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Home/News/Google Tensor G5 comes on 3nm build and a new GPU
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Google Tensor G5 comes on 3nm build and a new GPU

Robert Haba
Jun 11, 20253 min read
Robert Haba
Robert Haba
Founder · Editor-in-Chief
Robert Haba is the founder and editor-in-chief of Droid Tools. A lifelong gadget enthusiast with over a decade following the Android ecosystem, he built this publication to cut through the noise and give readers honest, real-world coverage of the tech they actually use.
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Key Takeaways

Automated Editorial Synthesis
AI Overview
  • According to reports, Google's Pixel 10 series will use the Tensor G5 as its next processor.
  • According to reports, it will be manufactured under the codename "Laguna" under a multi-year agreement with TSMC, which would completely replace Samsung.
  • There have been major architectural modifications in this flagship processor.

According to reports, Google’s Pixel 10 series will use the Tensor G5 as its next processor. According to reports, it will be manufactured under the codename “Laguna” under a multi-year agreement with TSMC, which would completely replace Samsung. There have been major architectural modifications in this flagship processor.

According to reports, the Google Tensor G5 has an 8-core CPU and makes use of TSMC’s 3nm node. One Cortex-X4 prime core at 3.4 GHz, three to five Cortex-A725 performance cores at roughly 2.85 GHz, and two to four Cortex-A525 efficiency cores at 2.4 GHz are typical configurations, though reports vary significantly. Using the Cortex-A725, the design prioritizes efficiency and long-term performance, which is further improved by the 3nm technology. The goal of switching to more modern efficiency cores is to enhance the user experience in general.

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A single-core score of roughly 1323 and a multi-core score of roughly 4004 are displayed in the leaked Geekbench 6 results. These are preliminary findings, but they fall short of the Tensor G4’s scores (about 1950 single-core and 4741 multi-core).

There is potential for improvement through software optimization, as indicated by projected scores of 2200 single-core and 5700 multi-core, as well as a company objective of maybe surpassing 2300 single-core and 7600+ multi-core. Early software optimization or certain test setups could be the cause of the initial lower scores. In early incarnations, the emphasis on a more efficient production process may put power efficiency ahead of peak performance.

Despite architectural modifications and the switch to a 3nm technology, early benchmarks indicate that the Tensor G5 might not much outperform its predecessor in Geekbench 6. The particular setups of the testing devices or early software optimization may be to blame for this. In early generations, the shift to a more efficient manufacturing process may put power efficiency ahead of peak performance benefits.

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The Tensor G5 is anticipated to include a dual-core Imagination Technologies IMG DXT-48-1536 GPU clocked at 1.1 GHz, whereas the Google Tensor G4 used an Arm Mali-G715 MP7 GPU. This marks a substantial shift away from Google’s prior dependence on Arm Mali GPUs. This points to a change in strategy, either motivated by discontent with Mali’s performance in some domains or a keen interest in the capabilities of the IMG DXT.

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The highest level in the Ray Tracing Level System (RTLS), Level 4 ray tracing, is supported by the IMG DXT GPU, allowing for powerful visuals with low power consumption. This attempts to give the Pixel 10 more lifelike and captivating visual and gaming experiences. Users that value visual quality and game performance will find Level 4 ray tracing’s cutting-edge visuals appealing.

Power efficiency is a key component of the IMG DXT, and its successor, the DXTP, offers up to 20% more power efficiency (FPS/W). Although DXT is used by the Tensor G5, this suggests a common pattern in Imagination’s designs. By switching to IMG DXT, the Pixel 10’s graphics subsystem may become more power efficient, which could solve a persistent problem with Tensor-based devices’ short battery life. A major benefit would be increased power efficiency over the Mali-G715 MP7.

Stay connected with the latest from Droid Tools—follow us on X @droid_tools, like our page on Facebook, check out our updates on Instagram, and follow us on Google News for real-time news, device tips, and mobile tech insights.

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Tags:#cortexgoogle#gpu#pixel#pixel10#soc#tensor#tsmc
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Robert Haba
Robert HabaFounder · Editor-in-Chief
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Robert Haba is the founder and editor-in-chief of Droid Tools. A lifelong gadget enthusiast with over a decade following the Android ecosystem, he built this publication to cut through the noise and give readers honest, real-world coverage of the tech they actually use.

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