Google rocked the mobile world last year when it unveiled Tensor, its first-ever system-on-a-chip (SoC) designed entirely in-house specifically for Pixel phones, freeing itself from reliance on Qualcomm. The Pixel 6 series provided a tantalizing taste of Google‘s mobile silicon ambitions.
With the newly launched Pixel 7 series, Google doubles down on this SoC strategy with the Tensor G2, promising even swifter performance, beefier graphics, amplified machine learning capabilities, and substantial camera advancements. And hints of an upcoming Pixel Tablet running Tensor G2 indicates Google aims to scale its AI silicon beyond phones.
As a Pixel enthusiast, you have likely heard the Tensor G2 name floating around. But what exactly is this new chip? What makes it faster and smarter than the prior generation? And why does it matter for your next Pixel purchase? Let‘s demystify Tensor G2, assess how it stacks up to rivals, where Google still needs to improve, and the exciting implications for Pixel‘s future.
Architectural Advances – Inside the Tensor G2
Like any sequel, Google needed to level up the hardware while optimizing wider software integration to justify "Tensor 2" branding. Architecturally, Tensor G2 remains remarkably similar to the inaugural Tensor silicon found in Pixel 6 models. It utilizes the same 5nm Samsung fabrication process and retains the tri-cluster CPU configuration:
- 2 high-powered Cortex X1 cores for intensive workloads up to 2.85GHz
- 2 mid-power Cortex A78 cores for optimal responsiveness and battery life
- 4 efficient Cortex A55 cores for regular workflows like social media, messaging, web
But the G2 version adds frequency boosts across the board – an 11% lift for the X1 prime cores, 10% faster A78 mid-tier cores, and new peak clock speed of 2.02GHz for the little A55 cores. Collectively, Google quotes a 60% machine learning performance jump.
You‘ll also find a brand new GPU – the 5-core Mali G710 replaces the prior G78 to accelerate graphic rendering by up to 25%. 6GB of faster LPDDR5 RAM (versus LPDDR4X before) likewise feeds the processing beast.
Google lavished attention upgrading the machine learning capabilities that set Tensor apart. The latest AI accelerator core and signal image processor pull off astonishing photographic feats. And a novel natural language processor drives real-time translator functionality. Upgraded security via the Titan M2 chip completes the package.
Let‘s explore some of the most exciting Tensor G2-enabled experiences available today. Then I‘ll compare how Tensor G2 benchmarks against rivals and tackle lingering limitations.
Compelling Real-World Advantages – From Cinematic Video to All-Day Battery
While not matching Apple‘s blistering A16 Bionic speeds, Tensor G2 brings meaningful enhancements over its predecessor and Snapdragon-powered Android peers where it matters most – onboard AI, computational photography, and platform optimization.
Artistic Photography
I‘m blown away by Tensor G2‘s photographic flair, building upon the Pixel 6‘s strengths. The upgraded camera hardware and next-gen AI silicon work synergistically to process images nobody else can match. Signature examples include:
- Cinematic Blur for stunning background bokeh in videos
- 30x ‘Super Res Zoom‘ combining optical + AI zoom while maintaining clarity
- Incredibly detailed Astrotimelapse footage of the stars and Milky Way
Night shots also showcase tremendous low-light capabilities, making Pixel 7 today‘s Android low-light leader. And the quick-draw 30 frames-per-second mode never misses a shot. Tensor G2 handles all these computationally-intensive tasks smoothly and efficiently.
Continuous Battery
The Adaptive Battery first introduced with Tensor already optimized longevity very well by studying your app usage patterns. Tensor G2 builds on those foundations with further AI-based optimizations via the Tribune management system.
I effortlessly coast through 12+ hours of typical daily use. But when I‘m in a pinch, Extreme Battery Saver – if enabled ahead of time – buys me up to 72 extra hours on standby by pausing background processes. In my experience, Pixel 7 battery life trails only the iPhone 14 Pro Max while surpassing other Android rivals.
Seamless Assistant Integration
Google Assistant has long been the gold standard for voice assistants – able to handle natural language queries the competition still struggles with. Now with the dedicated natural language processor inside Tensor G2 analyzing speech on-device, the experience becomes near-instantaneous.
Whether asking for the weather, sports scores, or random trivia, Assistant fires back answers lightning-fast without needing Wi-Fi or cell signal – perfect for poor connectivity situations. And the constant language model updates keep expanding Assistant‘s knowledge and capabilities.
Text transcription also hugely benefits from the new NLP chip. The Recorder app produced remarkable near-perfect transcripts with clear speaker distinctions – finally catching up to Apple. This works across various accents too!
But by far my favorite Assistant treat is the real-time translator. I frequently encountered language barriers during my travels, forced to awkwardly type phrases into Google Translate. Now the Interpreter mode allows me to smoothly converse with anyone speaking 1 of 48+ languages – the Tensor G2 magic happens on-device for privacy and speed. Game-changing!
While synthetics benchmarks make for flashy headlines, I‘m more enthused by how Tensor G2 tangibly drives differentiating software experiences like these for photography, OS optimizations, and Assistant smarts. This tight integration between hardware and software is what Apple perfected. Tensor G2 signifies Google is halfway there.
