Google is set to switch to TSMC for its proprietary Tensor G5 SoC in 2025.
The new report reveals that Google’s switch will also bring a 3nm process to the Tensor G5 in Pixel devices.
Of course, that brings with it more than performance, which is something that the Tensor chipsets lack when placed in competition with Qualcomm and MediaTek.
It brings power efficiency as well.
A representative from a major global foundry company stated, “The main reason big customers choose TSMC is the difference in chip power efficiency offered by both companies at cutting-edge processes.”
The representative also highlighted challenges in heat management. “Heat issues in semiconductors have been a longstanding challenge for leading chip manufacturers over the past 20 years, but it has become a crucial issue with the onset of the AI semiconductor era,” they explained. “In mobile chips, heat issues can compromise the entire structure of smartphones, and for server chips, the heat generated by one server rack can spread like wildfire, potentially causing overload across the entire server.”
Since the debut of the first Tensor chip in the Pixel 6 series in 2021, Google has been using Samsung to produce its subsequent chips.
This was partly because Samsung’s Exynos provided a foundation for Tensor.
However, as Google approaches the tenth Pixel generation, the company is gearing up for a significant change.
As reported in July 2023, Google has struck a deal with TSMC to produce the first fully custom Tensor chip for Pixel devices, likely called Tensor G5 if Google keeps its existing numbering scheme.
Since the initial report, development has continued to progress, including Google locking down testing facilities for the chip.
A recent report offers additional information.
Business Korea reports that Google will be using TSMC’s 3nm process for this upcoming Tensor generation.
Qualcomm will likely be the sole SoC supplier for the Samsung Galaxy S25 (vs. 40% for the S24), as the Exynos 2500 may not ship due to Samsung’s lower-than-expected 3nm yield.
In addition to the significant increase in supply share, Qualcomm’s Snapdragon 8 Gen 4 will see a price…
— 郭明錤 (Ming-Chi Kuo) (@mingchikuo) June 17, 2024
This comes as no surprise, as Apple started leveraging this process on the 2023 iPhone 15 Pro lineup, and both Qualcomm and MediaTek are also expected to adopt the newer process with their upcoming generations.
Analyst Ming-Chi Kuo says that Samsung may end up shifting back to a Snapdragon-only approach for the Galaxy S25 next year.
Why this change?
To few people’s surprise, the report goes on to discuss that Samsung, is struggling with yield and power efficiency issues, including on the upcoming Exynos 2500 chip.
Power consumption and heat performance are said to be about 10-20% lower than TSMC’s 3nm process.
The current Tensor G3 is built on a 4nm Samsung process, and by late-2025, switching to 3nm was inevitable.
Will it improve the performance metrics on the Pixel 10?
That is question which will be answered in due time.
Google is switching to TSMC for its Tensor G5 production due to TSMC’s superior 3nm process, which offers better yield, power efficiency, and performance compared to Samsung’s current capabilities.
The 3nm process will provide significant improvements in performance and power efficiency, making the Tensor G5 more competitive with other high-end SoCs from Qualcomm and MediaTek.
The Tensor G5 is expected to be featured in Pixel devices starting in 2025, likely debuting with the Pixel 10 series.
The Tensor G5, produced using TSMC’s 3nm process, is anticipated to surpass its predecessors in terms of performance, power efficiency, and overall chip yield, addressing previous limitations found in Tensor chips manufactured by Samsung.
Apple has already started using TSMC’s 3nm process for its 2023 iPhone 15 Pro lineup, and both Qualcomm and MediaTek are expected to adopt this advanced process for their upcoming SoCs.
Also Read: Google’s Tensor G5 Chip Could be A New Era for Pixel Phones with Exynos-Free Design
Also Read: Google Pixel 7 Tensor G2 Chip; Speed in Learning Tasks
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