Efinix, Inc.

Embedded System Solutions

Efinix® offers efficient, reliable, and integrated solutions in an open-source format, enabling you to accelerate your project development in embedded system applications.

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High-Speed Communication

Efinix® FPGAs are engineered for fast, reliable data transfer with low power and latency, ideal for performance-driven systems across a variety of applications.

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System in Package Solutions (SiP)

Our SiP Solutions integrate FPGAs with essential system components into a single compact module — reducing PCB complexity, accelerating prototyping, and streamlining production for faster time-to-market. Ideal for applications from embedded vision to edge computing.
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Test and Measurement Solutions

Efinix® FPGAs bring the performance, flexibility, and low power needed for today's test and measurement systems.
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Sapphire SoC Suite of RISC-V Processors

Efinix's Sapphire SoC suite of RISC-V processors provides a range of choices to meet your design requirements from a tiny soft core (Sapphire Lite SoC) to a highly configurable soft core (Sapphire SoC) to a 1-GHz capable hard core (High-performance Sapphire SoC).
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FPGA Families

With up to 2 million logic elements, Titanium FPGAs bring high performance, high capacity, and low power to the mainstream market.

Combines an extra efficient architecture with commonly used features and protocols, so you can go big and still have room to innovate.

Trion FPGAs are for general-purpose logic applications and span 4K to 120K logic elements.

Efficient Solutions to Enable Your Success

At the heart of our FPGAs is our disruptive Quantum® fabric, which delivers power, performance, and area advantages over traditional FPGA technologies. Our Titanium FPGAs are ready to unlock new applications and deliver rapid time to market for innovations in the mainstream marketplace. With densities ranging from 4K to 1 million logic elements (LEs), our FPGAs are ready to meet your next design challenge, whether it is custom logic, compute acceleration, machine learning, or deep learning.