Neural Processing Units (NPUs) Global Market Report 2026

A neural processing unit (NPU) is a dedicated hardware processor specifically built to accelerate artificial intelligence and machine learning workloads, particularly neural network computations. It efficiently handles matrix operations, parallel processing, and inference tasks compared with traditional CPUs or GPUs. NPUs deliver faster, low-power AI performance across devices such as smartphones, laptops, edge systems, and data-center accelerators.

The primary types of neural processing units (NPUs) include standalone and integrated NPUs. Standalone NPUs are dedicated accelerators that independently execute AI and deep learning workloads. They support deep learning, machine learning, and natural language processing across embedded, discrete, and cloud-based deployments, serving computer vision, robotics, autonomous vehicles, healthcare diagnostics, and more across consumer electronics, automotive, healthcare, and IT and telecom sectors.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

Tariffs are impacting the neural processing unit market by increasing costs of imported semiconductor wafers, advanced packaging materials, lithography equipment, and electronic components essential for npu manufacturing. asia-pacific regions such as taiwan and south korea are most affected due to their central role in chip fabrication, while north america faces higher design and prototyping costs. these tariffs are elevating production expenses and influencing pricing strategies for consumer and enterprise devices. however, they are also encouraging domestic semiconductor investments, regional fabrication expansion, and long-term supply chain diversification for ai hardware.

The neural processing units (npus) market research report is one of a series of new reports from The Business Research Company that provides neural processing units (npus) market statistics, including neural processing units (npus) industry global market size, regional shares, competitors with a neural processing units (npus) market share, detailed neural processing units (npus) market segments, market trends and opportunities, and any further data you may need to thrive in the neural processing units (npus) industry. This neural processing units (npus) market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The neural processing unit (NPU) market size has grown exponentially in recent years. It will grow from $5.01 billion in 2025 to $6.25 billion in 2026 at a compound annual growth rate (CAGR) of 24.9%. The growth in the historic period can be attributed to increasing adoption of artificial intelligence (AI)-enabled devices, growing demand for on-device neural computing, rising deployment of edge artificial intelligence (AI) applications, expanding use of deep learning workloads, and increasing requirement for low-power, high-performance processors.

The neural processing unit (NPU) market size is expected to see exponential growth in the next few years. It will grow to $15.06 billion in 2030 at a compound annual growth rate (CAGR) of 24.6%. The growth in the forecast period can be attributed to growing integration of neural processing units (NPUs) in smartphones and wearables, increasing adoption of autonomous and artificial intelligence (AI)-driven systems, rising demand for real-time inference processing, expanding deployment of intelligent edge infrastructure, and growing emphasis on energy-efficient artificial intelligence (AI) accelerators. Major trends in the forecast period include technology advancements in heterogeneous artificial intelligence (AI) architectures, innovations in low-power neural acceleration, developments in chiplet-based neural processing unit (NPU) designs, research and development in advanced artificial intelligence (AI) model optimization, and advancements in on-device learning and federated artificial intelligence (AI) systems.

The rising use of smartphones is anticipated to drive the expansion of the neural processing units (NPUs) market in the coming years. Smartphones are advanced mobile devices that support internet connectivity, application usage, and real-time communication. Smartphone usage is increasing due to the rapid growth of mobile internet connectivity, which enables users to access digital platforms and conduct activities from anywhere at any time. Greater smartphone adoption strengthens demand for neural processing units by accelerating the need for fast and energy-efficient on-device artificial intelligence computing. NPUs enhance performance and user experience by enabling real-time processing for applications such as image recognition, natural language understanding, and augmented reality. For instance, in November 2024, according to Eurostat, the Luxembourg-based statistical office of the European Union, approximately 89% of EU residents aged 16-74 living in cities used smartphones to access the internet in 2023, compared with 86% in towns and suburbs and 82% in rural areas. Therefore, the increasing smartphone penetration is driving the growth of the neural processing units (NPUs) market.

Major companies operating in the neural processing units (NPUs) market are concentrating on the development of technologically advanced products, such as on-device NPUs, to enable real-time AI processing directly on end devices. On-device NPUs are neural processing units embedded within devices such as smartphones, laptops, and IoT hardware, allowing artificial intelligence workloads to be executed locally for faster, more energy-efficient, and privacy-focused AI processing. For example, in October 2023, Qualcomm Technologies Inc., a US-based semiconductor company, introduced the Snapdragon 8 Gen 3 mobile platform, which features an enhanced Hexagon NPU delivering up to 98% faster AI performance and approximately 40% better performance per watt compared with its predecessor. The platform enables on-device generative AI and advanced camera AI pipelines for real-time inference. This launch represents a major technological advancement by bringing high-efficiency neural processing to mainstream mobile and edge platforms, bridging on-device intelligence with energy-optimized performance. It provides a scalable and efficient solution for delivering responsive AI experiences while reducing dependence on cloud infrastructure.

