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市場調查報告書
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1907280

神經型態晶片：市場佔有率分析、產業趨勢與統計、成長預測（2026-2031）

Neuromorphic Chip - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

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簡介目錄

預計到 2025 年，神經型態晶片市場價值將達到 3.3 億美元，到 2031 年將達到 231.7 億美元，高於 2026 年的 6.7 億美元。

預計在預測期（2026-2031 年）內，複合年成長率將達到 103.1%。

神經形態晶片市場-IMG1

隨著類腦處理器突破馮諾依曼瓶頸，實現極高的能源效率並支援網路邊緣的即時決策，神經型態晶片市場正迅速擴張。智慧型手機和汽車中的邊緣人工智慧、不斷上漲的資料中心電力成本以及政府對類腦研發投入的增加，共同構成了一個良性循環，持續吸引資金和人才流入新產品開發領域。雖然汽車高級駕駛輔助系統（ADAS）目前佔據最大的商業性需求，但醫療、工業IoT和航太應用正在進一步拓展市場需求。由於類比、數位或混合訊號架構尚未形成事實上的標準，各廠商透過專有的儲存技術、軟體堆疊和特定領域的最佳化來凸顯自身優勢，因此市場競爭依然激烈。

全球神經型態晶片市場趨勢與洞察

消費和汽車領域對邊緣人工智慧的需求不斷成長

搭載高通驍龍8 Gen 3處理器的智慧型手機可提供45 TOPS的裝置端運算效能，徹底消除雲端延遲。這項技術為車載感知系統類似架構的開發鋪平了道路。汽車製造商正在採用神經形態處理器來滿足毫秒級響應目標和嚴格的散熱設計要求，而這一轉變正使ADAS（高級駕駛輔助系統）運行期間的電池消耗降低兩位數。

資料中心能源危機推動超低功耗運算

2023年，全球資料中心將消耗176兆瓦時（TWh）的電力，而人工智慧推理工作負載預計到2028年將使這項需求翻倍。 IBM的NorthPole晶片證明，與GPU相比，神經形態硬體在保持相似精確度的同時，可以達到25倍的節能效果。超大規模資料中心業者目前正在試驗混合機架，將Loihi 2叢集與傳統加速器結合，以協助控制不斷飆升的電力成本。

軟體和工具鏈生態系尚不成熟

開發人員被迫同時使用 Nengo、Lava 和 MetaTF 等編譯器，而缺乏所有硬體平台的統一編譯器導致計劃進度和整合成本大幅增加。企業 IT 團隊對採用 CUDA 等標準持謹慎態度，這抑制了短期採購熱情。

細分市場分析

儘管混合訊號裝置體積小巧，但預計它們將成為神經型態晶片市場的主要成長引擎，複合成長率高達105.2%。類比-數位混合拓樸結構比純數位邏輯更能自然捕捉突觸的連續動態特性，同時利用CMOS製程來實現可擴展性。預計到2025年，數位晶片仍將佔據神經型態晶片市場43.62%的佔有率，這主要得益於成熟的EDA支援和便利的軟體移植性。雖然用於數位產品的神經型態晶片市場規模預計將會擴大，但由於混合訊號技術的興起，其相對重要性預計將會下降。三星等廠商正在致力於將混合訊號技術應用於行動AI推理，而Start-Ups則在改進用於微瓦級感測器節點的類比模組。投資重點集中在製程相容的電阻式儲存陣列上，這種陣列可以減少突觸的體積和刷新開銷。

混合訊號技術的強勁發展勢頭源於其能夠以低於100毫瓦的功耗提供即時邊緣智慧，從而推動自主無人機、智慧耳機和植入式醫療設備的普及。一款於2025年發布的碳基三元邏輯原型展示了材料創新將如何進一步降低面積和能耗。數位技術廠商正透過片上SRAM整合來降低資料傳輸延遲，但類比技術的動態範圍和局部優勢仍需迎頭趕上。隨著晶圓代工廠不斷改進製程配方，混合訊號技術的產量比率挑戰將有所緩解，並有望在2031年之前削弱數位科技的統治地位。

