Eyeq4 Datasheet -

The Mobileye EyeQ4 is a high-performance vision system-on-chip (SoC) designed for Advanced Driver Assistance Systems (ADAS) and semi-autonomous driving. It provides approximately 2.5 teraflops of processing power while maintaining a low-power automotive-grade envelope of roughly 3W. Technical Specifications Summary

The EyeQ4 architecture is based on a heterogeneous computing model that assigns specific tasks to specialized cores for maximum efficiency. Feature Specification Details Processor Cores

4x multi-threaded 64-bit RISC MIPS CPUs (4 hardware threads each) Vision Accelerators

6x Vector Microcode Processors (VMP), 2x Multithreaded Processing Clusters (MPC), 2x Programmable Macro Arrays (PMA) Compute Power >2.5 Teraflops (or 2.5 TOPS depending on variant) Power Consumption ~3 Watts (up to 5W in some high-load configurations) Process Node

28nm Fully Depleted Silicon On Insulator (FD-SOI) by STMicroelectronics Camera Support Up to 8 cameras simultaneously at 36 FPS Safety Standard ISO 26262 compliant with ASIL-B(D) safety level Packaging Flip-Chip FBGA 784-pin; 22.5 x 22.5 x 1.7 mm EyeQ4 Variant Differences

Mobileye developed multiple versions of the chip to support different vehicle capabilities: EyeQ4-High (EyeQ4H)

: The most capable version, supporting trifocal front-sensing, surround-view systems (4 cameras), and sensor fusion with radar and laser scanners. EyeQ4-Medium (EyeQ4M)

: A cost-optimized variant with a subset of cores, typically used for monocular or trifocal camera configurations in standard ADAS applications. Key Interfaces and Connectivity

According to the EyeQ4 Product Brief, the chip includes the following I/O: Memory: Dual 32-bit LPDDR4 SDRAM interfaces at 1.6GHz. Network: 1Gb Ethernet port.

Video Input: 4x MIPI CSI-2 Rx serial video ports and 1x parallel video port.

Automotive Buses: 3x CAN ports (>1Mbps), 3x UART, 3x I2C, and 4x SPI interfaces. Documentation and Resources Mobileye EyeQ4 Vision Processor Family - Yole Group

The Mobileye EyeQ4 is a high-performance vision processor designed for Advanced Driver Assistance Systems (ADAS) and autonomous driving, offering a massive leap in processing power over its predecessors. Key Technical Specifications Performance: 2.5 Tera Operations Per Second (TOPS).

Efficiency: 10x more powerful than EyeQ3 with only a 20% increase in power consumption. Architecture:

Manufactured using 28nm FD-SOI technology by STMicroelectronics.

Features 14 computing cores, including specialized vector accelerators. Integrates four multi-threaded MIPS InterAptiv cores.

Camera Support: Capable of processing up to 10 cameras simultaneously at 36 frames per second. "Interesting" Breakthroughs & Capabilities

High Utilization: Achieves a 96% utilization rate, which is significantly higher than most general-purpose GPUs.

Complex Recognition: Supports "any-angle" vehicle detection and next-generation lane detection.

Scalability: Used in configurations ranging from a single "Mono" camera for collision avoidance to "Tricam" setups for semi-autonomous driving.

Safety Standards: Designed for compliance with EU NCAP and US NHTSA regulatory requirements.

Market Impact: By 2018, it was already launched in 78 different vehicle models from 16 major manufacturers like BMW, Nissan, and GM.

💡 Pro-Tip: For specific implementation, designers often pair the EyeQ4 with a dedicated power management unit like the TI LP875761-Q1 to handle the SoC's core rail requirements.

If you'd like to dive deeper, would you prefer details on the programming architecture or its role in specific car models?

