Google's TPUs have made headlines across the AI world, following reports of external adoption; however, there's an angle to this that might prove to be a significant constraint.
Google's 'Ironwood' AI Chips Are Seeing Immense Market Spotlight, But There's a Problem With This
The interest around ASICs is massive in today's world of AI computing, mainly since it is believed that in the next layer of AI application, which is inferencing, chips like Google's TPUs will dominate with better TCOs and performance capabilities. Following the introduction of Google's 7th-generation Ironwood TPUs, companies like Meta and Anthropic showed interest in integrating the ASICs into their workloads, and the narrative of TPUs being externally adopted gained momentum. However, supply chain constraints pose a significant challenge for Google if it intends to enter the infrastructure market.
According to a report by ChinaTimes, it is revealed that Google's TPUs may not meet market expectations in terms of chip volume, primarily due to the company's difficulty in securing advanced packaging supplies from suppliers like TSMC, which is necessary for a successful ramp-up. Technologies, such as CoWoS, are one way chip manufacturers have scaled up performance tremendously relative to previous generations. In the case of TPUv7, Google has adopted an MCM (Multi-Chip Module) design, which allows the firm to integrate multiple chips into a unified package.
Instead of a large monolithic die, TPUv7 integrates several silicon dies on a silicon interposer, featuring microbump arrays to connect the chiplets. This ultimately allows for scalability and specifically optimizes the internal design for matrix multipliers and inference fabric. Interestingly, Ironwood also integrates networking PHYs and routing logic directly into the package through interposer routing, ultimately resulting in ultra-low-latency D2D connections. Advanced packaging is an integral part of Google's TPU technology stack, which is why the firm must secure sufficient capacity to increase external adoption.
Fubon Research predicts that Google TPU shipments in 2026 will be lower than projections made by mainstream analyst companies, mainly since the CoWoS bottleneck is too significant to ignore. TSMC's existing supply chain is fully committed to products from Apple and NVIDIA, which is why bringing in extra customers for advanced packaging is a problematic move, even after the large-scale spending TSMC is making to increase production capacity. Since Google would be a relatively new entrant in the supply chain when it comes to volume manufacturing, it is certainly at the end of the queue.
This certainly doesn't mean that TPUs wouldn't be adopted, but rather the bottlenecks within the industry make it difficult for Google to offer its custom silicon to a wide range of customers. One way Google could address this situation is by utilizing firms like Intel or Amkor for advanced packaging, and the tech giant is already rumored to be exploring EMIB-T solutions. The AI supply chain is highly unpredictable when it comes to catering to customer orders, which is why we cannot be certain about what Google's next step will be.
About the author: Muhammad Zuhair is a hardware and technology reporter for Wccftech, specializing in the semiconductor industry and the complex interplay between technology, manufacturing, and geopolitics. His coverage focuses on the corporate strategies and technological roadmaps of industry giants like TSMC, NVIDIA, Samsung, and Intel. Zuhair's expertise lies in deconstructing complex topics such as fabrication nodes (e.g., 2nm process), the economic impact of policies like the CHIPS Act, and the strategic development of AI infrastructure from NVIDIA, AMD and Intel.
Follow Wccftech on Google to get more of our news coverage in your feeds.