由於脈衝神經網路具有軟體親和性，預計到2025年，其收入將佔36.35%。同時，ReRAM交叉陣列將在神經型態晶片市場維持最快的成長速度，複合年成長率高達104.8%。交叉陣列將多位元權重儲存在記憶體中，融合了運算和儲存功能，從而最大限度地減少資料傳輸。概念驗證系統在功耗僅為個位數毫瓦的情況下，實現了94.6%的MNIST準確率。雖然與脈衝神經元相關的神經型態晶片的市場規模將繼續成長，但隨著電阻式裝置尺寸的縮小，其市場佔有率將會下降。相變記憶體將在對壽命要求極高的工作負載中發揮輔助作用。

這種架構轉變也標誌著設計理念正從以神經元為中心轉變為以記憶體為中心。 DenRAM 圖將時間動態直接編碼到電阻狀態中，進而提升序列學習能力。然而，脈衝神經網路在稀疏事件處理方面仍然具有優勢，使其在視覺感測器和雷達領域極具吸引力。產業藍圖擴大採用異質晶片提案，將這些範式整合到單一中介層上，從而加速軟體重用和系統整合。

區域分析

2025年，北美在神經型態晶片市場將維持34.85%的佔有率，這得益於DARPA的資助以及英特爾擁有11.5億個神經元的Hala Point平台。該地區產學研合作蓬勃發展，麻省理工學院的整合光子處理器能夠在亞納秒內完成神經運算，準確率超過92%，預示未來有望衍生出商業化產品。加拿大Nengo Software等公司的工具開發技術正在推動整個生態系統的成熟，並吸引創業投資湧入矽谷新興企業。

儘管亞太地區絕對規模較小，但卻是神經型態晶片市場成長最快的地區，預計到2031年將以104.7%的複合年成長率成長。中國的達爾文猴系統由960個達爾文3晶片組成，包含20億個神經元，展​​現了中國在人工智慧硬體領域實現戰略自主的決心。韓國正透過與歐盟500萬歐元的夥伴關係來推進自旋電子半導體的發展，而日本的一個財團則將相變記憶體與邊緣攝影機結合，以推進工廠自動化。印度的國家光子晶片計畫和新加坡的神經形態機器人研究所完善了該地區多元化的研發版圖。

歐洲仍然是重要的第二大研發中心，利用「地平線」計畫的資金大力投資電阻式記憶體和事件驅動視覺研究。德國汽車製造商主導ADAS試點項目，整合脈衝神經網路協處理器，並利用本地一級供應商提供汽車級封裝。瑞士公司SynSense正向歐洲無人機OEM廠商供應功耗低於1毫瓦的DSP模組，凸顯了跨國供應鏈的綜效。監管機構在隱私和永續性的領導地位正在影響全球設計目標，鼓勵晶片製造商實施透明的功耗報告和設備端資料保存。

其他福利：

  • Excel格式的市場預測（ME）表
  • 分析師支持（3個月）

目錄

第1章 引言

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章 市場情勢

  • 市場概覽
  • 市場促進因素
    • 消費和汽車領域對邊緣人工智慧的需求不斷成長
    • 資料中心能源危機推動超低功耗運算
    • 政府主導腦研究與發展計劃
    • 事件驅動型感測器和SoC整合浪潮
    • 對衛星搭載式人工智慧處理的需求
    • OT網路安全異常檢測要求
  • 市場限制
    • 軟體和工具鏈生態系尚不成熟
    • 模擬非揮發性記憶體（NVM）的製造差異
    • 缺乏尖峰系統測試和檢驗標準
    • 醫療設備監管的路徑尚不明朗。
  • 產業價值鏈分析
  • 監管環境
  • 技術展望
  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭對手之間的競爭
  • 神經型態晶片的新應用案例
  • 宏觀經濟趨勢如何影響市場
  • 投資分析

第5章 市場規模與成長預測

  • 按晶片類型
    • 模擬
    • 數位的
    • 混合訊號
  • 建築設計
    • 脈衝神經網路
    • 基於ReRAM的架構
    • 相變記憶體架構
  • 按最終用戶行業分類
    • 汽車（ADAS/AV）
    • 工業IoT和機器人技術
    • 家用電子電器
    • 金融服務及網路安全
    • 醫療和醫療設備
    • 航太/國防
  • 按部署模式
    • 邊緣設備
    • 資料中心/雲
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 南美洲其他地區
    • 歐洲
      • 德國
      • 英國
      • 法國
      • 義大利
      • 其他歐洲地區
    • 亞太地區
      • 中國
      • 日本
      • 韓國
      • 印度
      • 亞太其他地區
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 其他中東地區
    • 非洲
      • 南非
      • 其他非洲地區