Mobileye EyeQ4 represents a pivotal bridge in the evolution of automotive technology, moving from simple driver assistance to high-level semi-autonomous driving. As a System-on-Chip (SoC) designed specifically for vision processing, its datasheet reveals a sophisticated architecture engineered to handle the chaotic, real-world environment of modern roads. The Architecture of Vision

At the heart of the EyeQ4 is a specialized heterogeneous architecture. Unlike a standard computer processor, the EyeQ4 utilizes a mix of multi-threaded CPU cores vector microcode processors (VMPs)

. This "asymmetric" design allows the chip to perform massive parallel processing—essentially "seeing" and "interpreting" multiple data streams from cameras and sensors simultaneously—while maintaining a remarkably low power profile of approximately 3 to 5 watts. Safety and Redundancy

A critical takeaway from the EyeQ4 specifications is its focus on functional safety

. In the automotive world, a chip failure can have life-altering consequences. The EyeQ4 was built to meet

safety standards, meaning it includes hardware-level redundancies. It doesn't just process pixels; it constantly checks its own work to ensure that the "decisions" it passes to the car’s braking or steering systems are reliable and error-free. Capability vs. Efficiency

While modern chips like the EyeQ5 or NVIDIA’s Orin offer more raw tera-operations per second (TOPS), the EyeQ4 is a masterclass in efficiency

. It provides the computational muscle for Level 2 and Level 3 autonomous features—such as lane keeping, traffic sign recognition, and pedestrian detection—without requiring the liquid cooling or massive battery drain seen in more experimental platforms. Conclusion

The EyeQ4 datasheet is more than a technical list; it is a blueprint for the "eyes" of the modern vehicle. By balancing high-speed visual processing with rigorous safety standards and low power consumption, Mobileye created a platform that transitioned autonomous driving from a laboratory concept into a scalable, everyday reality for millions of drivers. (like TOPS) or compare it to the newer EyeQ5/EyeQ6

The Mobileye EyeQ4 is a high-performance System-on-Chip (SoC) designed for Advanced Driver Assistance Systems (ADAS) and autonomous driving

. Launched in 2018, it offers approximately 10 times the processing power of its predecessor, the EyeQ3, while maintaining high energy efficiency. Yole Group Core Technical Specifications Architecture eyeq4 datasheet

: Features 4 CPU cores with 4 hardware threads each, integrated with Mobileye's proprietary Vector Microcode Processors (VMP). Performance

: Capable of over 2.5 Teraflops (TFLOPS) of processing power. Power Consumption : Highly efficient, typically consuming only Manufacturing Process : Built using 28nm FD-SOI

(Fully Depleted Silicon On Insulator) technology for low power consumption. Vision Processing : Supports visual input from up to simultaneously at 30fps. Yole Group Key Functional Features Environment Modeling

: Capability for vehicle detection from any angle, next-generation lane detection, and traffic light detection. Mapping & Localization : Supports Road Experience Management (REM™) for real-time crowd-sourced mapping. Safety Applications

: Powers critical functions such as Autonomous Emergency Braking (AEB), Pedestrian AEB, and Forward Collision Warning (FCW). Driving Policy

: Includes support for complex path planning and "Driving Policy" to manage vehicle behavior in traffic. Yole Group Product Variants EyeQ4-High

: The premium version capable of processing multiple cameras (up to 8) for 360-degree surround-view and semi-autonomous functions.

: A mid-range version typically used for mono-camera systems, such as the ZF S-Cam4 family. Yole Group Automotive Integration

The EyeQ4 has been widely adopted by major global automotive manufacturers, including: General Motors Yole Group For detailed power supply designs involving this chip, Texas Instruments

The Mobileye EyeQ4 is a high-performance vision processor designed specifically for Advanced Driver Assistance Systems (ADAS) and semi-autonomous driving. Launched in 2018, it represented a significant leap in computational efficiency, providing approximately 10 times the processing power of its predecessor, the EyeQ3, while maintaining a very low power envelope. Core Technical Specifications

The EyeQ4 is built on a heterogeneous architecture that utilizes specialized cores for different computer vision tasks to maximize efficiency.

Process Technology: Manufactured using STMicroelectronics' 28nm FD-SOI (Fully Depleted Silicon On Insulator) process, which is optimized for low power consumption.

Performance: Capable of reaching 2.5 Tera Operations Per Second (TOPS) (or 2.5 TFLOPS).

Power Consumption: Typically draws only 3 Watts, making it suitable for windshield-mounted camera systems without specialized cooling.

