Quick Answer
The Google Tensor G3 is the successor to the Tensor G2, offering a more advanced CPU architecture with a focus on improved AI and machine learning capabilities. While the G3 provides a noticeable boost in general processing power and graphics performance, both chipsets share a core design philosophy centered on enhancing on-device AI features for photography, speech recognition, and security.
Google Tensor G3 vs Google Tensor G2: Full Comparison
Introduction
Understanding the progression from Google Tensor G2 to Tensor G3 is key for anyone interested in the evolution of mobile silicon, particularly in how it powers modern smartphone experiences. This comparison breaks down the technical specifications, architectural changes, and real-world implications of these two system-on-chips (SoCs). By examining aspects like CPU design, GPU performance, AI processing, and manufacturing, readers can gain a clear picture of what each generation offers and how they differ in their approach to mobile computing.
CPU & Performance
The core computing architectures of these two chips represent a significant generational shift.
- Tensor G2: Utilized a CPU cluster with 2x Cortex-X1 cores, 2x Cortex-A78 cores, and 4x Cortex-A55 cores. This was a refined version of the original Tensor’s layout, built on Samsung’s 5nm process technology.
- Tensor G3: Introduces a more modern 9-core CPU configuration: 1x Cortex-X3, 4x Cortex-A715, and 4x Cortex-A510. This move to Arm’s latest v9 architecture cores, fabricated on an improved Samsung 4nm process, typically results in better performance per watt and more efficient multitasking.
In practical terms, the G3 generally provides faster app loading, smoother UI navigation, and better handling of intensive tasks compared to the G2.
GPU & Gaming
Graphical performance sees a notable upgrade with the newer chipset.
- Tensor G2: Employed the Arm Mali-G710 MP7 GPU. This provided capable graphics performance for most mobile games at high settings.
- Tensor G3: Upgrades to the Arm Immortalis-G715 MP10 GPU. This next-generation GPU not only offers higher peak performance but also introduces hardware-based ray tracing support, enabling more realistic lighting and shadows in supported games. The performance uplift is generally noticeable in graphically demanding titles.
AI & Machine Learning (TPU)
This area is the cornerstone of Google’s Tensor philosophy, with both chips featuring a custom-designed Tensor Processing Unit (TPU).
- Shared Focus: Both the G2 and G3 are engineered to accelerate on-device AI and ML tasks. This powers features like advanced computational photography (e.g., Magic Eraser, Photo Unblur), real-time speech recognition and translation, and enhanced security with the Titan M2 security coprocessor.
- Generational Improvement: The Tensor G3’s TPU is a newer, more powerful iteration. It can handle more complex AI models faster and more efficiently. This often translates to quicker processing of photo edits, more accurate live translation, and the enablement of new AI-driven features that require greater computational resources.
Connectivity & Modem
Both chips integrate a modem for cellular connectivity, with the G3 offering a slight generational update.
- Tensor G2: Included the Exynos Modem 5300, which provided support for sub-6GHz and mmWave 5G, Wi-Fi 6E, and Bluetooth 5.2.
- Tensor G3: Integrates the newer Exynos Modem 5400. While core connectivity features like 5G bands remain similar in most regions, the newer modem typically offers improvements in power efficiency and signal stability.
Comparison Table: Google Tensor G3 vs Tensor G2
| Feature | Google Tensor G2 | Google Tensor G3 |
|---|---|---|
| CPU Architecture | 2x Cortex-X1, 2x Cortex-A78, 4x Cortex-A55 (8 cores) | 1x Cortex-X3, 4x Cortex-A715, 4x Cortex-A510 (9 cores) |
| GPU | Arm Mali-G710 MP7 | Arm Immortalis-G715 MP10 (with Ray Tracing) |
| AI Processor | Custom Google TPU (2nd Gen) | Custom Google TPU (3rd Gen, more powerful) |
| Manufacturing Process | Samsung 5nm LPE | Samsung 4nm LPP (4LPP+) |
| Modem | Exynos Modem 5300 (Integrated) | Exynos Modem 5400 (Integrated) |
| Key AI Features | Magic Eraser, Photo Unblur, Live Translate, Face Unblur | All G2 features, plus enhanced versions and new features like Video Boost, Audio Magic Eraser |
| Security | Titan M2 security chip | Titan M2 security chip |
Frequently Asked Questions (FAQ)
What is the main difference between Tensor G3 and G2?
The main differences lie in the CPU and GPU architecture. The Tensor G3 uses newer Arm v9 cores (like Cortex-X3) and a more powerful Immortalis-G715 GPU with ray tracing support, while the G2 uses older v8 architecture cores and a Mali-G710 GPU. The G3’s AI TPU is also more capable.
Does the Tensor G3 have better battery life than the G2?
Battery life depends on many factors, including the device’s screen, battery size, and software optimization. However, the Tensor G3’s move to a more efficient 4nm manufacturing process and modern CPU cores is generally designed to improve power efficiency, which can contribute to better battery life under similar conditions.
Is the AI performance significantly better on the Tensor G3?
Yes, the Tensor G3 features a next-generation Tensor Processing Unit (TPU). This allows it to run more complex machine learning models faster and more efficiently than the G2, enabling new and improved on-device AI features for photography, audio, and video processing.
Can the Tensor G3 handle more demanding games?
Typically, yes. The upgrade to the Arm Immortalis-G715 MP10 GPU provides a clear boost in graphical performance over the G2’s Mali-G710. The addition of hardware-accelerated ray tracing support also future-proofs the chip for games that utilize this technology.
Final Thoughts
The Google Tensor G3 represents a logical and substantial step forward from the Tensor G2. It builds upon the same foundation of prioritizing on-device AI and machine learning but does so with significantly updated core hardware. The shift to a modern CPU cluster and a more advanced GPU provides tangible benefits in general performance and gaming. For users whose priorities include having the latest AI-powered features and the headroom for more demanding applications, the G3 offers clear generational improvements. The Tensor G2 remains a capable chipset that powers a robust suite of AI features, making devices equipped with it still very competent for everyday and photography-focused tasks. The choice in a device often comes down to how much value one places on having the latest silicon advancements versus the capable performance of the previous generation.