Google’s Tensor project was launched with high hopes — to be a secret weapon against Apple’s A-series chips, a unique differentiator from Qualcomm’s Snapdragon and Samsung’s Exynos processors. Four years and five generations later, the question looms large: has Tensor truly lived up to its promise, or has it fallen short? Let’s break down the full story behind Tensor — the compromises, the vision, the wins, and whether Google’s bet on AI over raw performance is the right long-term strategy.
The Case for Failure: Why Tensor Has Struggled to Keep Up
From the outset, Google’s Tensor chips have been behind the curve in terms of pure performance. They have never been the fastest processors in their release year, and persistent issues — from heat management to battery efficiency — have dogged the platform. Even with the Pixel 9, some concerns around power consumption and thermal throttling only started to ease.
More troubling for users were longstanding modem issues affecting connectivity on Pixel devices, problems that lingered until very recently. These challenges highlight a fundamental reality: Google’s Tensor chips have been designed for compromise, not peak performance.
Leaked details reveal that Google isn’t chasing flagship-level performance or investing top dollar in manufacturing. Even the recent switch to TSMC, the industry leader in chip fabrication, doesn’t promise a massive leap forward. While the Tensor G5 chip made with TSMC’s advanced process will be an improvement, it likely won’t match the Snapdragon 8 Elite’s performance.
At its core, Tensor was built around AI — computational photography, machine learning, and unique features that no other platform could deliver. And in that respect, Google has delivered. Many users rave about the Pixel’s photo processing capabilities, which stand out in a crowded market. However, outside of camera innovation, Google hasn’t dominated other smartphone areas, and competition is closing the gap fast.
Without improvements in both AI capabilities and raw performance, Google risks losing its competitive edge in the premium phone segment. Meanwhile, many competitors are delivering similar or better experiences without designing custom chips, raising questions about the necessity of Tensor’s bespoke approach.
The Case for Success: Why Tensor Still Matters
Despite its shortcomings, Tensor has been a commercial success for Google. Pixel sales have grown year-over-year, marking the biggest wins Google has seen in the smartphone market — no small feat given how saturated the space is.
Interestingly, the average user often doesn’t care much about benchmark scores or raw chip speed. What resonates are the tangible, everyday experiences powered by Tensor’s AI: the Magic Eraser, real-time photo enhancements, and other subtle but impactful features. These “small, slower” innovations create moments of delight that influence buying decisions more than peak performance numbers ever could.
Google continues to double down on its custom Tensor Processing Unit (TPU), which drives AI-enhanced features. Looking ahead, leaked rumors suggest ambitious new capabilities such as 100x zoom and ultra-low-light video are on the horizon, promising to keep Pixel devices at the forefront of computational photography.
The TPU’s importance cannot be overstated; it’s becoming one of the most critical performance drivers in modern smartphones. This focus on tightly integrating hardware and software to unlock new user experiences echoes the innovations that brought optical image stabilization and night mode to phones in the past.
Why TSMC Is a Game-Changer for Tensor’s Future
Google’s recent shift to TSMC for Tensor chip manufacturing is a crucial strategic move. TSMC leads the industry in cutting-edge chip fabrication, and this partnership is expected to boost efficiency and performance by 15 to 35 percent over previous Tensor generations.
However, it’s important to temper expectations. A more advanced process alone can’t overcome architectural limitations. Nonetheless, this year’s improvements should be more significant than the incremental gains we’ve seen in the past, setting the stage for stronger future Tensor chips.
Long-Term Vision: Software Support and Integration
One of Tensor’s biggest advantages is software support. Google aims for up to seven years of smartphone updates — a feat difficult to achieve with fragmented hardware like Samsung’s wide array of devices. By controlling both hardware and software, Google can optimize the entire experience, delivering timely updates and unique features that enhance user satisfaction over time.
This long-term approach is the essence of silicon development — a multi-year plan, not a one-off gamble. Entering the fifth generation of Tensor chips, Google is laying a foundation that integrates deeply with upcoming AI models like Gemini, which will be embedded into Pixel devices to further elevate their capabilities.
Has Tensor Failed? A Nuanced Conclusion
So, has Google’s Tensor project failed? The answer isn’t a simple yes or no.
On one hand, Tensor chips haven’t delivered the peak performance that some expected in a $1,000+ premium smartphone. For many buyers, this is a drawback they must accept to enjoy the unique Google features enabled by Tensor.
On the other hand, Tensor has enabled Google to build a cohesive product lineup — including more affordable Pixel A-series phones that benefit from economies of scale by sharing top-tier silicon. This strategy has been a clear success and continues to be an easy recommendation for many users.
In my view, Tensor is more of a development challenge than a failure. The risk lies in Google falling behind in raw performance, potentially allowing competitors to pull far ahead in the coming years. What happens then? That remains an open question for the future.
I’d love to hear your thoughts on Tensor’s journey and what you think lies ahead for Google’s custom silicon. Drop your comments below and let’s start a conversation.
Thanks for reading, and stay tuned for more insights!