Input Capability: Supports simultaneous processing for up to 8 cameras at 36 frames per second (fps). Processor Architecture The EyeQ4 integrates several types of programmable cores: The Evolution of EyeQ

Mobileye EyeQ4 is a high-performance vision system-on-chip (SoC) designed specifically for advanced driver-assistance systems (ADAS) and semi-autonomous driving. Developed by Mobileye (an Intel company) and manufactured by STMicroelectronics, it represented a massive jump in processing power—roughly 10 times that of its predecessor, the EyeQ3, while consuming only 20% more power. Key Specifications & Architecture

is built on a 28nm Fully Depleted Silicon On Insulator (FD-SOI) process, which is critical for maintaining high performance with a low power envelope of approximately 3 watts. -High Specifications Compute Performance ~2.5 Teraflops (1.26 Billion MAC/s) CPU Cores

4 multi-threaded MIPS InterAptiv cores (4 hardware threads each) Vision Accelerators

6 Vector Microcode Processors (VMP), 2 Multithreaded Processing Clusters (MPC), 2 Programmable Macro Arrays (PMA) Camera Input Up to 8 cameras simultaneously at 36 fps Functional Safety ISO 26262 ASIL-B(D) Packaging Flip-Chip FBGA 784-pin (22.5 x 22.5 x 1.7mm) Specialized Processing Cores The "magic" of the

datasheet lies in its heterogeneous architecture, which uses different types of proprietary accelerators for specific vision tasks:

Vector Microcode Processors (VMP): A VLIW and SIMD machine optimized for computer vision and deep learning algorithms.

Multithreaded Processing Cluster (MPC): More versatile and efficient than a standard GPU, handling complex control and data management.

Programmable Macro Array (PMA): A CGRA dataflow machine providing compute density similar to fixed-function hardware while remaining programmable. Product Variants: High vs. Mid The Evolution of EyeQ - Mobileye

Mobileye EyeQ4 is an automotive-grade vision processor (SoC) designed by Mobileye and manufactured by STMicroelectronics using 28nm FD-SOI technology. It represents a massive leap in processing power for Advanced Driver Assistance Systems (ADAS) compared to its predecessors. Core Specifications Architecture

: High-performance multi-core design including 4 multi-threaded MIPS InterAptiv CPU cores, 6 Vector Microcode Processors (VMP), 2 Multithreaded Processing Clusters (MPC), and 2 Programmable Macro Arrays (PMA). Performance : Delivers 2.5 Teraflops (TOPS)

of processing power, which is roughly 10x the capability of the EyeQ3. Efficiency : Consumes approximately

, making it highly energy-efficient relative to its output (only 20% more power than the EyeQ3 for 10x the power). Vision Input : Supports visual input from up to simultaneously at 30fps. Key Capabilities Advanced Detection

: Includes vehicle detection from any angle, next-generation lane detection, and traffic light detection. Environmental Modeling

: Capable of full environmental modeling and holistic path planning. : Supports Mobileye's Road Experience Management (REM) for crowd-sourced high-definition mapping. Safety Features

: Powers Automated Emergency Braking (AEB), Forward Collision Warning (FCW), and Adaptive Cruise Control (ACC). Review: The "Sweet Spot" for Semi-Autonomous Driving

The EyeQ4 is widely considered the processor that moved ADAS from simple "passive" alerts to "active" semi-autonomous driving. Unmatched Efficiency

: At just 3W, it delivers heavy-duty processing without requiring complex cooling systems, a critical factor for automotive reliability. Massive Scalability

: It was designed to support everything from basic mono-camera systems to complex "Tri-cam" setups found in luxury brands like BMW. Proven Reliability Technical Specifications

: Already integrated into over 160 car models from major OEMs like GM, Nissan, and Honda. Generationally Older : While powerful, it has since been surpassed by the EyeQ Ultra

, which offer significantly higher TOPS for Level 4/5 autonomy. Closed System

: Historically, Mobileye chips have been more "black box" systems, though later generations (like EyeQ5) began moving toward more open software platforms. performance against the newer

Overview

The EyeQ4 is a high-performance, low-power SoC that enables advanced driver-assistance systems (ADAS) and autonomous driving applications. It is designed to process multiple sensor inputs, including cameras, radar, and lidar, and provide a comprehensive view of the environment.

Key Features

Technical Specifications

Applications

Conclusion

The EyeQ4 is a powerful and feature-rich SoC that is well-suited for autonomous driving and ADAS applications. Its high-performance processing, advanced computer vision, and machine learning capabilities make it an attractive solution for developers of autonomous vehicles.

Rating: 4.5/5

Pros:

Cons:

Note that this review is based on the datasheet and may not reflect the actual performance of the EyeQ4 in real-world applications.