In October 2025, NXP Semiconductors, a Netherlands-based semiconductor company specializing in automotive, industrial, and IoT solutions, acquired Kinara Inc. for an undisclosed amount. Through this acquisition, NXP aims to enhance its edge AI portfolio by incorporating Kinara's high-performance, power-efficient Discrete Neural Processing Units (DNPUs), enabling real-time, secure, and energy-efficient on-device AI inference for applications such as factory automation, smart cameras, and intelligent vehicles. Kinara Inc. is a US-based AI semiconductor company that focuses on edge AI accelerators, AI chips, and neural processing solutions.

Major companies operating in the neural processing units (npus) market are Amazon.com Inc., Apple Inc., Google LLC, Samsung Electronics Co. Ltd., Huawei Technologies Co. Ltd., NVIDIA Corporation, Intel Corporation, Qualcomm Incorporated, Advanced Micro Devices Inc., Baidu Inc., MediaTek Inc., Synopsys Inc., Cadence Design Systems Inc., Arm Ltd., VeriSilicon Holdings Co. Ltd., BrainChip Holdings Ltd., Cambricon Technologies Corporation, Cerebras Systems Inc., Mythic Inc., SiMa.ai Inc., Kneron Inc., Syntiant Corp., Horizon Robotics Inc., Graphcore Ltd., Blaize Inc.

North America was the largest region in the neural processing unit (NPU) market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the neural processing units (npus) market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the neural processing units (npus) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The neural processing units (NPUs) market consists of revenues earned by entities by providing services ai model acceleration, neural network processing, real-time inference, image and video recognition, natural language processing acceleration, edge ai computing, energy-efficient ai execution, hardware-level optimization, on-device machine learning, predictive analytics acceleration, sensor data processing and computer vision enhancement. The market value includes the value of related goods sold by the service provider or included within the service offering. The neural processing unit (NPU) market includes sales of edge neural processing units (NPUs), mobile neural processing units (NPUs), cloud-based neural processing units (NPUs), embedded/iot neural processing units (NPUs), server-grade neural processing units (NPUs), ai accelerator neural processing units (NPUs), vision-specific neural processing units (NPUs), low-power neural processing units (NPUs) and high-performance compute neural processing units (NPUs). Values in this market are 'factory gate' values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Neural Processing Units (NPUs) Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses neural processing units (npus) market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for neural processing units (npus) ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The neural processing units (npus) market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

• The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
• The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
• The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
• The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
• The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
• The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
• The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
• The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
• Market segmentations break down the market into sub markets.
• The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
• Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
• The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
• The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.

Scope

• Markets Covered:1) By Type: Standalone Neural Processing Units (NPUs); Integrated Neural Processing Units (NPUs)
• 2) By Technology: Deep Learning; Machine Learning; Natural Language Processing; Other Technologies
• 3) By Form Factor: Embedded Neural Processing Units (NPUs); Discrete Neural Processing Units (NPUs); Cloud-based Neural Processing Units (NPUs)
• 4) By Application: Natural Language Processing; Computer Vision; Robotics; Autonomous Vehicles; Healthcare and Diagnostics
• 5) By End-User: Consumer Electronics; Automotive; Healthcare; Information Technology (IT) and Telecommunications; Other End-Users
• Subsegments:
• 1) By Standalone Neural Processing Units (NPUs): High Performance Neural Compute Modules; Dedicated Artificial Intelligence Acceleration Units; Edge Deployment Processing Systems; Independent Neural Inference Engines; Customizable Artificial Intelligence Hardware Platforms
• 2) By Integrated Neural Processing Units (NPUs): System on Chip Embedded Neural Modules; Processor Integrated Artificial Intelligence Cores; Mobile Device Neural Acceleration Units; Multi Function Computing Chipsets; Hybrid Processing and Neural Optimization Engines
• Companies Mentioned: Amazon.com Inc.; Apple Inc.; Google LLC; Samsung Electronics Co. Ltd.; Huawei Technologies Co. Ltd.; NVIDIA Corporation; Intel Corporation; Qualcomm Incorporated; Advanced Micro Devices Inc.; Baidu Inc.; MediaTek Inc.; Synopsys Inc.; Cadence Design Systems Inc.; Arm Ltd.; VeriSilicon Holdings Co. Ltd.; BrainChip Holdings Ltd.; Cambricon Technologies Corporation; Cerebras Systems Inc.; Mythic Inc.; SiMa.ai Inc.; Kneron Inc.; Syntiant Corp.; Horizon Robotics Inc.; Graphcore Ltd.; Blaize Inc.
• Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain
• Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
• Time Series: Five years historic and ten years forecast.
• Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
• Data Segmentations: country and regional historic and forecast data, market share of competitors, market segments.
• Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
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