NPU market seen topping $13 billion by 2030

The neural processing units market is projected to surge through 2030 as edge AI, computer vision and energy-efficiency demands push adoption across consumer devices, automotive systems and data centers. Asia-Pacific and China are expected to lead the expansion, while Apple holds the top sales position in 2025.

Why it matters: - Neural processing units are becoming a core chip category for AI workloads that need low power, low latency and on-device processing. - The market’s growth signals broader adoption of edge AI across smartphones, cameras, industrial systems, robotics and autonomous vehicles. - The shift also matters for semiconductor vendors competing to supply specialized AI hardware as demand rises.

What happened: - The Business Research Company released its Global Market Report 2026 on neural processing units, covering market size, trends and forecasts for 2026-2035. - The report puts the global NPU market at more than $13 billion by 2030, with a 22% compound annual growth rate. - NPUs are expected to account for about 44% of the broader tensor processing unit market, which is forecast to reach about $30 billion by 2030. - The report says NPUs will represent roughly 0.2% of the wider electrical and electronics industry, projected at $5,579 billion in 2030. - The report is available through the company’s announcement.

The details: - Standalone NPUs are projected to hold 74% of the market by 2030, or about $10 billion. - Demand for dedicated AI acceleration hardware is driving standalone adoption in edge inference and on-premises deployments. - Modular AI accelerator cards, latency-sensitive compute units and efficiency gains in chip architecture are supporting that shift. - The market spans deep learning, machine learning, natural language processing and other technology types. - NPU form factors include embedded, discrete and cloud-based designs. - Key applications include natural language processing, computer vision, robotics, autonomous vehicles and healthcare diagnostics. - Major end markets include consumer electronics, automotive, healthcare, and IT and telecommunications. - Asia-Pacific is forecast to become the largest regional market, reaching $5 billion by 2030 from $2 billion in 2025, at a 23% CAGR. - China is projected to be the largest single-country market, reaching $3 billion by 2030 from $1 billion in 2025, also at a 23% CAGR. - Apple led global NPU sales in 2025 with a 3% market share. - Other major competitors include Qualcomm, NVIDIA, Huawei, Samsung, Google, Intel, AMD, Amazon and Arm. - The top 10 firms accounted for 28% of revenue in 2025, indicating a moderately fragmented market. - The report says entry barriers remain moderate to high because of semiconductor complexity, R&D intensity and fast innovation cycles. - Indie Semiconductor launched the iND881 edge AI SoC in June 2026, combining an NPU, a DSP and an Arm Cortex-A53 CPU for automotive and robotics perception systems. - The iND881 supports multi-camera ISP integration and up to 2 TOPS of NPU performance for object detection, sensor fusion and real-time decision-making in ADAS and autonomous vehicles.

Between the lines: - Edge AI is the clearest demand driver because companies want faster decisions closer to the device and less dependence on cloud processing. - Energy efficiency is becoming a purchasing criterion, not just a technical feature, as battery life and operating costs matter more in mobile and industrial use cases. - The regional growth picture points to Asia-Pacific as both a manufacturing hub and a major demand center for AI-enabled devices and semiconductor investment. - The competitive picture suggests that scale, ecosystem integration and product breadth may matter as much as raw chip performance.

What's next: - The report expects standalone and integrated NPUs to add more than $8 billion in combined market value between 2025 and 2030. - Standalone NPUs are projected to add $6 billion over that period, while integrated NPUs add $2 billion. - Further growth is expected from chiplet packaging, heterogeneous computing, AI-driven automation and faster integration into next-generation edge devices. - Companies are likely to keep focusing on edge AI architectures, lower-latency designs and broader NPU integration across devices and systems.

The bottom line: - NPUs are moving from niche accelerator chips to a mainstream enabler of efficient AI, with the strongest momentum coming from edge devices, Asia-Pacific demand and energy-conscious computing.