The Mobileye EyeQ4 is a high-performance vision-based System-on-Chip (SoC) designed specifically for Advanced Driver Assistance Systems (ADAS) and autonomous driving. Leveraging a heterogeneous multi-core architecture, it delivers significant leaps in computational efficiency compared to its predecessors.

The following data summarizes the key specifications and architectural details typically found in an EyeQ4 datasheet. Core Performance Specifications

The EyeQ4 is engineered to provide "super-computer" capabilities within a strictly constrained automotive power envelope.

Computational Power: Up to 2.5 Tera Operations Per Second (TOPS).

Power Consumption: Approximately 3 Watts, achieved through a high-efficiency 28nm FD-SOI (Fully Depleted Silicon On Insulator) manufacturing process.

Safety Rating: Designed to meet ISO-26262 standards with a safety level of ASIL-B(D).

Camera Support: Capable of processing up to 8 cameras simultaneously at 36 frames per second (fps). Architectural Overview

The EyeQ4 utilizes a diverse set of specialized accelerators to handle complex computer vision and deep learning tasks efficiently. Description CPU Cores General Purpose Compute

Quad-core MIPS interAptiv processors with multi-threading (up to 4 threads per core). VMP Vector Microcode Processor

6 cores dedicated to VLIW and SIMD operations, ideal for short integral types in vision algorithms. MPC Multi-threaded Processor Cluster

2 cores offering higher efficiency than standard CPUs and more versatility than a GPU. PMA Programmable Macro Array

2 Cores using a CGRA dataflow machine architecture for dense computer vision algorithms. EyeQ4 Family Variants

Mobileye offers different versions of the EyeQ4 to provide a scalable solution for varying levels of vehicle autonomy.

EyeQ4 High: The full-capability version designed for surround-view systems and trifocal front-sensing. It processes information from multiple cameras, radars, and lidars to create a "safety cocoon" around the vehicle.

EyeQ4 Mid: A subset version tailored for mid-range ADAS. It integrates fewer cores (e.g., three MIPS cores and four VMP cores) and is typically used in single-camera or trifocal configurations.

EyeQ4 Lite: Optimized for entry-level NCAP compliance and basic collision avoidance features. Key Features and Applications

The EyeQ4 datasheet highlights several next-generation ADAS capabilities:

Object Detection: Support for vehicle detection from any angle and pedestrian/cyclist identification.

Mapping (REM): Integration with Mobileye Road Experience Management (REM) for crowdsourced high-definition mapping. Lane Keep Assist

Lane Detection: Next-generation lane and road boundary detection for centering and departure warnings.

Sensor Fusion: Efficiently fuses data from optical sensors with radar and scanning-beam lasers. Physical and Electrical Characteristics

Detailed hardware integration data for the EyeQ4-Mid and EyeQ4-High includes: Package: Flip-Chip FBGA with 784 pins. Dimensions: 22.5 mm x 22.5 mm x 1.7 mm.

Manufacturing: Produced by STMicroelectronics using a proprietary 28nm process.

Interfaces: Includes high-speed automotive interfaces such as Ethernet, CAN, and PCIe for ECU communication.

For developers seeking to integrate this chip, the Mobileye Technology Page provides further insights into the evolution of this architecture and its role in modern autonomous platforms.

Inside the EyeQ4: The "Supercomputer" Driving Your Next Car Mobileye EyeQ4

isn't just another chip; it's the silicon brain that moved Advanced Driver Assistance Systems (ADAS) from simple warnings to near-autonomous "safety cocoons". Launched in 2018, this System-on-Chip (SoC) provides a staggering 10x more processing power

than its predecessor, the EyeQ3, while keeping power consumption remarkably low.

Here is a deep dive into the technical specifications and capabilities that make the a landmark in automotive technology. Technical Specifications: The Power of Efficiency is manufactured using 28nm Fully Depleted Silicon On Insulator (FD-SOI) technology by STMicroelectronics

. This specialized manufacturing process is what allows it to deliver "super-computer" performance within a tiny power envelope. Computational Performance: 2.5 Teraflops (trillions of operations per second). Power Consumption: Approximately , which is less than many standard mobile phone processors. Architecture: A heterogeneous mix of cores designed for specific tasks: Four multi-threaded MIPS cores. VMP (Vector Microcode Processors):

Six cores for image processing and integral types used in computer vision. MPC (Multi-threaded Processing Cluster):

