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Publication: Sep 2024
Report Type: Sub-Tracker
Report Format: PDF DataSheet
Report ID: GAC43226 
  Pages: 160+  

Asia Pacific Generative AI TPUs Chip Market Size and Forecast by Architecture Type, Node Type, End User Application, Distribution Channel, Memory Integration, and Region: Statistics | 2019-2032

Report Format: PDF DataSheet |   Pages: 160+  

 Sep 2024  | 

Asia Pacific Generative AI TPUs Chip Market Growth and Performance

  • In 2023, the Asia Pacific generative AI TPUs chip market size reached US$ 1.13 Billion, growing by 42.8% compared to previous year.
  • The generative AI TPUs chip market in Asia Pacific is projected to expand at a CAGR of 27.2% throughout the forecast period to reach US$ 9.89 Billion in 2032.
  • Contribution by the matrix multiplication accelerators sub-segment to overall architecture type segment revenue is expected to surge to US$ 3.29 Billion by 2032.
  • With 25.5% market share, the consumer electronics sector was the largest end-user vertical for prominent generative AI TPUs chip players in 2023

Asia Pacific Generative AI TPUs Chip Market Scope

Analysis Period

2019-2032

Actual Data

2019-2023

Base Year

2024

Estimated Year

2024

CAGR Period

2024-2032
 

Research Scope

Architecture Type

Matrix Multiplication Accelerator

Systolic Array

Neural Network Processing Units (NPUs

Hybrid Architecture

Node Type

Advanced Nod

Mid-range Nod

Legacy Nod

End User Application

Consumer Electronic

Automotiv

Industria

Telecommunication

Healthcare

Aerospace & Defens

Energ

Data Processin

Distribution Channel

Direct Sale

Distributors and Reseller

Online Marketplace

Memory Integration

High-Bandwidth Memory (HBM

GDDR Memor

On-Chip Memor

 

Asia Pacific Generative AI TPUs Chip Industry: Country Coverage

 

Countries

Asia Pacific

Japa

Australi

Chin

South Kore

Indi

Malaysi

Hong Kon

Indonesi

New Zealan

Singapor

Thailan

Vietna

Philippine

Taiwa

Rest of Asia Pacifi
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*Research Methodology: This report is based on DataCube’s proprietary 3-stage forecasting model, combining primary research, secondary data triangulation, and expert validation. [Learn more]