第6章 競爭情勢

  • 市場集中度
  • 策略趨勢
  • 市佔率分析
  • 公司簡介
    • Intel Corporation
    • International Business Machines Corporation
    • Samsung Electronics Co., Ltd.
    • SK hynix Inc.
    • BrainChip Holdings Ltd
    • SynSense AG
    • GrAI Matter Labs SAS
    • Nepes Corporation
    • Qualcomm Technologies, Inc.
    • Micron Technology, Inc.
    • Synaptics Incorporated
    • Innatera Nanosystems BV
    • Prophesee SA
    • MemryX Inc.
    • Mythic Inc.
    • Syntiant Corp.
    • Gyrfalcon Technology Inc.
    • Applied Brain Research Inc.
    • General Vision Inc.
    • Vicarious Corp.

第7章 市場機會與未來展望

簡介目錄
Product Code: 54455

The neuromorphic chip market was valued at USD 0.33 billion in 2025 and estimated to grow from USD 0.67 billion in 2026 to reach USD 23.17 billion by 2031, at a CAGR of 103.1% during the forecast period (2026-2031).

Neuromorphic Chip - Market - IMG1

The neuromorphic chip market is accelerating because brain-inspired processors overcome the von Neumann bottleneck, unlock extreme energy efficiency, and enable real-time decision-making at the network edge. Edge artificial intelligence in smartphones and vehicles, mounting data-center electricity costs, and rising government funding for brain-inspired R&D collectively create a flywheel that keeps capital and talent flowing into new product launches. Automotive advanced driver-assistance systems (ADAS) currently absorb the largest commercial volumes, while healthcare, industrial IoT, and aerospace applications provide additional demand diversity. Competition remains intense because no single architecture, analog, digital, or mixed-signal, has emerged as a de facto standard, pushing vendors to differentiate through proprietary memory technologies, software stacks, and domain-specific optimizations.

Global Neuromorphic Chip Market Trends and Insights

Rising Edge-AI Demand in Consumer and Automotive

Smartphones built on Qualcomm's Snapdragon 8 Gen 3 now perform 45 TOPS on-device, eliminating cloud latency and inspiring similar architectures for in-car perception systems. Automotive OEMs adopt neuromorphic processors to meet millisecond response targets and stringent thermal envelopes, a shift that lowers battery drain by double-digit margins during ADAS operation.

Data-Center Energy Crisis Favoring Ultra-Low-Power Compute

Global data centers consumed 176 TWh in 2023, and AI inference workloads threaten to double electricity demand by 2028. IBM's NorthPole chip proves neuromorphic hardware can deliver 25-fold energy savings over GPUs while sustaining similar accuracy. Hyperscalers now pilot hybrid racks that pair Loihi 2 clusters with conventional accelerators to curb spiraling utility bills.

Immature Software and Toolchain Ecosystem

Developers juggle Nengo, Lava, and MetaTF because no unified compiler spans every hardware platform, inflating project timelines and integration costs. Enterprise IT teams hesitate until a CUDA-like standard emerges, dampening short-term procurement.

Other drivers and restraints analyzed in the detailed report include:

  1. Government Brain-Inspired R&D Programs
  2. Event-Driven Sensor-SoC Integration Wave
  3. Fabrication Variability of Analog NVM

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Mixed-signal devices, though representing a smaller base, will compound at 105.2% to become the principal growth engine for the neuromorphic chip market. Their hybrid analog-digital topology captures continuous synaptic dynamics more naturally than purely digital logic, yet still leverages CMOS toolflows for scale. Digital chips preserved a 43.62% neuromorphic chip market share in 2025, owing to mature EDA support and easier software portability. The neuromorphic chip market size allocated to digital products is projected to expand, but its relative weight will slip as mixed-signal gains traction. Vendors such as Samsung pursue mixed-signal for mobile AI inference, while start-ups refine analog blocks for micro-watt sensor nodes. Investment gravitates toward process-compatible resistive memory arrays that shrink synapse footprints and cut refresh overhead.

