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Publication: Sep 2024
Report Type: Sub-Tracker
Report Format: PDF DataSheet
Report ID: GAC43286 
  Pages: 110+  

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

Report Format: PDF DataSheet |   Pages: 110+  

 Sep 2024  | 

India Generative AI TPUs Chip Market Growth and Performance

  • 2023 saw the India generative AI TPUs chip market size rose to US$ 102.8 Million, marking a 42.9% YoY growth.
  • DataCube Research foresees, the generative AI TPUs chip market in India is set to make significant strides on the global stage, with projected revenue reaching US$ 1.68 Billion by 2032. Moreover, our analysis indicates a promising trajectory, an anticipated CAGR of 36.1% from 2024 to 2032.
  • Within the Indian generative AI TPUs chip market, our research highlights the dominance of the systolic arrays segment, which claimed the largest market share of 29.6% in 2023. This underscores the segment's robust position and potential for continued growth.
  • In our projections, we also pay close attention to end user dynamics. We anticipate the healthcare sector to emerge as a key driver of growth, expanding with a fastest CAGR of 41.0% during the forecast period spanning 2024 to 2032.

India 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
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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]