Eyeq4 Datasheet ~upd~ Here

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 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.

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 eyeq4 datasheet

: 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

: 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

Thermal and Mechanical Data

The EyeQ4 is offered in a FCBGA-484 package.

| Parameter | Value | |-----------|-------| | Package Dimensions | 17 mm × 17 mm | | Ball pitch | 0.8 mm | | Ball count | 484 | | Junction-to-case thermal resistance (θjc) | 2.5 °C/W | | Maximum junction temperature (Tj) | 105°C (150°C for short transients) |

Thermal design note: The datasheet recommends a 4-layer PCB with at least 6 thermal vias under the exposed die pad for conduction to chassis ground.

EyeQ4 Datasheet: A Deep Dive into Mobileye’s Automotive-Grade Vision SoC

Technical Specifications Summary

For engineers reading an eyeq4 datasheet, the following electrical and physical parameters are critical:

10. Revision History

| Revision | Date | Changes | |----------|------------|----------------------------------| | 1.0 | 2018-08-01 | Initial production datasheet | | 1.1 | 2019-02-10 | Added REM support, power numbers | | 1.2 | 2020-05-22 | Updated temp range, ESD ratings |

Disclaimer: This datasheet is a summarized reference. For complete electrical characteristics, timing diagrams, register maps, and safety manual, refer to the official EyeQ4 Datasheet (Document #: EYQ4-DS-001) from Mobileye / Intel Corporation. All specifications subject to change without notice.

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

High-performance processing: The EyeQ4 features a multi-core processor that provides up to 2.5 times the processing power of its predecessor, the EyeQ3.
Advanced computer vision: The SoC includes a dedicated computer vision engine that enables applications such as object detection, tracking, and scene understanding.
Machine learning capabilities: The EyeQ4 supports machine learning algorithms for tasks such as classification, regression, and clustering.
Sensor fusion: The SoC can fuse data from multiple sensors, including cameras, radar, and lidar, to provide a comprehensive view of the environment.

Technical Specifications

Process node: 16nm FinFET
CPU: Multi-core processor with up to 12 cores
Memory: Up to 8GB of LPDDR4 memory
Interface: Support for various interfaces, including PCIe, USB, and CAN

Applications

Autonomous driving: The EyeQ4 is designed to enable Level 3 and Level 4 autonomous driving applications, including highway driving, urban driving, and parking.
Advanced driver-assistance systems (ADAS): The SoC can also be used for ADAS applications, such as lane departure warning, blind spot detection, and forward collision warning.

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:

High-performance processing
Advanced computer vision and machine learning capabilities
Support for multiple sensors and interfaces

Cons:

High power consumption
Complex software development required

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 28nm FD-SOI, high-performance System-on-Chip (SoC) designed for camera-based Advanced Driver Assistance Systems (ADAS), delivering over 2.5 teraflops of processing power at 3W. Featuring six VMP cores, two MPC cores, and two PMA cores, it supports up to 8 simultaneous cameras for advanced computer vision and autonomous emergency braking. For more details, visit Mobileye.

The Mobileye EyeQ4 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

The EyeQ4 architecture is built for "super-computer" capabilities within a low-power automotive-grade package. Performance: Capable of more than 2.5 Teraflops (2.5 TOPS).

Power Consumption: Extremely efficient, typically consuming only 3 watts.

Manufacturing Process: Developed by Mobileye and manufactured by STMicroelectronics using 28nm FD-SOI (Fully Depleted Silicon On Insulator) technology, which helps maintain low power consumption despite high performance.

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

Camera Support: Can process information from up to 8 cameras simultaneously at 36 frames per second (fps). Architecture & Hardware Cores

The EyeQ4-High variant features a diverse array of 14 computing cores designed to handle specific vision tasks efficiently: Description MIPS CPUs

Four multi-threaded MIPS processor cores (often InterAptiv) for general data management and control. VMP Cores Thermal and Mechanical Data The EyeQ4 is offered

Six Vector Microcode Processors for dedicated image processing tasks. MPC Cores

Two Multithreaded Processing Cluster cores, more versatile and efficient than standard GPUs for automotive tasks. PMA Cores

Two Programmable Macro Array cores, providing high compute density for fixed-function hardware acceleration. Core Capabilities

The EyeQ4 was engineered to support a "safety cocoon" around the vehicle, enabling features essential for semi-autonomous and autonomous driving: The Evolution of EyeQ - Mobileye

The Mobileye EyeQ4 Go to product viewer dialog for this item.

is a high-performance System-on-Chip (SoC) designed for Advanced Driver Assistance Systems (ADAS) and autonomous driving. Manufactured by STMicroelectronics using 28nm FD-SOI technology, it provides 10x the processing power of its predecessor, the EyeQ3, while maintaining a low power envelope. Technical Specifications

The EyeQ4 architecture utilizes a heterogeneous mix of specialized accelerators to achieve high efficiency. Specification Performance 2.5 TOPS (High variant) / ~1.1 TOPS (Mid variant) Power Consumption ~3 Watts (Automotive grade) CPU Cores 4 multi-threaded MIPS InterAptiv cores (4 threads each) Vision Accelerators

