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¼¼°èÀÇ Ä¨·¿ ½ÃÀå ±Ô¸ð, Á¡À¯À², µ¿Ç⠺м® º¸°í¼ : ÇÁ·Î¼¼¼ À¯Çüº°, ÆÐŰ¡ ±â¼úº°, ÃÖÁ¾»ç¿ëÀÚ »ê¾÷º°, Áö¿ªº°, ºÎ¹® ¿¹Ãø(2025-2033³â)Chiplet Market Size, Share & Trends Analysis Report By Processor Type (CPU Chiplets, GPU Chiplets, AI/ML Accelerators), By Packaging Technology (2.5D/3D Packaging, Multi-Chip Module), By End-user Industry, By Region, And Segment Forecasts, 2025 - 2033 |
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Chiplet Market Summary
The global chiplet market size was estimated at USD 9.06 billion in 2024 and is projected to reach USD 223.56 billion by 2033, growing at a CAGR of 43.7% from 2025 to 2033. The market is gaining momentum, driven by surging demand for AI and high-performance computing (HPC) workloads, which require scalable, modular processing architectures.
The rising cost and complexity of monolithic system-on-chips (SoCs) are encouraging a shift toward disaggregated chiplet-based designs that improve yield and reduce time-to-market. Additionally, rapid advancements in 2.5D/3D integration and advanced packaging technologies are making heterogeneous integration more feasible and cost-effective. The market also holds significant potential in edge AI and IoT applications, where power efficiency and customization are critical. However, high design and validation costs further act as a restraint, particularly for smaller players with limited R&D budgets.
The surging demand for AI and HPC workloads is driving significant advancements in chiplet technology to meet the need for scalable, efficient computing solutions. Industries across sectors such as healthcare, automotive, and finance increasingly rely on AI for data processing, while HPC applications require enhanced computational power for tasks such as simulations and analytics. Traditional monolithic chips face challenges in addressing these demands efficiently, making modular chiplet architectures more attractive due to their flexibility and cost-effectiveness. For instance, in March 2025, Axelera AI unveiled Titania, a scalable AI inference chiplet based on its Digital In-MemoryComputing (D-IMC) architecture. Supported by up to USD 66.2 million (EUR 61.6 million) in EU funding through the DARE Project, Titania targets edge-to-cloud AI and HPC applications, aligning with Europe's strategy for processor independence and extreme-scale computing.
As semiconductor nodes advance, the expense to design, manufacture, and validate large monolithic SoCs has escalated dramatically, with costs often ranging from hundreds of millions to over a billion dollars per chip, especially at cutting-edge process nodes like 3nm or 5nm. This increase is driven by the need for greater transistor counts, advanced packaging, and rigorous testing to ensure high yields. Chiplets, by contrast, offer a modular approach that divides functionality across smaller, easier-to-manufacture dies, reducing risk and cost. This modularity also accelerates development cycles and enhances yield by isolating defects to individual chiplets rather than the entire SoC, presenting a more cost-effective and scalable solution for complex semiconductor designs.
Rapid advancements in 2.5D/3D and advanced packaging technologies are driving significant growth in the chiplet market. These packaging innovations enable the integration of multiple heterogeneous dies within a single package, enhancing performance, power efficiency, and form factor compared to traditional monolithic chips. Techniques such as silicon interposers, through-silicon vias (TSVs), and chip-on-wafer-on-substrate (CoWoS) allow for high-density interconnects, reduced signal latency, and improved thermal management.
The expansion into Edge AI and IoT devices is being propelled by the increasing need for scalable, low-latency, and energy-efficient processing solutions that can operate closer to data sources. This trend is driven by the rapid adoption of smart devices, connected sensors, and real-time analytics in automotive and industrial automation applications. To address these demands, chiplet architectures offering modular and customizable integration have become essential, enabling improved performance and faster time-to-market for edge deployments. For instance, in January 2025, DreamBig announced advancements in its MARS Chiplet Platform, integrating 3D HBM-stacked Chiplet Hub and Networking IO Chiplets. Partnering with Samsung Foundry and Silicon Box, DreamBig aims to deliver high-performance AI, data center, and automotive solutions with reduced latency and enhanced energy efficiency. This indicates that chiplet-based platforms are critical enablers of next-generation edge AI and IoT innovations.
High design and validation costs significantly restrain the chiplet market, frequently totaling several million USD per project. The complexity of integrating multiple dies into a cohesive system demands extensive engineering resources, comprehensive testing, and thorough validation to ensure compatibility and reliability across diverse components. These substantial upfront expenses increase financial risk, particularly for smaller companies and startups, limiting broader adoption. Also, the high cost barrier slows innovation and market expansion despite the clear technological advantages of chiplet architectures.
Global Chiplet Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global chiplet market report based on processor type, packaging technology, end-user industry, and region: