@120fps (VP9, AVS2, AV1) and 4K@60fps video decoding (H.264/AVC), as well as 4K@60fps video encoding (H.264/AVC).

Built-in 16-megapixel ISP

Built-in 16-megapixel ISP with support for low-light noise reduction, RGB-IR sensors, and up to 120dB HDR. AI-ISP enhances image quality in low-noise conditions. Supports MIPI-CSI input.

38 x 38mm mini size

CAM-3576Q38 measures a mere 38 × 38 × 11.5 mm. With its ultra-compact design, it can be seamlessly integrated into smart cameras, surveillance systems, and other space-constrained devices, freeing up valuable internal space for core components while significantly improving overall integration and space utilization.

Multiple Operating Systems

Equipped with a variety of expansion interfaces including Fast Ethernet, MIPI-CSI, USB 2.0, Type-C, RS485, ADC, I2C, UART, and MIC, meeting peripheral expansion requirements across diverse application scenarios.

Rich Expansion Interfaces

Supports an RTLinux kernel with excellent real-time performance, making it widely suitable for industrial applications. It is compatible with Linux OS, and Buildroot, providing a secure and stable system environment for product development and manufacturing.

Development Materials

Includes complete source code, tutorials, technical documentation, and development tools, enabling users to efficiently perform secondary development and quickly create independently controllable products.

6 TOPS NPU Computing Power

Built-in powerful NPU with computing power of up to 6 TOPS, supporting INT4/INT8/INT16/FP16/BF16/TF32 mixed operations. Dual-core collaboration or independent operation, and parallel multi-tasking across diverse scenarios.Capable of intelligent data processing, voice recognition, and image analysis, meeting the edge computing AI application needs of most terminal devices.

Application Scenarios

Widely applicable to edge computing, private deployment of large models, smart cameras, intelligent security, automotive electronics, dashcams, and other application fields.

Edge Computing

Private Deployment of Large Models

Smart Camera

Intelligent Security

Automotive Electronics

Dash Cams

Interfaces

Specifications

CAM-3576Q38
Basic Specifications	SOC	CAM-3576Q38: Rockchip RK3576 CAM-3576JQ38: Rockchip RK3576J CAM-3576MQ38: Rockchip RK3576M
	CPU	CAM-3576Q38: Octa-core 64-bit processor (4×A72 + 4×A53) with a maximum frequency of 2.2GHz CAM-3576JQ38/3576MQ38: Octa-core 64-bit processor (4×A72 + 4×A53) with a maximum frequency of 1.6GHz
	GPU	G52 MC3@1GHz, support OpenGL ES 1.1/2.0/3.2, OpenCL 2.0, Vulkan 1.1, embedded with high-performance 2D acceleration hardware
	ISP	Built-in 16 million pixel ISP, support low-light noise reduction, support RGB-IR sensor, support up to 120dB HDR, AI-ISP to improve low-noise image effect
	NPU	6 TOPS NPU, It supports INT4/INT8/INT16/FP16/BF16/TF32 operations, supports dual-core collaborative or independent work, and supports multi-task and multi-scene parallelism
	AI performance	Support the privatization deployment of ultra-large-scale parametric models under the Transformer architecture, such as Gemma series, ChatGLM series, Qwen series, Phi series and other large language models It supports traditional network architectures such as CNN, RNN, and LSTM, and supports the import and export of RKNN models; Support a variety of deep learning frameworks, including TensorFlow, TensorFlow Lite, PyTorch, Caffe, ONNX and Darknet. It also supports the development of custom operators Support Docker container management technology It supports the real-time object detection algorithm YOLO (You Only Look Once), which is fast and real-time compared with traditional object detection methods, and can accurately identify and locate multiple target objects in images or videos, powering AI applications
	Decoding/ Encoding	Decoding: 8K@30fps/4K@120fps (VP9, AVS2, AV1), 4K@60fps (H.264/AVC) Encoding: 4K@60fps (H.264/AVC) Image codec: 4K@60fps MJPG
	RAM	LPDDR4/LPDDR4x/LPDDR5 (4GB/8GB/16GB optional)
	Storage	eMMC (16GB/32GB/64GB/128GB/256GB optional)
	Storage expansion	1 × TF Card
	OS	It supports RTLinux kernel and has excellent real-time performance, which is widely used in industrial application scenarios. Support Linux OS, Buildroot, and provide a safe and stable system environment for product research and production. It has new industrial features such as real-time network, Flexbus, hardware resource isolation, and DSMC to meet the needs of different industrial applications.
	Power	DC 12V (Connected via 8P-1.25mm Wafer connector)
	Dimension	38.09mm × 38.11mm × 11.54mm
	Weight	≈21g
	Environment	CAM-3576Q38: Operating Temperature: -20℃~60℃, Storage Humidity: 10%～90%RH (non-condensing) CAM-3576JQ38/3576MQ38: Operating temperature: -40℃～85℃, Operating humidity: 10%～90%RH (non-condensing)
Interface Specifications	Ethernet	1 × 100M Ethernet (Led out via 8P-1.25mm Wafer connector)
	Wireless network	1 WiFi module on board, supporting 2.4GHz/5GHz dual-band WiFi6 (802.11a/b/g/n/ac/ax)
	Video input	1 × MIPI-CSI DPHY (Supports MIPI V1.2 version; 1×4Lanes, 40Pin-0.5mm)
	Audio output	1 × MIC (2Pin-1.25mm), 1 × Speaker (4Pin-1.25mm, 2×10W/6Ω or 2×10W/8Ω)
	USB	1 × USB2.0 (Led out via 24Pin-0.5mm FPC connector), 1 × Type-C (Device)
	Antenna	1 × WiFi antenna
	Button	1 × Reset, 1 × MaskRom
	Other interfaces	1 × Expansion Interface (24Pin-0.5mm FPC connector, led out: 5V, 1×USB2.0, 1×ADC, 1×I2C, 1×UART, 10×GPIO), 1 × RS485 (Led out via 8P-1.25mm Wafer connector), 1 × RTC Battery Holder (2Pin-1.25mm), 1 × Debug (3Pin-1.25mm), 1 × Recovery (2Pin-1.25mm)