Mixed-signal's momentum reflects its capacity to deliver real-time edge intelligence at sub-100 mW levels, enabling autonomous drones, smart ear buds, and implantable medical devices. Carbon-based ternary logic prototypes unveiled in 2025 illustrate how material innovation could further compress area and energy envelopes. Digital incumbents respond by integrating on-chip SRAM to reduce data shuttling penalties, yet must match analog's dynamic range and locality advantages. As foundries refine process recipes, mixed-signal yield headwinds will abate, positioning the category to erode digital's dominance through 2031.

Spiking neural networks commanded 36.35% of 2025 revenue thanks to software familiarity, but ReRAM crossbars are on track for a 104.8% CAGR, the fastest within the neuromorphic chip market. Crossbar arrays store multi-bit weights in-memory, fusing compute and storage to minimize data movement. Proof-of-concept systems achieved 94.6% MNIST accuracy while consuming single-digit milliwatts. The neuromorphic chip market size tied to spiking neurons will still expand in absolute terms, though its share slides as resistive devices scale. Phase-change memory holds a supporting role for endurance-critical workloads.

The architecture shift also signals a broader move from neuron-centric to memory-centric design; DenRAM diagrams encode temporal dynamics directly in resistive states, improving sequence learning. Spiking networks, however, retain an edge in sparse event processing, keeping them attractive for vision sensors and radar. Industry roadmaps increasingly propose heterogeneous chips that combine these paradigms on a single interposer, accelerating software reuse and system integration.

The Neuromorphic Chip Market Report is Segmented by Chip Type (Analog, Digital, Mixed-Signal), Architecture (Spiking Neural Network, ReRAM-Based Architectures, and More), End-User Industry (Automotive, Industrial IoT & Robotics, and More), Deployment Model (Edge Devices, Data-centre/Cloud), and Geography (North America, South America, Europe, Asia-Pacific, and More). The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America preserved 34.85% neuromorphic chip market share in 2025 on the back of DARPA funding and Intel's 1.15 billion-neuron Hala Point platform. The region hosts robust academic-industry linkages; MIT's integrated photonic processor completed neural computations in sub-nanosecond intervals while retaining more than 92% accuracy, signaling future spin-outs into commercial stacks. Canadian tooling expertise, highlighted by Nengo software, further entrenches the ecosystem's maturity and draws venture capital to Silicon Valley start-ups.

Asia-Pacific, though smaller in absolute terms, is the neuromorphic chip market's fastest-growing territory with a forecast 104.7% CAGR to 2031. China's Darwin Monkey system offers 2 billion neurons across 960 Darwin 3 chips, demonstrating the state's commitment to strategic autonomy in AI hardware. South Korea's EUR 5 million EU partnership advances spintronic semiconductors, while Japanese consortia pair phase-change memory with edge cameras for factory automation. India's national photonic-chip initiative and Singapore's neuromorphic robotics labs round out the region's diversified R&D map.

Europe remains a pivotal secondary hub, channeling Horizon funds into resistive memory and event-driven vision research. German automakers spearhead ADAS pilots that integrate Spiking Neural Network coprocessors, leveraging local tier-ones for vehicle-grade packaging. Swiss firm SynSense supplies sub-1 mW DSP blocks to European drone OEMs, underscoring cross-border supply-chain synergies. Regulatory leadership in privacy and sustainability influences global design targets, nudging chipmakers toward transparent power reporting and on-device data retention.

  1. Intel Corporation
  2. International Business Machines Corporation
  3. Samsung Electronics Co., Ltd.
  4. SK hynix Inc.
  5. BrainChip Holdings Ltd
  6. SynSense AG
  7. GrAI Matter Labs SAS
  8. Nepes Corporation
  9. Qualcomm Technologies, Inc.
  10. Micron Technology, Inc.
  11. Synaptics Incorporated
  12. Innatera Nanosystems BV
  13. Prophesee SA
  14. MemryX Inc.
  15. Mythic Inc.
  16. Syntiant Corp.
  17. Gyrfalcon Technology Inc.
  18. Applied Brain Research Inc.
  19. General Vision Inc.
  20. Vicarious Corp.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 Introduction

