Eyeq4 Datasheet -
The is a high-performance vision processor (SoC) designed specifically for advanced driver-assistance systems (ADAS) and autonomous driving. Launched in 2018, it represented a significant jump in performance, offering roughly ten times the processing capability of its predecessor, the EyeQ3. Key Technical Specifications
Introduced as a significant upgrade to its predecessors (EyeQ2 and EyeQ3), the Mobileye EyeQ4, launched in 2018, is designed specifically for high-end ADAS and initial autonomous capabilities. It serves as the "brain" behind features like Automated Emergency Braking (AEB), lane-keeping assist, and surround-view monitoring, offering . Go to product viewer dialog for this item.
The Mobileye EyeQ4 is a high-performance, low-power System-on-Chip (SoC) designed specifically for camera-based Advanced Driver Assistance Systems (ADAS) and autonomous driving. Launched in 2018 as the successor to the EyeQ3, it offers roughly ten times the processing capability while maintaining a strict automotive power envelope.
4x MIPI CSI-2 Rx serial video ports and 1x parallel video port. eyeq4 datasheet
. In the automotive world, a chip failure can have life-altering consequences. The EyeQ4 was built to meet
The EyeQ4 datasheet provides a comprehensive overview of the EyeQ4 SoC, highlighting its key features, technical specifications, and applications. As a leading SoC in the field of autonomous driving and AI, the EyeQ4 is an ideal solution for various industries, including automotive, industrial, and consumer applications. By understanding the EyeQ4 datasheet, developers and engineers can unlock the full potential of this powerful SoC and create innovative solutions that transform industries.
Two cores offering compute density similar to fixed-function hardware while remaining fully programmable. Key ADAS Capabilities The is a high-performance vision processor (SoC) designed
At the heart of the EyeQ4's power is its heterogeneous multi-core architecture, specifically designed to handle the complex algorithms of computer vision with extreme efficiency. The chip is manufactured by STMicroelectronics using their advanced 28nm Fully Depleted Silicon-On-Insulator (FD-SOI) process, a technology that offers a strong balance between high performance and low power consumption.
: Manufactured using STMicroelectronics' 28nm FD-SOI (Fully Depleted Silicon On Insulator) process, which is optimized for low power consumption.
A standout feature of the EyeQ4 datasheet is its utilization of the manufacturing process. Traditional bulk CMOS suffers from elevated parasitic leakage at smaller nodes. FD-SOI introduces an ultra-thin layer of insulator (silicon dioxide) buried inside the substrate. This structure provides massive benefits: It serves as the "brain" behind features like
2 cores offering higher efficiency than standard CPUs and more versatility than a GPU. Programmable Macro Array
The is a highly advanced, application-specific system-on-chip (SoC) designed by Mobileye and manufactured by STMicroelectronics to power Level 2 and Level 2+ Advanced Driver Assistance Systems (ADAS) . Fabricated using a specialized 28nm Fully Depleted Silicon-on-Insulator (FD-SOI) process, the EyeQ4 delivers an impressive 2.5 Teraflops (or 2.5 TOPS) of processing power while drawing a meager 3 to 5 Watts . This extreme efficiency allows it to process up to eight high-resolution automotive cameras simultaneously at 36 frames per second, making it a foundational component for modern collision avoidance, lane keeping, and adaptive cruise control systems worldwide. Architectural Breakdown
: Built on 28nm FD-SOI (Fully Depleted Silicon On Insulator) technology, which allows for low power consumption while maintaining high performance.
The EyeQ4 features . VMPs are specialized Vector Processors designed to handle classical computer vision tasks efficiently. They excel at matrix operations, image scaling, filtering, and pixel-level manipulations, offering vastly superior performance-per-watt compared to standard DSPs. Programmable Macro Array (PMA)
: Achieves a 96% utilization rate, which is significantly higher than most general-purpose GPUs.