6 Vector Microcode Processors (VMP), 2 Multithreaded Processing Clusters (MPC), 2 Programmable Macro Arrays (PMA) Camera Support Up to 8 cameras simultaneously at 36 fps Safety Standard ISO 26262 compliant; ASIL-B(D) level Package Flip-Chip FBGA 784-pin (22.5 x 22.5 x 1.7mm) Key Capabilities The Evolution of EyeQ - Mobileye

EyeQ4 Datasheet Write-up

The EyeQ4 is a high-performance, low-power System-on-Chip (SoC) designed for advanced driver-assistance systems (ADAS) and autonomous driving applications. Developed by Mobileye, a leading provider of computer vision and machine learning technologies, the EyeQ4 is a fourth-generation SoC that offers significant improvements in processing power, memory, and software capabilities compared to its predecessors.

Overview

The EyeQ4 datasheet provides an in-depth look at the SoC's architecture, features, and specifications. Here are some key highlights:

Processing Power: The EyeQ4 features a heterogeneous, multi-core architecture with a combination of CPU, GPU, and specialized cores for computer vision and machine learning tasks. This enables the SoC to deliver up to 2.5 TOPS (tera-operations per second) of processing power, making it suitable for demanding ADAS and autonomous driving applications.
Memory: The EyeQ4 has a large memory capacity, with up to 16 GB of LPDDR4 RAM and 128 GB of eMMC storage. This provides ample memory for running complex algorithms and storing data from various sensors.
Sensor Support: The SoC supports a wide range of sensors, including cameras, radar, lidar, and ultrasonic sensors, allowing for comprehensive environmental perception and situational awareness.
Software: The EyeQ4 is designed to run on Mobileye's proprietary software stack, which includes a range of tools and libraries for computer vision, machine learning, and autonomous driving applications.

Key Features

The EyeQ4 datasheet highlights several key features that make it an attractive solution for ADAS and autonomous driving applications:

Computer Vision: The SoC's dedicated computer vision cores enable efficient processing of complex computer vision algorithms, such as object detection, tracking, and segmentation.
Machine Learning: The EyeQ4's GPU and specialized cores support popular machine learning frameworks, including TensorFlow and PyTorch, allowing developers to deploy trained models for tasks like image classification and predictive analytics.
Advanced Interfaces: The SoC supports a range of interfaces, including PCIe, USB, and CAN, for connecting to various peripherals and sensors.
Power Efficiency: The EyeQ4 is designed to operate at low power consumption levels, making it suitable for use in automotive applications where energy efficiency is critical.

Applications

The EyeQ4 is designed for a range of ADAS and autonomous driving applications, including:

Lane Departure Warning (LDW): The SoC's computer vision capabilities enable accurate detection of lane markings and warnings for lane departure.
Adaptive Cruise Control (ACC): The EyeQ4's sensor support and processing power enable smooth and efficient control of ACC systems.
Automatic Emergency Braking (AEB): The SoC's machine learning capabilities enable predictive analytics and automatic emergency braking in critical situations.

Conclusion

The EyeQ4 datasheet provides a comprehensive overview of Mobileye's latest SoC for ADAS and autonomous driving applications. With its powerful processing capabilities, large memory capacity, and support for a range of sensors and software frameworks, the EyeQ4 is well-suited for demanding applications like computer vision, machine learning, and autonomous driving. As the automotive industry continues to evolve towards more advanced driver-assistance systems and autonomous vehicles, the EyeQ4 is poised to play a key role in enabling these technologies.

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 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. Disclaimer: This datasheet is a summarized reference

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

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?

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

How to Obtain the Complete EyeQ4 Datasheet

As of this writing, no public download of the full 2,500+ page EyeQ4 datasheet exists. Access is gated through:

Mobileye Partner Program – Sign a mutual NDA and license agreement.
Intel’s Design Resource Center – Available to customers with signed purchase orders.
Automotive Tier-1 internal portals (Bosch, Denso, Aptiv).

For academic or evaluation purposes, Mobileye offers a redacted public datasheet (45 pages) covering mechanical, power, and thermal specs without register-level details.

Conclusion

The EyeQ4 datasheet is more than just a list of pins and voltages—it is a roadmap to understanding how mass-market autonomy was achieved in the late-2010s. With its blend of 28nm efficiency, 2.5 TOPS of dedicated vision power, and support for eight cameras, the EyeQ4 struck a critical balance between cost, thermal output, and real-world performance.

While the newer EyeQ5 and EyeQ6 dominate headlines for 7nm and 5nm processes, the EyeQ4 remains in active production, powering millions of vehicles on the road today. For any automotive engineer looking to build a robust, proven ADAS platform, a deep dive into the EyeQ4 datasheet is an essential first step.

Further Reading:

Mobileye EyeQ4 Safety Manual (For ISO 26262 certification details)
Intel Automotive Solutions Brief: "The Road to EyeQ6"
Application Note AN-EQ4-001: "Hardware Design Guidelines for EyeQ4"

Last updated: October 2024. Specifications subject to change by manufacturer.

Design Considerations for Engineers

If you are downloading the EYEQ4 datasheet for a new project, keep these practical engineering factors in mind: