Eyeq4 Datasheet [upd] May 2026

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.

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 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. eyeq4 datasheet

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 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 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

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

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 Overview The EyeQ4 is a high-performance, low-power SoC

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

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

EYEQ4 Datasheet Overview

The EYEQ4 is a highly integrated, low-power, and compact image signal processor (ISP) designed for various camera applications. The EYEQ4 datasheet provides detailed specifications, features, and technical information for the chip.

Key Features:

Datasheet Contents:

The EYEQ4 datasheet typically includes:

Target Applications:

The EYEQ4 is suitable for various camera applications, including:

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 a high-performance vision processor System-on-Chip (SoC) designed specifically for Advanced Driver Assistance Systems (ADAS) and semi-autonomous driving. Launched in 2018, it represented a significant jump in performance, offering roughly 10 times the processing power of its predecessor, the EyeQ3, with only a 20% increase in power consumption. Core Specifications & Performance

The EyeQ4 architecture is built on a 28nm FD-SOI (Fully Depleted Silicon On Insulator) process technology from STMicroelectronics, which is critical for its high efficiency. Specification Details Performance Over 2.5 Teraflops (TFLOPS) or 2.5 TOPS Power Consumption Approximately 3 Watts for typical automotive use Video Processing

Can process up to 8 cameras simultaneously at 36 FPS (high version) Package Size 22.5 x 22.5 mm (784-pin Flip-Chip FBGA) Architecture Overview

The EyeQ4 uses a heterogeneous "accelerator-rich" architecture. It doesn't rely solely on standard CPUs but instead uses four specialized classes of programmable accelerators designed for computer vision tasks.

MIPS CPU Cores: Features four multi-threaded MIPS InterAptiv processor cores (with 4 threads each) for general-purpose management and control.

Vector Microcode Processors (VMP): Six programmable cores optimized for vision algorithms like image filtering and feature extraction. Technical Specifications

Multithreaded Processing Cluster (MPC): Two cores designed to be more versatile than a GPU and more efficient than a CPU for complex vision tasks.

Programmable Macro Array (PMA): Two cores offering compute density similar to fixed-function hardware while remaining fully programmable. Key ADAS Capabilities

The EyeQ4 enables several safety and autonomous functions that were difficult for previous generations: The Evolution of EyeQ - Mobileye

Deep Learning Accelerator. Dedicated high-performance AI engine. The main source of horse power for convolutional neural networks. ZF and Mobileye Safety Technology Chosen by Toyota

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:

Key Features

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

Applications

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

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 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?

The Essential Guide to the EyeQ4 Datasheet: Architecture, Performance, and Applications

Pin-to-Pin Compatibility

The EyeQ4 uses a BGA-585 package. Note: It is not pin-compatible with EyeQ3 or EyeQ5. You will need a unique PCB layout.

3. Performance

2. Key Features

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:

  1. Mobileye Partner Program – Sign a mutual NDA and license agreement.
  2. Intel’s Design Resource Center – Available to customers with signed purchase orders.
  3. 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.

Design Considerations for Engineers

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

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