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 Research Methodology

3 Executive Summary

4 Market Landscape

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Rising edge-AI demand in consumer and automotive
    • 4.2.2 Data-center energy crisis favouring ultra-low-power compute
    • 4.2.3 Government brain-inspired R&D programmes
    • 4.2.4 Event-driven sensor-SoC integration wave
    • 4.2.5 On-board satellite AI processing need
    • 4.2.6 OT-cybersecurity anomaly detection requirements
  • 4.3 Market Restraints
    • 4.3.1 Immature software and toolchain ecosystem
    • 4.3.2 Fabrication variability of analog NVM
    • 4.3.3 Lack of spike-system test/validation standards
    • 4.3.4 Unclear medical-device regulatory path
  • 4.4 Industry Value Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Porter's Five Forces Analysis
    • 4.7.1 Bargaining Power of Suppliers
    • 4.7.2 Bargaining Power of Buyers
    • 4.7.3 Threat of New Entrants
    • 4.7.4 Threat of Substitute Products
    • 4.7.5 Intensity of Competitive Rivalry
  • 4.8 Emerging Use-Cases for Neuromorphic Chips
  • 4.9 Impact of Macroeconomic Trends on the Market
  • 4.10 Investment Analysis

5 Market Size and Growth Forecasts (Value)

  • 5.1 By Chip Type
    • 5.1.1 Analog
    • 5.1.2 Digital
    • 5.1.3 Mixed-Signal
  • 5.2 By Architecture
    • 5.2.1 Spiking Neural Network
    • 5.2.2 ReRAM-based Architectures
    • 5.2.3 Phase-Change-Memory Architectures
  • 5.3 By End-User Industry
    • 5.3.1 Automotive (ADAS / AV)
    • 5.3.2 Industrial IoT and Robotics
    • 5.3.3 Consumer Electronics
    • 5.3.4 Financial Services and Cybersecurity
    • 5.3.5 Healthcare and Medical Devices
    • 5.3.6 Aerospace and Defense
  • 5.4 By Deployment Model
    • 5.4.1 Edge Devices
    • 5.4.2 Data-centre / Cloud
  • 5.5 By Geography
    • 5.5.1 North America
      • 5.5.1.1 United States
      • 5.5.1.2 Canada
      • 5.5.1.3 Mexico
    • 5.5.2 South America
      • 5.5.2.1 Brazil
      • 5.5.2.2 Argentina
      • 5.5.2.3 Rest of South America
    • 5.5.3 Europe
      • 5.5.3.1 Germany
      • 5.5.3.2 United Kingdom
      • 5.5.3.3 France
      • 5.5.3.4 Italy
      • 5.5.3.5 Rest of Europe
    • 5.5.4 Asia-Pacific
      • 5.5.4.1 China
      • 5.5.4.2 Japan
      • 5.5.4.3 South Korea
      • 5.5.4.4 India
      • 5.5.4.5 Rest of Asia-Pacific
    • 5.5.5 Middle East
      • 5.5.5.1 Saudi Arabia
      • 5.5.5.2 United Arab Emirates
      • 5.5.5.3 Rest of Middle East
    • 5.5.6 Africa
      • 5.5.6.1 South Africa
      • 5.5.6.2 Rest of Africa

6 Competitive Landscape

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
    • 6.4.1 Intel Corporation
    • 6.4.2 International Business Machines Corporation
    • 6.4.3 Samsung Electronics Co., Ltd.
    • 6.4.4 SK hynix Inc.
    • 6.4.5 BrainChip Holdings Ltd
    • 6.4.6 SynSense AG
    • 6.4.7 GrAI Matter Labs SAS
    • 6.4.8 Nepes Corporation
    • 6.4.9 Qualcomm Technologies, Inc.
    • 6.4.10 Micron Technology, Inc.
    • 6.4.11 Synaptics Incorporated
    • 6.4.12 Innatera Nanosystems BV
    • 6.4.13 Prophesee SA
    • 6.4.14 MemryX Inc.
    • 6.4.15 Mythic Inc.
    • 6.4.16 Syntiant Corp.
    • 6.4.17 Gyrfalcon Technology Inc.
    • 6.4.18 Applied Brain Research Inc.
    • 6.4.19 General Vision Inc.
    • 6.4.20 Vicarious Corp.

7 Market Opportunities and Future Outlook

  • 7.1 White-space and Unmet-need Assessment