Eyeq4 Datasheet -
Approximately 3 Watts , achieved through a high-efficiency 28nm FD-SOI (Fully Depleted Silicon On Insulator) manufacturing process.
+-----------------------------------------------------------------------+ | MIPS CPU Cluster | | (4 Cores / 16 Hardware Threads Base Control) | +-----------------------------------------------------------------------+ | Vector Microcode | Programmable Macro | Multithreaded Processing | | Processors (VMP) | Arrays (PMA) | Clusters (MPC) | | (6 x Wide SIMD) | (Dataflow Accelerators)| (Versatile OpenCL/Algo) | +-----------------------------------------------------------------------+ | High-Bandwidth Interconnect & L2 | +-----------------------------------------------------------------------+ General-Purpose Control Layer eyeq4 datasheet
Conclusion The EyeQ4 family exemplifies the automotive vision SoC trend: providing heterogeneous, high-efficiency compute tailored to perception and DNN inference, while incorporating functional safety and automotive-grade interfaces. For OEMs and tier-1 suppliers, EyeQ4-class chips enable consolidation of ADAS functionality, support more advanced automation levels, and shorten time-to-market when combined with a mature software ecosystem — though they must be complemented by system-level safety architectures, careful thermal/power planning, and extensive validation to meet the stringent requirements of automotive deployment. Approximately 3 Watts , achieved through a high-efficiency
Thermal management is addressed in a 2020 Mobileye-proprietary application note, "EyeQ4 SoC Digital 1.0V Core Power Rail," which details the chip's thermal model, system thermal resistance, and mission profile, crucial for safe automotive operation. While newer and more powerful chips have emerged,
The Mobileye EyeQ4 is a landmark system-on-chip that successfully balanced high-performance vision processing with the rigorous power, thermal, and safety constraints of the automotive industry. Its sophisticated heterogeneous architecture and efficient power delivery have enabled it to serve as the brain for countless ADAS systems, bridging the gap between driver assistance and the autonomous driving revolution. While newer and more powerful chips have emerged, the EyeQ4 remains a benchmark for energy-efficient, purpose-built AI vision processors.