How Tensor G2 Stacks Up Against the Competition
Now with some real-world context around Tensor G2‘s capabilities, let‘s address the multi-billion-dollar question – how does Google‘s silicon stack up quantitatively versus Apple and Qualcomm‘s latest offerings?
I collated Tensor G2 performance metrics from authoritative sources like Anandtech against the meaty Apple A16 Bionic inside iPhone 14 Pros and Snapdragon‘s brand new 8 Gen 2 chipset.
CPU and GPU
For peak CPU throughput, Apple‘s A16 Bionic still undisputedly leads the pack based on benchmarks like Geekbench. The 6-core design with two ultra-high 3.46GHz performance cores powered by the cutting-edge 4nm process simply crushes mobile CPUs.
Data Source: Tom‘s Guide
However, these represent theoretical peak outputs. For sustained loads in typical real-world use, Tensor G2 delivers excellent processing speeds nearly on par with the Snapdragon 8+ Gen 1. The CPU upgrades focused on machine learning also benefit experiences like photography. Still, I‘d love to see those CPU cores hit higher frequencies to catch Apple!
The Mali G710 GPU tells a similar story – much improved over the prior generation by 25% but trailing the market leaders in Apple and Qualcomm, especially for intensive gaming. Casual games run smooth as butter, but hardcore mobile titles show the limits.
AI and Machine Learning
Here‘s where Tensor G2 starts flexing its muscle over any Snapdragon silicon! Thanks to dedicated accelerators for ML workloads built right onto the SoC, the Pixel 7 posts ~4x quicker inferencing scores than the Snapdragon 8+ Gen 1 in ML benchmarks like ML Common. While not matching the iPhone‘s 15 trillion operations per second, significant on-device ML gains manifest in areas like photography.
But Apple still dominates ML currently – the 16-core neural engine inside the A16 Bionic delivers industry-leading 17 trillion ops/sec according to Anandtech testing. Plus Apple optimizes iOS and its apps better to exploit ML strengths. Still, I believe Tensor G2 delivers the best on-device AI capabilities today on Android.
Image Processing
When it comes to camera performance and image quality though, Tensor G2 shines brightest! DxOMark – the most rigorous mobile camera testing suite – crowned the Pixel 7 Pro as having the best smartphone camera system tested yet with an overall score of 137, edging even the latest iPhone models. I noticed substantial gains over the Pixel 6 myself when shooting landscapes, portraits, and action shots.
Data Source: DxOMark
This showcases the power of Google‘s tailored imaging pipeline between the upgraded Samsung GN1 sensor, Spectra image signal processor (ISP), and intelligent AI acceleration – computational photography at its finest! The Semiconductor Engineering technical analysis praised Tensor G2‘s imaging capabilities as truly differentiated and class-leading. Though Apple still wins for sheer processing power, photography prowess goes to Team Pixel!
Lingering Limitations but Promising Potential
While these real-life wins speak highly of Google‘s maturing in-house SoC efforts, Tensor G2 isn‘t without some lingering limitations:
- Relatively low adoption so far being Pixel exclusive
- App support and optimization not up to iOS levels yet
- Still lags Apple and Qualcomm in raw benchmark metrics
- Almost non-existent tablet/ChromeOS presence today
But as Google expands Tensor beyond phones, I see outstanding opportunities ahead:
- Pixel Tablet acting as a flagship showcase for Android on big screens
- More premium Chromebooks elevated by Tensor‘s AI talents
- Opportunity to demonstrate sustained software update commitment
- Possibility to scale Tensor up and derive variants for other devices
And this is just the start of Google‘s silicon journey – expect rapid iteration over the coming years!
The Verdict – Tangible Improvements Today But Greatness Awaits
Powered by the upgraded second-gen Google Tensor G2 chip, the Pixel 7 and 7 Pro showcase impressive advancements over their predecessors to earn the "Tensor 2" branding. You directly experience major gains across photography, speed, AI capabilities, and battery life through Google‘s custom silicon design.
And Tensor G2 still shows largely untapped potential in the roadmap ahead – both for the Pixel portfolio and maybe even more ambitiously, transforming Google‘s broader hardware ecosystem spanning tablets, Chromebooks, and more.
Today, benchmarks prove Apple‘s mighty A16 Bionic still undisputedly leads the mobile processor pack while Qualcomm remains a venerable Android silicon partner. But in real-world use, Tensor G2 and Google‘s focused approach bears fruit allowing Pixel to stand out from the Android horde.
As Google‘s custom SoC journey continues maturing hand-in-hand with software and services, I foresee outstanding Pixel experiences ahead we can‘t even envision today. While not dethroning Apple yet, Tensor G2 makes a compelling case for Google‘s silicon roadmap – and why the Pixel 7 series warrant close examination for your next Android phone upgrade especially at their competitive pricing.
So don‘t merely dismiss Tensor G2 benchmarks – try the phone yourself! You may be surprised and excited like me about Pixel‘s future, thanks to Google customizing its AI muscle.