Two cores more versatile than GPUs and more efficient than CPUs. PMA (Programmable Macro Array):

Two cores providing high compute density for dense computer vision algorithms. Supports dual 1.6GHz, 32-bit LPDDR4 SDRAM interfaces. Connectivity:

Includes a 1Gb Ethernet port, multiple CAN ports (>1Mbps), UART, and I2C interfaces. Safety Rating: Designed according to ISO-26262 to provide safety levels. Advanced ADAS Capabilities What does all that silicon power actually do? The is designed to process information from up to eight cameras simultaneously

at 36 frames per second. This allows it to support sophisticated features that were previously impossible for a single chip: ZF and Mobileye Safety Technology Chosen by Toyota

Mobileye EyeQ4 is a high-performance System-on-Chip (SoC) designed for vision-based Advanced Driver Assistance Systems (ADAS) and semi-autonomous driving. Launched as a significant leap over its predecessor, the EyeQ3, it provides the computational "super-computer" power required for complex environmental modeling while maintaining strict automotive power efficiency. Core Specifications & Architecture Performance: Delivers over 2.5 Teraflops (2.5 TOPS) of compute power. Power Consumption: Highly efficient, typically consuming only Process Technology: Manufactured using STMicroelectronics' 28nm FD-SOI (Fully Depleted Silicon-on-Insulator) process. Heterogeneous Processor Mix: Four multi-threaded MIPS processor cores. VMP (Vector Microcode Processors):

Six cores (in the "High" version) optimized for computer vision and deep learning tasks. MPC (Multi-threaded Processing Cluster): Two cores more versatile than traditional GPUs. PMA (Programmable Macro Array):

Two cores providing compute density similar to fixed-function hardware. Functional Capabilities

The EyeQ4 is designed to create a "safety cocoon" around the vehicle by processing multiple sensor inputs simultaneously. Multi-Camera Support: The "High" version can process information from up to simultaneously at 36 frames per second. Sensor Fusion:

Supports inputs from trifocal front cameras, surround-view systems, long-range rear cameras, radars, and scanning beam lasers. Advanced Features: Deep Learning:

Utilizes cutting-edge computer vision algorithms like Deep Layered Networks. 3D Detection: First to introduce 3D vehicle and motorbike detection. Environmental Mapping:

Supports Road Experience Management (REM) for high-definition mapping harvesting. Safety Alerts:

Includes Hazard Detection, Red Light Warning, and Stop Sign/No Entry warnings. Variants & Compliance Scalability: Available in multiple versions, including EyeQ4-High (full autonomous capability) and

(subset of cores for select functions), allowing carmakers to scale hardware solutions. Safety Standard: Developed according to the standard, providing a safety level of Market Presence: Integrated into vehicles from major OEMs such as , Ford, General Motors, Nissan, and Volvo. generations?

Hardware Interface Overview

Key Specification (from datasheet):

Software Stack

The datasheet often references the necessity of Mobileye’s EyeQ Kit – a proprietary SDK. Important: The chip will not run arbitrary Linux or C++ code. It runs Mobileye’s closed software stack. Developers can add small accelerators via the Programmable Macro Array.

Ordering Information and Part Numbers

From the marketing datasheet:

| Part Number | Description | Temperature Range | |-------------|-------------|-------------------| | EYQ4-C-AA | Commercial sample, AEC-Q100 Grade 2 | -40°C to +105°C | | EYQ4-P-AE | Pre-production engineering | 0°C to +85°C | | EYQ4-V-22QMY | Automotive qualified, 22nm variant (rare) | -40°C to +105°C |

The full datasheet contains additional part numbers for ISO 26262 ASIL-D certified variants.

What is the EyeQ4?

Launched in 2018, the EyeQ4 is Mobileye’s fourth-generation system-on-a-chip (SoC) designed specifically for Level 2 (L2) and Level 3 (L3) autonomous driving features. Unlike its predecessors, the EyeQ4 was architected to process multiple camera inputs simultaneously, enabling surround-view sensing and advanced feature fusion.

The chip powers features like Traffic Jam Assist, Lane Keep Assist, Automatic Emergency Braking (AEB), and even some highway pilot systems found in vehicles from BMW, Nissan, Volkswagen, and Geely.

3. Memory Subsystem

According to the datasheet, the EyeQ4 features a unified memory architecture with: