Google (NASDAQ: GOOGL) is preparing for a major expansion of its AI infrastructure in 2026 as it moves its seventh-generation Tensor Processing Unit (TPU), known as Ironwood, into mass deployment. This next phase marks a significant step in Google’s long-term strategy to scale artificial intelligence workloads while intensifying competition with GPU-based systems, though not fully replacing them.
According to Fubon Research, the TPU v7 program represents a fundamental shift in how Google designs and scales computing. Instead of focusing on individual servers, Google is elevating the unit of design to entire racks, tightly integrating hardware, networking, power, and software at the system level. This approach allows for more efficient large-scale AI training and inference while optimizing cost and performance.
Unlike GPUs, which are general-purpose accelerators, TPUs are application-specific integrated circuits (ASICs) built specifically for AI workloads. Fubon analysts note that TPUs rely on static matrix arrays that require pre-defined data streams and kernels before computation begins, contrasting with GPUs that can dynamically initiate hardware kernels at runtime. Despite Google’s advances, Nvidia GPUs retain strong competitive advantages due to the maturity of the CUDA ecosystem and the high cost and complexity of porting existing AI codebases.
Ironwood introduces a dual-chiplet design to improve manufacturing yield and cost efficiency, alongside continued use of liquid cooling, a technology Google has adopted for ASICs since 2018. The TPU v7 architecture also heavily leverages optical circuit switching (OCS) to interconnect racks, reducing latency and power consumption while enabling stable, high-bandwidth connections for long-duration AI training workloads.
Each TPU v7 rack contains 64 chips, and clusters can scale to 144 racks, allowing synchronous operation of up to 9,216 TPUs. Fubon estimates Google will deploy approximately 36,000 TPU v7 racks in 2026, requiring over 10,000 optical circuit switches. Power demands are substantial, with per-chip consumption estimated at 850 to 1,000 watts and total rack power reaching up to 100 kilowatts. To manage this, Google is expected to deploy advanced power distribution and battery backup systems.
While total TPU production could reach 3.2 million units in 2026, analysts caution that effective TPU adoption requires deep expertise in Google’s software stack, meaning GPUs will likely remain dominant for most enterprises and developers in the near future.


Nvidia Tightens AI Chip Sales in Asia With Stricter Customer Approval Process
SK Hynix Soars 13% in Nasdaq Debut After Record $26.5 Billion IPO
Elon Musk Says Anthropic Leads AI Race as Claude Models Challenge OpenAI
Samsung Q2 Profit Hits Record on AI Memory Boom as Shares Tumble
Muji Owner Ryohin Keikaku Stock Soars After Raising Full-Year Earnings Forecast
Nippon Paint Reportedly Offers Up to €7.5 Billion for Akzo Nobel Decorative Paints Business
Deutsche Bank Fined A$2 Million by ASIC Over OTC Derivatives Reporting Errors
Morgan Stanley Says China’s Reusable Rocket Progress Poses Long-Term Challenge to SpaceX
Chinese Chip Stocks Jump as Apple Reportedly Tests CXMT Memory Chips for China Devices
OpenAI Executive Fidji Simo to Step Down Amid Health Challenges Ahead of IPO
Yaskawa Electric Shares Slide as Weak Profit Overshadows Strong AI Demand
Meta Says States Seek $1.4 Trillion in Penalties Over Teen Social Media Addiction Lawsuit
Morgan Stanley Names Marks & Spencer Top European Retail Pick, Sees Strong Upside
SoftBank Corp Partners With Sierra to Expand AI Customer Support Across Japan
Apple Tests China's CXMT Memory Chips as DRAM Maker Gains Global Market Share
SK Hynix Shares Drop After Strong Nasdaq Debut Despite $26 Billion ADR Listing 



