Artificial intelligence is rapidly becoming integral to everyday life and business operations. As this transformation progresses, shifting AI capabilities to the edge will become increasingly crucial, necessitating specialized hardware.
Edge processors are a relatively new class of technology, and AI-native options are even more cutting-edge. Still, several manufacturers offer chips that meet the edge’s need for lower power and latency and AI’s demand for computing capacity. What is the best AI-native embedded edge processor? Here are seven of the best vendors to consider.
1. Synaptics
The best AI-native embedded edge processors for most uses come from Synaptics through its Astra series of systems-on-a-chip. Synaptics specializes in microprocessors built specifically for AI functionality at the edge, giving them high performance and low power.
All Synaptics SR-series chips come with a quad-core ARM central processing unit capable of running up to 400 megahertz. Despite such high power, they use relatively little electricity, making them ideal for edge environments. They also come with built-in security features like memory scrambling and a secure boot function.
2. Silicon Labs
Silicon Labs is another AI-native edge processor developer to consider. The company made a name for itself by developing standard Internet of Things chips, and in 2024, it announced a partnership with AI startup Eta Compute to integrate AI functionality into this hardware.
According to Silicon Labs, its edge AI chips can perform machine learning functions up to eight times faster than conventional alternatives. It also claims they can do so at one-sixth of the energy. Like Synaptics, its products support secure boot, tamper protection and true random number generation to keep edge deployments safe.
3. Nvidia
The best-known player in the overall AI hardware space, Nvidia, has also started making AI-native embedded edge processors. While Nvidia is most famous for gaming hardware, its latest microarchitecture is ideal for the edge, thanks to its minimal power consumption but exceedingly quick performance.
Nvidia’s AI edge chips are not quite as small as others, which can hinder their implementation in some devices. However, the company’s reputation for quality and AI functionality speaks for itself. It may not have the most experience in the edge specifically, but it’s a leader in AI SoCs.
4. NXP Semiconductors
Another one of the best AI-native embedded edge processor producers is NXP Semiconductors. In addition to creating the appropriate hardware to run AI applications at the edge, NXP provides a suite of development tools to simplify the software side of things.
Like Synaptics, NXP’s AI edge chips rely on ARM CPUs for their high performance-per-watt ratio. However, the company shines most in its cybersecurity features. Its EdgeLock range of processors complies with several security standards by design, offers secure key injection, has built-in credential management and supports multiple cryptographic algorithms.
5. Qualcomm
Mobile SoC giant Qualcomm has ventured into edge AI applications, too. While the company hasn’t always dabbled in AI, its extensive experience in developing mobile hardware means it excels at enabling high functionality in a small footprint.
Qualcomm’s on-device AI chips achieve clock speeds up to 3.4 gigahertz, which many IoT-sized components can’t match. It also provides semiconductors purpose-built for a wide range of edge and IoT applications, which can simplify product development. The only thing limiting this manufacturer compared to some others is its relative inexperience in this niche, but its early results are already promising.
6. Intel
Another leading player in the embedded processor industry, Intel, also makes a range of AI-native edge chips. Intel’s IoT AI hardware focuses on using accelerators to boost large language model performance without needing the energy and space a conventional SoC might need.
Many of Intel’s latest edge solutions use field-programmable gate arrays instead of relying on more powerful CPUs alone to run AI functions efficiently in a small footprint. Its processors also boast an impressive amount of cores per socket, which helps with multitasking. While Intel has fallen behind other big names like Nvidia in the AI space, it’s starting to catch up with these new offerings.
7. DEEPX
South Korea-based DEEPX is another one of the best AI-native edge processor vendors to consider. DEEPX is a relative newcomer to this sector, but its focus on edge-specific AI hardware makes it a worthy competitor to other, more established brands.
DEEPX has won several CES Innovation Awards for its low-power SoCs, which claim to have the world’s most cost-effective AI boosters. Most, if not all, of the manufacturer’s products center around edge use cases, which may make them more relevant to IoT developers. However, being so far from the U.S. may create conflict amid larger reshoring initiatives. The U.S. could triple its semiconductor production capacity by 2032, so international providers are starting to fall out of favor.
How to Choose the Best AI-Native Embedded Edge Processor
These seven prominent manufacturers make the best AI-native embedded edge processors. However, your specific needs should influence your decision. Consider a few factors before deciding on a vendor.
First, look at each solution’s technical specs. In general, the lower power consumption and higher CPU performance an SoC achieves, the better, but these aren’t the only variables to compare. The chip’s physical size, software compatibility and cost can also make it more or less ideal for a given edge application.
Security is another concern. Attacks against IoT devices rose by a staggering 400% between 2022 and 2023, highlighting the need for edge cybersecurity. Any embedded AI edge processor that doesn’t feature built-in protections like secure boot and encryption is too risky to work with. You should also look for regulatory compliance-related defenses if your device must meet specific standards.
Finally, vendors offering custom support or easy implementation are generally preferable. Edge AI development can be complicated, so any way a provider can streamline that process is welcome.
Find an AI Edge Processor That Meets Your Needs
The best AI-native edge processor for you varies based on device type, application and organizational goals. You’ll likely find an option that aligns with your needs among these seven manufacturers. Start by assessing your priorities, and the optimal choice should become evident.
Baburajan Kizhakedath
